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Ladislav Krištoufek
(Ladislav Kristoufek)

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

RePEc Biblio mentions

As found on the RePEc Biblio, the curated bibliography of Economics:
  1. Ladislav Kristoufek, 2020. "Grandpa, grandpa, tell me the one about Bitcoin being a safe haven: Evidence from the COVID-19 pandemics," Papers 2004.00047, arXiv.org.

    Mentioned in:

    1. > Economics of Welfare > Health Economics > Economics of Pandemics > Specific pandemics > Covid-19 > Economic consequences

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Kristoufek, Ladislav, 2014. "Leverage effect in energy futures," Energy Economics, Elsevier, vol. 45(C), pages 1-9.

    Mentioned in:

    1. Leverage effect in energy futures (Energy Economics 2014) in ReplicationWiki ()
  2. Filip, Ondrej & Janda, Karel & Kristoufek, Ladislav & Zilberman, David, 2019. "Food versus fuel: An updated and expanded evidence," Energy Economics, Elsevier, vol. 82(C), pages 152-166.

    Mentioned in:

    1. Food versus fuel: An updated and expanded evidence (Energy Economics 2019) in ReplicationWiki ()
  3. Kristoufek, Ladislav, 2019. "Are the crude oil markets really becoming more efficient over time? Some new evidence," Energy Economics, Elsevier, vol. 82(C), pages 253-263.

    Mentioned in:

    1. Are the crude oil markets really becoming more efficient over time? Some new evidence (Energy Economics 2019) in ReplicationWiki ()

Working papers

  1. Karel Janda & Ladislav Kristoufek & Binyi Zhang, 2022. "Return and volatility spillovers between Chinese and US clean energy related stocks," CAMA Working Papers 2022-17, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.

    Cited by:

    1. Wei Jiang & Ruijie Gao & Chao Lu, 2022. "The Analysis of Causality and Risk Spillover between Crude Oil and China’s Agricultural Futures," IJERPH, MDPI, vol. 19(17), pages 1-16, August.
    2. Bai, Lan & Wei, Yu & Zhang, Jiahao & Wang, Yizhi & Lucey, Brian M., 2023. "Diversification effects of China's carbon neutral bond on renewable energy stock markets: A minimum connectedness portfolio approach," Energy Economics, Elsevier, vol. 123(C).
    3. Susovon Jana & Tarak N. Sahu, 2023. "Is the cryptocurrency market a hedge against stock market risk? A Wavelet and GARCH approach," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 52(3), November.
    4. Li, Hailing & Li, Yuxin & Zhang, Hua, 2023. "The spillover effects among the traditional energy markets, metal markets and sub-sector clean energy markets," Energy, Elsevier, vol. 275(C).
    5. Ahmed, Walid M.A. & Sleem, Mohamed A.E., 2023. "Short- and long-run determinants of the price behavior of US clean energy stocks: A dynamic ARDL simulations approach," Energy Economics, Elsevier, vol. 124(C).
    6. Gong, Xiao-Li & Zhao, Min & Wu, Zhuo-Cheng & Jia, Kai-Wen & Xiong, Xiong, 2023. "Research on tail risk contagion in international energy markets—The quantile time-frequency volatility spillover perspective," Energy Economics, Elsevier, vol. 121(C).
    7. Vilija Aleknevičien&# & Asta Bendoraityt&#, 2023. "Role of Green Finance in Greening the Economy: Conceptual Approach," Central European Business Review, Prague University of Economics and Business, vol. 2023(2), pages 105-130.
    8. Su, Xianfang & Zhao, Yachao, 2023. "What has the strongest connectedness with clean energy? Technology, substitutes, or raw materials," Energy Economics, Elsevier, vol. 128(C).
    9. Qi, Haozhi & Ma, Lijun & Peng, Pin & Chen, Hao & Li, Kang, 2022. "Dynamic connectedness between clean energy stock markets and energy commodity markets during times of COVID-19: Empirical evidence from China," Resources Policy, Elsevier, vol. 79(C).
    10. Xiaohong Qi & Guofu Zhang & Yuqi Wang, 2022. "Distributional Predictability and Quantile Connectedness of New Energy, Steam Coal, and High-Tech in China," Sustainability, MDPI, vol. 14(21), pages 1-16, October.
    11. Banerjee, Ameet Kumar & Sensoy, Ahmet & Goodell, John W., 2024. "Connectivity and spillover during crises: Highlighting the prominent and growing role of green energy," Energy Economics, Elsevier, vol. 129(C).
    12. Cheikh, Nidhaleddine Ben & Zaied, Younes Ben, 2023. "Investigating the dynamics of crude oil and clean energy markets in times of geopolitical tensions," Energy Economics, Elsevier, vol. 124(C).
    13. Deng, Jing & Xu, Zihan & Xing, Xiaoyun, 2023. "Dynamic spillovers between clean energy and non-ferrous metals markets in China: A network-based analysis during the COVID-19 pandemic," Resources Policy, Elsevier, vol. 83(C).
    14. Oktay Ozkan & Salah Abosedra & Arshian Sharif & Andrew Adewale Alola, 2024. "Dynamic volatility among fossil energy, clean energy and major assets: evidence from the novel DCC-GARCH," Economic Change and Restructuring, Springer, vol. 57(3), pages 1-19, June.
    15. Zhang, Yunhan & Li, Yan & Zhao, Wanli & Ji, Qiang, 2024. "Climate risk performance and returns integration of Chinese listed energy companies," Energy Economics, Elsevier, vol. 129(C).
    16. Hleil Alrweili & Ousama Ben-Salha, 2024. "Dynamic Asymmetric Volatility Spillover and Connectedness Network Analysis among Sectoral Renewable Energy Stocks," Mathematics, MDPI, vol. 12(12), pages 1-20, June.

  2. Karel Janda & Ladislav Kristoufek & Binyi Zhang, 2021. "Return and volatility spillovers between Chinese and U.S. Clean Energy Related Stocks: Evidence from VAR-MGARCH estimations," FFA Working Papers 4.001, Prague University of Economics and Business, revised 17 Jan 2022.

    Cited by:

    1. Wei Jiang & Ruijie Gao & Chao Lu, 2022. "The Analysis of Causality and Risk Spillover between Crude Oil and China’s Agricultural Futures," IJERPH, MDPI, vol. 19(17), pages 1-16, August.
    2. Li, Hailing & Li, Yuxin & Zhang, Hua, 2023. "The spillover effects among the traditional energy markets, metal markets and sub-sector clean energy markets," Energy, Elsevier, vol. 275(C).
    3. Ahmed, Walid M.A. & Sleem, Mohamed A.E., 2023. "Short- and long-run determinants of the price behavior of US clean energy stocks: A dynamic ARDL simulations approach," Energy Economics, Elsevier, vol. 124(C).
    4. Vilija Aleknevičien&# & Asta Bendoraityt&#, 2023. "Role of Green Finance in Greening the Economy: Conceptual Approach," Central European Business Review, Prague University of Economics and Business, vol. 2023(2), pages 105-130.
    5. Qi, Haozhi & Ma, Lijun & Peng, Pin & Chen, Hao & Li, Kang, 2022. "Dynamic connectedness between clean energy stock markets and energy commodity markets during times of COVID-19: Empirical evidence from China," Resources Policy, Elsevier, vol. 79(C).
    6. Xiaohong Qi & Guofu Zhang & Yuqi Wang, 2022. "Distributional Predictability and Quantile Connectedness of New Energy, Steam Coal, and High-Tech in China," Sustainability, MDPI, vol. 14(21), pages 1-16, October.
    7. Banerjee, Ameet Kumar & Sensoy, Ahmet & Goodell, John W., 2024. "Connectivity and spillover during crises: Highlighting the prominent and growing role of green energy," Energy Economics, Elsevier, vol. 129(C).
    8. Cheikh, Nidhaleddine Ben & Zaied, Younes Ben, 2023. "Investigating the dynamics of crude oil and clean energy markets in times of geopolitical tensions," Energy Economics, Elsevier, vol. 124(C).
    9. Deng, Jing & Xu, Zihan & Xing, Xiaoyun, 2023. "Dynamic spillovers between clean energy and non-ferrous metals markets in China: A network-based analysis during the COVID-19 pandemic," Resources Policy, Elsevier, vol. 83(C).
    10. Oktay Ozkan & Salah Abosedra & Arshian Sharif & Andrew Adewale Alola, 2024. "Dynamic volatility among fossil energy, clean energy and major assets: evidence from the novel DCC-GARCH," Economic Change and Restructuring, Springer, vol. 57(3), pages 1-19, June.
    11. Zhang, Yunhan & Li, Yan & Zhao, Wanli & Ji, Qiang, 2024. "Climate risk performance and returns integration of Chinese listed energy companies," Energy Economics, Elsevier, vol. 129(C).

  3. Jaroslav Pavlicek & Ladislav Kristoufek, 2019. "Modeling UK Mortgage Demand Using Online Searches," Working Papers IES 2019/18, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Jul 2019.

    Cited by:

    1. Jean-Charles Bricongne & Baptiste Meunier & Sylvain Pouget, 2023. "Web-scraping housing prices in real-time: The Covid-19 crisis in the UK," SciencePo Working papers Main hal-04064185, HAL.

  4. Karel Janda & Ladislav Kristoufek, 2019. "The relationship between fuel and food prices: Methods, outcomes, and lessons for commodity price risk management," CAMA Working Papers 2019-20, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.

    Cited by:

    1. Ji, Qiang & Bouri, Elie & Roubaud, David & Kristoufek, Ladislav, 2019. "Information interdependence among energy, cryptocurrency and major commodity markets," Energy Economics, Elsevier, vol. 81(C), pages 1042-1055.
    2. Zhuo Chen & Bo Yan & Hanwen Kang, 2022. "Dynamic correlation between crude oil and agricultural futures markets," Review of Development Economics, Wiley Blackwell, vol. 26(3), pages 1798-1849, August.
    3. Sergio Adriani David & Claudio M. C. Inácio & José A. Tenreiro Machado, 2019. "Ethanol Prices and Agricultural Commodities: An Investigation of Their Relationship," Mathematics, MDPI, vol. 7(9), pages 1-25, August.
    4. Bilgili, Faik & Koçak, Emrah & Kuşkaya, Sevda & Bulut, Ümit, 2020. "Estimation of the co-movements between biofuel production and food prices: A wavelet-based analysis," Energy, Elsevier, vol. 213(C).

  5. Ladislav Kristoufek, 2018. "Power-law cross-correlations: Issues, solutions and future challenges," Papers 1806.01616, arXiv.org.

    Cited by:

    1. Zhai, Lu-Sheng & Liu, Ruo-Yu, 2019. "Local detrended cross-correlation analysis for non-stationary time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 222-233.

  6. Ladislav Kristoufek, 2018. "Are the Crude Oil Markets Really Becoming More Efficient over Time? Some New Evidence," Working Papers IES 2018/07, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Feb 2018.

    Cited by:

    1. Sattarhoff, Cristina & Gronwald, Marc, 2022. "Measuring informational efficiency of the European carbon market — A quantitative evaluation of higher order dependence," International Review of Financial Analysis, Elsevier, vol. 84(C).
    2. Corzo Santamaría, Teresa & Martin-Bujack, Karin & Portela, Jose & Sáenz-Diez, Rocio, 2022. "Early market efficiency testing among hydrogen players," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 723-742.
    3. Daniele Valenti & Andrea Bastianin & Matteo Manera, 2022. "A weekly structural VAR model of the US crude oil market," Working Papers 2022.11, Fondazione Eni Enrico Mattei.
    4. Matthieu Garcin, 2018. "Hurst exponents and delampertized fractional Brownian motions," Working Papers hal-01919754, HAL.
    5. Marc Gronwald & Sania Wadud & Kingsley Dogah, 2024. "Informational Efficiency of World Oil Markets: One Great Pool, but with Varying Depth," CESifo Working Paper Series 11017, CESifo.
    6. Cao, K.H. & Qi, H.S. & Tsai, C.H. & Woo, C.K. & Zarnikau, J., 2021. "Energy trading efficiency in the US Midcontinent electricity markets," Applied Energy, Elsevier, vol. 302(C).
    7. Wang, Xiaoyang, 2022. "Efficient markets are more connected: An entropy-based analysis of the energy, industrial metal and financial markets," Energy Economics, Elsevier, vol. 111(C).
    8. Li, Wenhui & Zhu, Qi & Wen, Fenghua & Nor, Normaziah Mohd, 2022. "The evolution of day-of-the-week and the implications in crude oil market," Energy Economics, Elsevier, vol. 106(C).
    9. A. Gómez-Águila & J. E. Trinidad-Segovia & M. A. Sánchez-Granero, 2022. "Improvement in Hurst exponent estimation and its application to financial markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-21, December.
    10. Marc Gronwald & Sania Wadud & Kingsley Dogah, 2024. "Oil Market Efficiency, Quantity of Information, and Oil Market Turbulence," CESifo Working Paper Series 10995, CESifo.
    11. Espinosa-Paredes, G. & Rodriguez, E. & Alvarez-Ramirez, J., 2022. "A singular value decomposition entropy approach to assess the impact of Covid-19 on the informational efficiency of the WTI crude oil market," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    12. Tiwari, Aviral Kumar & Abakah, Emmanuel Joel Aikins & Mefteh-Wali, Salma & Owusu, Patrick, 2023. "Measuring price efficiency in petroleum markets: New insights using various long-range dependence techniques," Resources Policy, Elsevier, vol. 82(C).

  7. Ondrej Filip & Karel Janda & Ladislav Kristoufek & David Zilberman, 2017. "Food versus fuel: An updated and expanded evidence," CAMA Working Papers 2017-73, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.

    Cited by:

    1. Declerck, Francis & Indjehagopian, Jean-Pierre & Lantz, Frédéric, 2020. "Dynamics of biofuel prices on the European market: Impact of the EU environmental policy on the resources markets," ESSEC Working Papers WP2003, ESSEC Research Center, ESSEC Business School, revised 21 Feb 2020.
    2. Baum, Daniela & Spann, Martin & Füller, Johann & Thürridl, Carina, 2019. "The impact of social media campaigns on the success of new product introductions," Journal of Retailing and Consumer Services, Elsevier, vol. 50(C), pages 289-297.
    3. Gbadebo A. Oladosu & Keith L. Kline & Johannes W. A. Langeveld, 2021. "Structural Break and Causal Analyses of U.S. Corn Use for Ethanol and Other Corn Market Variables," Agriculture, MDPI, vol. 11(3), pages 1-15, March.
    4. Yoon, Seong-Min, 2022. "On the interdependence between biofuel, fossil fuel and agricultural food prices: Evidence from quantile tests," Renewable Energy, Elsevier, vol. 199(C), pages 536-545.
    5. Lundberg, Liv & Cintas Sanchez, Olivia & Zetterholm, Jonas, 2023. "The impact of blending mandates on biofuel consumption, production, emission reductions and fuel prices," Energy Policy, Elsevier, vol. 183(C).
    6. Tiwari, Aviral Kumar & Nasreen, Samia & Shahbaz, Muhammad & Hammoudeh, Shawkat, 2020. "Time-frequency causality and connectedness between international prices of energy, food, industry, agriculture and metals," Energy Economics, Elsevier, vol. 85(C).
    7. Kayisoglu, Gizem & Gunes, Bunyamin & Besikci, Elif Bal, 2022. "SLIM based methodology for human error probability calculation of bunker spills in maritime operations," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    8. A. Alcantara & F. J. Lopez-Gimenez & M. P. Dorado, 2020. "Universal Kinetic Model to Simulate Two-Step Biodiesel Production from Vegetable Oil," Energies, MDPI, vol. 13(11), pages 1-15, June.
    9. Gabriel E. Lade & C.-Y. Cynthia Lin Lawell, 2021. "The Design of Renewable Fuel Mandates and Cost Containment Mechanisms," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 79(2), pages 213-247, June.
    10. Guo, Jin & Tanaka, Tetsuji, 2022. "Energy security versus food security: An analysis of fuel ethanol- related markets using the spillover index and partial wavelet coherence approaches," Energy Economics, Elsevier, vol. 112(C).
    11. Abubakari Ahmed & Eric Dompreh & Alexandros Gasparatos, 2019. "Human wellbeing outcomes of involvement in industrial crop production: Evidence from sugarcane, oil palm and jatropha sites in Ghana," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-33, April.
    12. Schulz, Nicolai & Proestou, Maria & Feindt, Peter, 2023. "Resilience Challenge Salience in Bioeconomy Policies: A Global Analysis," SocArXiv rp2by, Center for Open Science.
    13. Francis Declerck & Jean-Pierre Indjehagopian & Frédéric Lantz, 2020. "Dynamics of Biofuel Prices on the European Market : Impact of the EU Environmental policy on the resources markets," Working Papers hal-03193880, HAL.
    14. Ji, Qiang & Bouri, Elie & Roubaud, David & Kristoufek, Ladislav, 2019. "Information interdependence among energy, cryptocurrency and major commodity markets," Energy Economics, Elsevier, vol. 81(C), pages 1042-1055.
    15. Zhuo Chen & Bo Yan & Hanwen Kang, 2022. "Dynamic correlation between crude oil and agricultural futures markets," Review of Development Economics, Wiley Blackwell, vol. 26(3), pages 1798-1849, August.
    16. Douvartzides, Savvas & Charisiou, Nikolaos D. & Wang, Wen & Papadakis, Vagelis G. & Polychronopoulou, Kyriaki & Goula, Maria A., 2022. "Catalytic fast pyrolysis of agricultural residues and dedicated energy crops for the production of high energy density transportation biofuels. Part I: Chemical pathways and bio-oil upgrading," Renewable Energy, Elsevier, vol. 185(C), pages 483-505.
    17. Gabriela N. Tenea & Fabricio Veintimilla, 2021. "Potential Use of Native Yeasts to Produce Bioethanol and Other Byproducts from Black Sugarcane, an Alternative to Increment the Subsistence Farming in Northern Ecuador," Sustainability, MDPI, vol. 13(19), pages 1-15, September.
    18. Karel Janda & Ladislav Kristoufek, 2019. "The relationship between fuel and food prices: Methods, outcomes, and lessons for commodity price risk management," CAMA Working Papers 2019-20, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    19. Liya Hau & Huiming Zhu & Muhammad Shahbaz & Ke Huang, 2023. "Quantile Dependence between Crude Oil and China’s Biofuel Feedstock Commodity Market," Sustainability, MDPI, vol. 15(11), pages 1-17, June.
    20. Conteratto, Caroline & Artuzo, Felipe Dalzotto & Benedetti Santos, Omar Inácio & Talamini, Edson, 2021. "Biorefinery: A comprehensive concept for the sociotechnical transition toward bioeconomy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    21. Martin Kügemann & Heracles Polatidis, 2022. "Methodological Framework to Select Evaluation Criteria for Multi-Criteria Decision Analysis of Road Transportation Fuels and Vehicles," Energies, MDPI, vol. 15(14), pages 1-18, July.
    22. Deepayan Debnath & Madhu Khanna & Deepak Rajagopal & David Zilberman, 2019. "The Future of Biofuels in an Electrifying Global Transportation Sector: Imperative, Prospects and Challenges," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 41(4), pages 563-582, December.
    23. Dervis Kirikkaleli & Ibrahim Darbaz, 2021. "The Causal Linkage between Energy Price and Food Price," Energies, MDPI, vol. 14(14), pages 1-13, July.
    24. Benes, Ondrej & Janda, Karel, 2022. "Environmental Dimensions of Biofuels," EconStor Preprints 259403, ZBW - Leibniz Information Centre for Economics.
    25. Tanaka, Tetsuji & Guo, Jin & Wang, Xiufang, 2023. "Did biofuel production strengthen the comovements between food and fuel prices? Evidence from ethanol-related markets in the United States," Renewable Energy, Elsevier, vol. 217(C).
    26. Ondřej Filip & Karel Janda & Ladislav Krištoufek, 2018. "Ceny biopaliv a souvisejících komodit: analýza s použitím metod minimální kostry grafu a hierarchických stromů [Prices of Biofuels and Related Commodities: an Analysis Using Methods of Minimum Span," Politická ekonomie, Prague University of Economics and Business, vol. 2018(2), pages 218-239.
    27. Aviral Kumar Tiwari & Rabeh Khalfaoui & Sakiru Adebola Solarin & Muhammad Shahbaz, 2018. "Analyzing the time-frequency lead–lag relationship between oil and agricultural commodities," Post-Print hal-03797590, HAL.
    28. Curtis McKnight & Feng Qiu & Marty Luckert & Grant Hauer, 2021. "Prices for a second‐generation biofuel industry in Canada: Market linkages between Canadian wheat and US energy and agricultural commodities," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 69(3), pages 337-351, September.
    29. Busquet, Milande & Bosma, Niels & Hummels, Harry, 2021. "A multidimensional perspective on child labor in the value chain: The case of the cocoa value chain in West Africa," World Development, Elsevier, vol. 146(C).

  8. Ladislav Kristoufek, 2016. "Fractal approach towards power-law coherency to measure cross-correlations between time series," Papers 1608.06781, arXiv.org, revised Feb 2017.

    Cited by:

    1. Wang, Luo-Qing & Xu, Yong-Xiang, 2018. "Assessing the relevance of individual characteristics for the structure of similarity networks in new social strata in Shanghai," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 881-889.
    2. Zhang, Wei & Wang, Pengfei & Li, Xiao & Shen, Dehua, 2018. "The inefficiency of cryptocurrency and its cross-correlation with Dow Jones Industrial Average," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 658-670.

  9. Kristoufek, Ladislav & Vošvrda, Miloslav S., 2016. "Herding, minority game, market clearing and efficient markets in a simple spin model framework," FinMaP-Working Papers 68, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.

    Cited by:

    1. Xin-Jie Zhang & Yong Tang & Jason Xiong & Wei-Jia Wang & Yi-Cheng Zhang, 2018. "Dynamics of Cooperation in Minority Games in Alliance Networks," Sustainability, MDPI, vol. 10(12), pages 1-17, December.

  10. Ladislav Kristoufek, 2016. "Power-law cross-correlations estimation under heavy tails," Papers 1602.05385, arXiv.org, revised Apr 2016.

    Cited by:

    1. Qin, Jing & Ge, Jintian & Lu, Xinsheng, 2018. "The effectiveness of the monetary policy in China: New evidence from long-range cross-correlation analysis and the components of multifractality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 1026-1037.
    2. Tomiwa Sunday Adebayo & Dervis Kirikkaleli, 2021. "Impact of renewable energy consumption, globalization, and technological innovation on environmental degradation in Japan: application of wavelet tools," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(11), pages 16057-16082, November.
    3. Xi, Caiping & Zhang, Shuning & Xiong, Gang & Zhao, Huichang & Yang, Yonghong, 2017. "The application of the multifractal cross-correlation analysis methods in radar target detection within sea clutter," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 839-854.
    4. Ladislav Kristoufek, 2018. "Power-law cross-correlations: Issues, solutions and future challenges," Papers 1806.01616, arXiv.org.
    5. Fernández-Martínez, M. & Sánchez-Granero, M.A. & Casado Belmonte, M.P. & Trinidad Segovia, J.E., 2020. "A note on power-law cross-correlated processes," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    6. Cao, Guangxi & Shi, Yingying, 2017. "Simulation analysis of multifractal detrended methods based on the ARFIMA process," Chaos, Solitons & Fractals, Elsevier, vol. 105(C), pages 235-243.
    7. Zhang, Wei & Wang, Pengfei & Li, Xiao & Shen, Dehua, 2018. "The inefficiency of cryptocurrency and its cross-correlation with Dow Jones Industrial Average," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 658-670.

  11. Ondrej Filip & Karel Janda & Ladislav Kristoufek & David Zilberman, 2016. "Foods, fuels or finances: Which prices matter for biofuels?," CAMA Working Papers 2016-63, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.

    Cited by:

    1. Václav Brož & Lukáš Pfeifer, 2021. "Are risk weights of banks in the Czech Republic procyclical? Evidence from wavelet analysis," Journal of Central Banking Theory and Practice, Central bank of Montenegro, vol. 10(1), pages 113-139.

  12. Pavlicek, Jaroslav & Kristoufek, Ladislav, 2015. "Nowcasting unemployment rates with Google searches: Evidence from the Visegrad Group countries," FinMaP-Working Papers 34, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.

    Cited by:

    1. Havranek, Tomas & Zeynalov, Ayaz, 2018. "Forecasting Tourist Arrivals with Google Trends and Mixed Frequency Data," EconStor Preprints 187420, ZBW - Leibniz Information Centre for Economics.
    2. Rodrigo Mulero & Alfredo García-Hiernaux, 2021. "Forecasting Spanish unemployment with Google Trends and dimension reduction techniques," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 12(3), pages 329-349, September.
    3. Havranek, Tomas & Zeynalov, Ayaz, 2018. "Forecasting Tourist Arrivals: Google Trends Meets Mixed Frequency Data," MPRA Paper 90205, University Library of Munich, Germany.
    4. Jianchun Fang & Wanshan Wu & Zhou Lu & Eunho Cho, 2019. "Using Baidu Index To Nowcast Mobile Phone Sales In China," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 64(01), pages 83-96, March.
    5. Nikolaos Askitas, 2015. "Google search activity data and breaking trends," IZA World of Labor, Institute of Labor Economics (IZA), pages 206-206, November.
    6. Chiara Sotis, 2021. "How do Google searches for symptoms, news and unemployment interact during COVID-19? A Lotka–Volterra analysis of google trends data," Quality & Quantity: International Journal of Methodology, Springer, vol. 55(6), pages 2001-2016, December.
    7. Samvel S. Lazaryan & Nikita E. German, 2018. "Forecasting Current GDP Dynamics With Google Search Data," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 6, pages 83-94, December.
    8. Simionescu, Mihaela & Zimmermann, Klaus F., 2017. "Big Data and Unemployment Analysis," GLO Discussion Paper Series 81, Global Labor Organization (GLO).
    9. Pater, Robert & Szkola, Jaroslaw & Kozak, Marcin, 2019. "A method for measuring detailed demand for workers' competences," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 13, pages 1-30.
    10. Tuhkuri, Joonas, 2016. "ETLAnow: A Model for Forecasting with Big Data – Forecasting Unemployment with Google Searches in Europe," ETLA Reports 54, The Research Institute of the Finnish Economy.
    11. Federico Botta & Helen Susannah Moat & Tobias Preis, 2020. "Measuring the size of a crowd using Instagram," Environment and Planning B, , vol. 47(9), pages 1690-1703, November.
    12. Simionescu, Mihaela & Raišienė, Agota Giedrė, 2021. "A bridge between sentiment indicators: What does Google Trends tell us about COVID-19 pandemic and employment expectations in the EU new member states?," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    13. Abay,Kibrom A. & Hirfrfot,Kibrom Tafere & Woldemichael,Andinet, 2020. "Winners and Losers from COVID-19 : Global Evidence from Google Search," Policy Research Working Paper Series 9268, The World Bank.
    14. Gulsah Senturk, 2022. "Can Google Search Data Improve the Unemployment Rate Forecasting Model? An Empirical Analysis for Turkey," Journal of Economic Policy Researches, Istanbul University, Faculty of Economics, vol. 9(2), pages 229-244, July.
    15. Mihaela, Simionescu, 2020. "Improving unemployment rate forecasts at regional level in Romania using Google Trends," Technological Forecasting and Social Change, Elsevier, vol. 155(C).
    16. Rodrigo Mulero & Alfredo Garcia-Hiernaux, 2023. "Forecasting unemployment with Google Trends: age, gender and digital divide," Empirical Economics, Springer, vol. 65(2), pages 587-605, August.
    17. Tierney, Heather L.R. & Kim, Jiyoon (June) & Nazarov, Zafar, 2018. "The Effects of Temporal Aggregation on Search Engine Data," MPRA Paper 84474, University Library of Munich, Germany.
    18. Nakamura, Nobuyuki & Suzuki, Aya, 2021. "COVID-19 and the intentions to migrate from developing countries: Evidence from online search activities in Southeast Asia," Journal of Asian Economics, Elsevier, vol. 76(C).
    19. M. Elshendy & A. Fronzetti Colladon & E. Battistoni & P. A. Gloor, 2021. "Using four different online media sources to forecast the crude oil price," Papers 2105.09154, arXiv.org.

  13. Ladislav Kristoufek, 2015. "Power-law correlations in finance-related Google searches, and their cross-correlations with volatility and traded volume: Evidence from the Dow Jones Industrial components," Papers 1502.00225, arXiv.org.

    Cited by:

    1. Aharon, David Y. & Qadan, Mahmoud, 2020. "When do retail investors pay attention to their trading platforms?," The North American Journal of Economics and Finance, Elsevier, vol. 53(C).
    2. Lahmiri, Salim, 2017. "On fractality and chaos in Moroccan family business stock returns and volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 29-39.
    3. Mario Maggi & Pierpaolo Uberti, 2021. "Google search volumes for portfolio management: performances and asset concentration," Annals of Operations Research, Springer, vol. 299(1), pages 163-175, April.
    4. Ferreira, Paulo & Kristoufek, Ladislav, 2020. "Uncovered interest rate parity through the lens of fractal methods: Evidence from the European Union," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 553(C).
    5. Teng, Yue & Shang, Pengjian, 2018. "Detrended fluctuation analysis based on higher-order moments of financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 311-322.
    6. Prakash Ranjan, Ravi & Bhattachharyya, Malay, 2018. "Does investor attention to energy stocks exhibit power law?," Energy Economics, Elsevier, vol. 75(C), pages 573-582.
    7. Aharon, David Y. & Qadan, Mahmoud, 2018. "What drives the demand for information in the commodity market?," Resources Policy, Elsevier, vol. 59(C), pages 532-543.
    8. Sukpitak, Jessada & Hengpunya, Varagorn, 2016. "The influence of trading volume on market efficiency: The DCCA approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 458(C), pages 259-265.
    9. Wang, Hong-Yong & Wang, Tong-Tong, 2018. "Multifractal analysis of the Chinese stock, bond and fund markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 280-292.
    10. Fan, Xiaoqian & Yuan, Ying & Zhuang, Xintian & Jin, Xiu, 2017. "Long memory of abnormal investor attention and the cross-correlations between abnormal investor attention and trading volume, volatility respectively," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 323-333.
    11. Mišečka, Tomáš & Ciaian, Pavel & Rajčániová, Miroslava & Pokrivčák, Jan, 2019. "In search of attention in agricultural commodity markets," Economics Letters, Elsevier, vol. 184(C).
    12. Zhang, Wei & Wang, Pengfei & Li, Xiao & Shen, Dehua, 2018. "Quantifying the cross-correlations between online searches and Bitcoin market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 657-672.
    13. Lima, Cristiane Rocha Albuquerque & de Melo, Gabriel Rivas & Stosic, Borko & Stosic, Tatijana, 2019. "Cross-correlations between Brazilian biofuel and food market: Ethanol versus sugar," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 687-693.
    14. Zhang, Wei & Wang, Pengfei & Li, Xiao & Shen, Dehua, 2018. "The inefficiency of cryptocurrency and its cross-correlation with Dow Jones Industrial Average," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 658-670.

  14. Vakrman, Tomas & Kristoufek, Ladislav, 2015. "Underpricing, underperformance and overreaction in initial pubic offerings: Evidence from investor attention using online searches," FinMaP-Working Papers 35, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.

    Cited by:

    1. Zhang, Wei & Li, Xiao & Shen, Dehua & Teglio, Andrea, 2016. "Daily happiness and stock returns: Some international evidence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 460(C), pages 201-209.
    2. Xiong, Xiong & Bian, Yuxiang & Shen, Dehua, 2018. "The time-varying correlation between policy uncertainty and stock returns: Evidence from China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 413-419.
    3. Shen, Dehua & Liu, Lanbiao & Zhang, Yongjie, 2018. "Quantifying the cross-sectional relationship between online sentiment and the skewness of stock returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 928-934.
    4. Shen, Dehua & Li, Xiao & Xue, Mei & Zhang, Wei, 2017. "Does microblogging convey firm-specific information? Evidence from China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 621-626.
    5. Zhang, Yongjie & Zhang, Yuzhao & Shen, Dehua & Zhang, Wei, 2017. "Investor sentiment and stock returns: Evidence from provincial TV audience rating in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 288-294.

  15. Ladislav Kristoufek & Karel Janda & David Zilberman, 2015. "Co-movements of Ethanol Related Prices: Evidence from Brazil and the USA," CAMA Working Papers 2015-11, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.

    Cited by:

    1. Capitani, Daniel Henrique Dario & Tonin, Julyerme M. & Cruz, Jose Cesar, 2017. "Integration and hedging efficiency between the Brazilian and the U.S. ethanol markets," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258520, Agricultural and Applied Economics Association.
    2. Aloisio S. Nascimento Filho & Hugo Saba & Rafael G. O. dos Santos & João Gabriel A. Calmon & Marcio L. V. Araújo & Eduardo M. F. Jorge & Thiago B. Murari, 2021. "Analysis of Hydrous Ethanol Price Competitiveness after the Implementation of the Fossil Fuel Import Price Parity Policy in Brazil," Sustainability, MDPI, vol. 13(17), pages 1-12, September.
    3. Nigatu, Getachew & Adjemian, Michael K., 2016. "The U.S. Role in the Price Determination of Major Agricultural Commodities," 2017 Allied Social Sciences Association (ASSA) Annual Meeting, January 6-8, 2017, Chicago, Illinois 250119, Agricultural and Applied Economics Association.
    4. Tan Ngoc Vu & Duc Hong Vo & Chi Minh Ho & Loan Thi-Hong Van, 2019. "Modeling the Impact of Agricultural Shocks on Oil Price in the US: A New Approach," JRFM, MDPI, vol. 12(3), pages 1-27, September.
    5. Sergio Adriani David & Claudio M. C. Inácio & José A. Tenreiro Machado, 2019. "Ethanol Prices and Agricultural Commodities: An Investigation of Their Relationship," Mathematics, MDPI, vol. 7(9), pages 1-25, August.
    6. Ondřej Filip & Karel Janda & Ladislav Krištoufek, 2018. "Ceny biopaliv a souvisejících komodit: analýza s použitím metod minimální kostry grafu a hierarchických stromů [Prices of Biofuels and Related Commodities: an Analysis Using Methods of Minimum Span," Politická ekonomie, Prague University of Economics and Business, vol. 2018(2), pages 218-239.
    7. Derick David Quintino & Heloisa Lee Burnquist & Paulo Jorge Silveira Ferreira, 2021. "Carbon Emissions and Brazilian Ethanol Prices: Are They Correlated? An Econophysics Study," Sustainability, MDPI, vol. 13(22), pages 1-18, November.

  16. Michal Paulus & Ladislav Kristoufek, 2015. "Worldwide clustering of the corruption perception," Papers 1502.00104, arXiv.org.

    Cited by:

    1. Massimo Buscema & Pier Luigi Sacco & Guido Ferilli, 2016. "Multidimensional Similarities at a Global Scale: An Approach to Mapping Open Society Orientations," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 128(3), pages 1239-1258, September.
    2. Budsaratragoon, Pornanong & Jitmaneeroj, Boonlert, 2020. "A critique on the Corruption Perceptions Index: An interdisciplinary approach," Socio-Economic Planning Sciences, Elsevier, vol. 70(C).

  17. Ladislav Kristoufek & Miloslav Vosvrda, 2015. "Gold, currencies and market efficiency," Papers 1510.08615, arXiv.org.

    Cited by:

    1. Khalfaoui, Rabeh, 2018. "Oil–gold time varying nexus: A time–frequency analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 86-104.
    2. Ferreira, Paulo & Kristoufek, Ladislav, 2017. "What is new about covered interest parity condition in the European Union? Evidence from fractal cross-correlation regressions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 554-566.
    3. Stosic, Darko & Stosic, Dusan & Ludermir, Teresa B. & Stosic, Tatijana, 2018. "Nonextensive triplets in cryptocurrency exchanges," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 1069-1074.
    4. Fernandes, Leonardo H.S. & Araújo, Fernando H.A., 2020. "Taxonomy of commodities assets via complexity-entropy causality plane," Chaos, Solitons & Fractals, Elsevier, vol. 137(C).
    5. Telli, Şahin & Chen, Hongzhuan, 2020. "Multifractal behavior in return and volatility series of Bitcoin and gold in comparison," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    6. Cristiana Vaz & Rui Pascoal & Helder Sebastião, 2021. "Price Appreciation and Roughness Duality in Bitcoin: A Multifractal Analysis," Mathematics, MDPI, vol. 9(17), pages 1-18, August.
    7. Aurelio F. Bariviera & Mar'ia Jos'e Basgall & Waldo Hasperu'e & Marcelo Naiouf, 2017. "Some stylized facts of the Bitcoin market," Papers 1708.04532, arXiv.org.
    8. Lee, Minhyuk & Song, Jae Wook & Kim, Sondo & Chang, Woojin, 2018. "Asymmetric market efficiency using the index-based asymmetric-MFDFA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 1278-1294.
    9. Kang, Sang Hoon & McIver, Ron P. & Hernandez, Jose Arreola, 2019. "Co-movements between Bitcoin and Gold: A wavelet coherence analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    10. Huang, Menghao & Shao, Wei & Wang, Jian, 2023. "Correlations between the crude oil market and capital markets under the Russia–Ukraine conflict: A perspective of crude oil importing and exporting countries," Resources Policy, Elsevier, vol. 80(C).
    11. Osman Gulseven, 2020. "Turn-of-the Year Affect in Gold Prices: Decomposition Analysis," Papers 2003.11027, arXiv.org.
    12. Matthieu Garcin, 2021. "Forecasting with fractional Brownian motion: a financial perspective," Working Papers hal-03230167, HAL.
    13. Katarzyna Czech & Łukasz Pietrych, 2021. "The Efficiency of the Polish Zloty Exchange Rate Market: The Uncovered Interest Parity and Fractal Analysis Approaches," Risks, MDPI, vol. 9(8), pages 1-17, August.
    14. Fernandes, Leonardo H.S. & de Araújo, Fernando H.A. & Silva, Igor E.M., 2020. "The (in)efficiency of NYMEX energy futures: A multifractal analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 556(C).
    15. Asif, Raheel & Frömmel, Michael & Mende, Alexander, 2022. "The crisis alpha of managed futures: Myth or reality?," International Review of Financial Analysis, Elsevier, vol. 80(C).
    16. Asif, Raheel & Frömmel, Michael, 2022. "Testing Long memory in exchange rates and its implications for the adaptive market hypothesis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 593(C).
    17. Pritpal Singh BHULLAR & Dyal BHATNAGAR, 2020. "Bitcoins as a determinant of stock market movements: A comparison of Indian and Chinese Stock Markets," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 0(3(624), A), pages 193-202, Autumn.
    18. Pho, Kim Hung & Ly, Sel & Lu, Richard & Hoang, Thi Hong Van & Wong, Wing-Keung, 2021. "Is Bitcoin a better portfolio diversifier than gold? A copula and sectoral analysis for China," International Review of Financial Analysis, Elsevier, vol. 74(C).
    19. Matthieu Garcin, 2021. "Forecasting with fractional Brownian motion: a financial perspective," Papers 2105.09140, arXiv.org, revised Sep 2021.
    20. Assaf, Ata & Kristoufek, Ladislav & Demir, Ender & Kumar Mitra, Subrata, 2021. "Market efficiency in the art markets using a combination of long memory, fractal dimension, and approximate entropy measures," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 71(C).
    21. Kristoufek, Ladislav, 2018. "On Bitcoin markets (in)efficiency and its evolution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 257-262.
    22. Stosic, Darko & Stosic, Dusan & Ludermir, Teresa B. & Stosic, Tatijana, 2019. "Exploring disorder and complexity in the cryptocurrency space," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 548-556.
    23. Zhang, Wei & Wang, Pengfei & Li, Xiao & Shen, Dehua, 2018. "The inefficiency of cryptocurrency and its cross-correlation with Dow Jones Industrial Average," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 658-670.
    24. Muhammad Ali Nasir & Toan Luu Duc Huynh & Sang Phu Nguyen & Duy Duong, 2019. "Forecasting cryptocurrency returns and volume using search engines," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 5(1), pages 1-13, December.
    25. Stosic, Darko & Stosic, Dusan & Ludermir, Teresa B. & Stosic, Tatijana, 2019. "Multifractal behavior of price and volume changes in the cryptocurrency market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 520(C), pages 54-61.

  18. Ladislav Kristoufek, 2014. "Spectrum-based estimators of the bivariate Hurst exponent," Papers 1408.6637, arXiv.org, revised Nov 2014.

    Cited by:

    1. Ladislav Kristoufek, 2016. "Power-law cross-correlations estimation under heavy tails," Papers 1602.05385, arXiv.org, revised Apr 2016.
    2. Ladislav Kristoufek, 2018. "Power-law cross-correlations: Issues, solutions and future challenges," Papers 1806.01616, arXiv.org.

  19. Ladislav Kristoufek, 2014. "Leverage effect in energy futures," Papers 1403.0064, arXiv.org.

    Cited by:

    1. da Silva, Marcus Fernandes & Leão Pereira, Éder Johnson de Area & da Silva Filho, Aloisio Machado & Nunes de Castro, Arleys Pereira & Miranda, José Garcia Vivas & Zebende, Gilney Figueira, 2015. "Quantifying cross-correlation between Ibovespa and Brazilian blue-chips: The DCCA approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 124-129.
    2. Ding, Ashley, 2021. "A state-preference volatility index for the natural gas market," Energy Economics, Elsevier, vol. 104(C).
    3. Naqvi, Bushra & Mirza, Nawazish & Umar, Muhammad & Rizvi, Syed Kumail Abbas, 2023. "Shanghai crude oil futures: Returns Independence, volatility asymmetry, and hedging potential," Energy Economics, Elsevier, vol. 128(C).
    4. Qin, Xiao & Zhou, Chunyang & Wu, Chongfeng, 2016. "Revisiting asymmetric price transmission in the U.S. oil-gasoline markets: A multiple threshold error-correction analysis," Economic Modelling, Elsevier, vol. 52(PB), pages 583-591.
    5. Baum, Christopher F. & Zerilli, Paola & Chen, Liyuan, 2021. "Stochastic volatility, jumps and leverage in energy and stock markets: Evidence from high frequency data," Energy Economics, Elsevier, vol. 93(C).
    6. Jin, Xiaoye, 2017. "Time-varying return-volatility relation in international stock markets," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 157-173.
    7. Batten, Jonathan A. & Kinateder, Harald & Szilagyi, Peter G. & Wagner, Niklas F., 2019. "Liquidity, surprise volume and return premia in the oil market," Energy Economics, Elsevier, vol. 77(C), pages 93-104.
    8. Ewing, Bradley T. & Malik, Farooq, 2017. "Modelling asymmetric volatility in oil prices under structural breaks," Energy Economics, Elsevier, vol. 63(C), pages 227-233.
    9. Yong Jiang & Chao-Qun Ma & Xiao-Guang Yang & Yi-Shuai Ren, 2018. "Time-Varying Volatility Feedback of Energy Prices: Evidence from Crude Oil, Petroleum Products, and Natural Gas Using a TVP-SVM Model," Sustainability, MDPI, vol. 10(12), pages 1-17, December.
    10. Nascimento Filho, A.S. & Pereira, E.J.A.L. & Ferreira, Paulo & Murari, T.B. & Moret, M.A., 2018. "Cross-correlation analysis on Brazilian gasoline retail market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 550-557.
    11. da Silva, Marcus Fernandes & de Area Leão Pereira, Éder Johnson & da Silva Filho, Aloisio Machado & de Castro, Arleys Pereira Nunes & Miranda, José Garcia Vivas & Zebende, Gilney Figueira, 2016. "Quantifying the contagion effect of the 2008 financial crisis between the G7 countries (by GDP nominal)," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 453(C), pages 1-8.
    12. Yang, Cai & Gong, Xu & Zhang, Hongwei, 2019. "Volatility forecasting of crude oil futures: The role of investor sentiment and leverage effect," Resources Policy, Elsevier, vol. 61(C), pages 548-563.
    13. George P. Papaioannou & Christos Dikaiakos & Akylas C. Stratigakos & Panos C. Papageorgiou & Konstantinos F. Krommydas, 2019. "Testing the Efficiency of Electricity Markets Using a New Composite Measure Based on Nonlinear TS Tools," Energies, MDPI, vol. 12(4), pages 1-30, February.
    14. Khalifa, Ahmed & Caporin, Massimiliano & Hammoudeh, Shawkat, 2015. "Spillovers between energy and FX markets: The importance of asymmetry, uncertainty and business cycle," Energy Policy, Elsevier, vol. 87(C), pages 72-82.
    15. Jo-Hui & Chen & Sabbor Hussain, 2022. "Jump Dynamics and Leverage Effect: Evidences from Energy Exchange Traded Fund (ETFs)," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 12(6), pages 1-7.
    16. Gong, Xu & Wen, Fenghua & Xia, X.H. & Huang, Jianbai & Pan, Bin, 2017. "Investigating the risk-return trade-off for crude oil futures using high-frequency data," Applied Energy, Elsevier, vol. 196(C), pages 152-161.
    17. Xiao, Yang, 2020. "The risk spillovers from the Chinese stock market to major East Asian stock markets: A MSGARCH-EVT-copula approach," International Review of Economics & Finance, Elsevier, vol. 65(C), pages 173-186.
    18. Samet Gunay & Audil Rashid Khaki, 2018. "Best Fitting Fat Tail Distribution for the Volatilities of Energy Futures: Gev, Gat and Stable Distributions in GARCH and APARCH Models," JRFM, MDPI, vol. 11(2), pages 1-19, June.
    19. Svetlana Borovkova & Diego Mahakena, 2015. "News, volatility and jumps: the case of natural gas futures," Quantitative Finance, Taylor & Francis Journals, vol. 15(7), pages 1217-1242, July.
    20. Liyuan Chen & Paola Zerilli & Christopher F Baum, 2018. "Leverage effects and stochastic volatility in spot oil returns: A Bayesian approach with VaR and CVaR applications," Boston College Working Papers in Economics 953, Boston College Department of Economics.
    21. Wei Kuang, 2022. "Oil tail-risk forecasts: from financial crisis to COVID-19," Risk Management, Palgrave Macmillan, vol. 24(4), pages 420-460, December.
    22. Hyeon-Seok Kim & Hui-Sang Kim & Sun-Yong Choi, 2024. "Investigating the Impact of Agricultural, Financial, Economic, and Political Factors on Oil Forward Prices and Volatility: A SHAP Analysis," Energies, MDPI, vol. 17(5), pages 1-24, February.
    23. Carnero M. Angeles & Pérez Ana, 2021. "Outliers and misleading leverage effect in asymmetric GARCH-type models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(1), pages 1-19, February.
    24. Kristoufek, Ladislav, 2018. "Fractality in market risk structure: Dow Jones Industrial components case," Chaos, Solitons & Fractals, Elsevier, vol. 110(C), pages 69-75.
    25. Li, Daye & Nishimura, Yusaku & Men, Ming, 2016. "Why the long-term auto-correlation has not been eliminated by arbitragers: Evidences from NYMEX," Energy Economics, Elsevier, vol. 59(C), pages 167-178.
    26. Riza Demirer & Rangan Gupta & Jacobus Nel & Christian Pierdzioch, 2020. "Effect of Rare Disaster Risks on Crude Oil: Evidence from El Nino from Over 140 Years of Data," Working Papers 2020104, University of Pretoria, Department of Economics.
    27. Jiqian Wang & Feng Ma & M.I.M. Wahab & Dengshi Huang, 2021. "Forecasting China's Crude Oil Futures Volatility: The Role of the Jump, Jumps Intensity, and Leverage Effect," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 921-941, August.
    28. Chen, Rongda & Bao, Weiwei & Jin, Chenglu, 2021. "Investor sentiment and predictability for volatility on energy futures Markets: Evidence from China," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 112-129.
    29. Xiaotong Lian & Yingda Song, 2021. "Pricing and calibration of the futures options market: A unified approximation," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(7), pages 1074-1091, July.
    30. Carnero, M. Angeles & Pérez, Ana, 2019. "Leverage effect in energy futures revisited," Energy Economics, Elsevier, vol. 82(C), pages 237-252.
    31. Pan, Qunxing & Sun, Yujia, 2023. "Changes in volatility leverage and spillover effects of crude oil futures markets affected by the 2022 Russia-Ukraine conflict," Finance Research Letters, Elsevier, vol. 58(PB).
    32. Giray GOZGOR & Cahit MEMIS, 2015. "Price volatility spillovers among agricultural commodity and crude oil markets: Evidence from the range-based estimator," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 61(5), pages 214-221.
    33. Gupta, Rangan & Ji, Qiang & Pierdzioch, Christian & Plakandaras, Vasilios, 2023. "Forecasting the conditional distribution of realized volatility of oil price returns: The role of skewness over 1859 to 2023," Finance Research Letters, Elsevier, vol. 58(PC).
    34. Liu, Zhichao & Ma, Feng & Long, Yujia, 2015. "High and low or close to close prices? Evidence from the multifractal volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 427(C), pages 50-61.
    35. Xu Gong & Boqiang Lin, 2022. "Predicting the volatility of crude oil futures: The roles of leverage effects and structural changes," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 610-640, January.
    36. Todea, Alexandru, 2016. "Cross-correlations between volatility, volatility persistence and stock market integration: the case of emergent stock markets," Chaos, Solitons & Fractals, Elsevier, vol. 87(C), pages 208-215.
    37. Bonnier, Jean-Baptiste, 2022. "Forecasting crude oil volatility with exogenous predictors: As good as it GETS?," Energy Economics, Elsevier, vol. 111(C).
    38. Ahmed Jeribi & Mohamed Fakhfekh, 2021. "Portfolio management and dependence structure between cryptocurrencies and traditional assets: evidence from FIEGARCH-EVT-Copula," Journal of Asset Management, Palgrave Macmillan, vol. 22(3), pages 224-239, May.
    39. Ferreira, Paulo & Pereira, Éder Johson de Area Leão & Silva, Marcus Fernandes da & Pereira, Hernane Borges, 2019. "Detrended correlation coefficients between oil and stock markets: The effect of the 2008 crisis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 517(C), pages 86-96.
    40. Jian Yang & Yinggang Zhou, 2020. "Return and volatility transmission between China's and international crude oil futures markets: A first look," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(6), pages 860-884, June.
    41. Lin, Yu & Xiao, Yang & Li, Fuxing, 2020. "Forecasting crude oil price volatility via a HM-EGARCH model," Energy Economics, Elsevier, vol. 87(C).
    42. Gozgor, Giray & Lau, Chi Keung Marco & Bilgin, Mehmet Huseyin, 2016. "Commodity markets volatility transmission: Roles of risk perceptions and uncertainty in financial markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 44(C), pages 35-45.

  20. Ladislav Kristoufek, 2014. "Detrended fluctuation analysis as a regression framework: Estimating dependence at different scales," Papers 1411.0496, arXiv.org, revised Jan 2015.

    Cited by:

    1. Paulo Ferreira, 2017. "Portuguese and Brazilian stock market integration: a non-linear and detrended approach," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 16(1), pages 49-63, April.
    2. Ladislav Kristoufek, 2016. "Power-law cross-correlations estimation under heavy tails," Papers 1602.05385, arXiv.org, revised Apr 2016.
    3. Ladislav Kristoufek, 2018. "Power-law cross-correlations: Issues, solutions and future challenges," Papers 1806.01616, arXiv.org.

  21. Ladislav Kristoufek & Petra Lunackova, 2014. "Rockets and feathers meet Joseph: Reinvestigating the oil-gasoline asymmetry on the international markets," Papers 1407.5466, arXiv.org.

    Cited by:

    1. Qin, Xiao & Zhou, Chunyang & Wu, Chongfeng, 2016. "Revisiting asymmetric price transmission in the U.S. oil-gasoline markets: A multiple threshold error-correction analysis," Economic Modelling, Elsevier, vol. 52(PB), pages 583-591.
    2. Bagnai, Alberto & Mongeau Ospina, Christian Alexander, 2018. "Asymmetries, outliers and structural stability in the US gasoline market," Energy Economics, Elsevier, vol. 69(C), pages 250-260.
    3. Palencia-González, Francisco J. & Navío-Marco, Julio & Juberías-Cáceres, Gema, 2020. "Analysis of brand influence in the rockets and feathers effect using disaggregated data," Research in International Business and Finance, Elsevier, vol. 52(C).
    4. Alberto Bagnai & Christian Alexander Mongeau Ospina, 2016. "Price asymmetries in the European gasoline market," a/ Working Papers Series 1602, Italian Association for the Study of Economic Asymmetries, Rome (Italy).
    5. Bragoudakis, Zacharias & Degiannakis, Stavros & Filis, George, 2020. "Oil and pump prices: Testing their asymmetric relationship in a robust way," Energy Economics, Elsevier, vol. 88(C).
    6. Zacharias Bragoudakis & Dimitrios Sideris, 2019. "Asymmetric price adjustment and the effects of structural reforms in a low income environment: the case of the gasoline market in Greece," Working Papers 274, Bank of Greece.
    7. Chen, Chaoyi & Polemis, Michael & Stengos, Thanasis, 2018. "On the Examination of Competition in the Petroleum Industry: A Pooled Panel Threshold Analysis," MPRA Paper 89671, University Library of Munich, Germany.
    8. Deltas, George & Polemis, Michael, 2018. "Estimating retail gasoline price dynamics: The effects of sample characteristics and research design," MPRA Paper 89570, University Library of Munich, Germany.
    9. Ligia Topan & Miguel Jerez & Sonia Sotoca, 2020. "The impact of oil prices on products groups inflation: is the effect asymmetric?," Documentos de Trabajo del ICAE 2020-01, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    10. Ogbuabor, Jonathan E. & Ukwueze, Ezebuilo R. & Mba, Ifeoma C. & Ojonta, Obed I. & Orji, Anthony, 2023. "The asymmetric impact of economic policy uncertainty on global retail energy markets: Are the markets responding to the fear of the unknown?," Applied Energy, Elsevier, vol. 334(C).
    11. Pal, Debdatta & Mitra, Subrata K., 2016. "Asymmetric oil product pricing in India: Evidence from a multiple threshold nonlinear ARDL model," Economic Modelling, Elsevier, vol. 59(C), pages 314-328.
    12. Zacharias Bragoudakis & Stavros Degiannakis & George Filis, 2019. "Oil and pump prices: is there any asymmetry in the Greek oil downstream sector?," Working Papers 268, Bank of Greece.
    13. Taner SEKMEN & Seher Gülşah TOPUZ, 2021. "Asymmetric Oil Price and Exchange Rate Pass-Through in the Turkish Oil-Gasoline Markets," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 74-93, June.
    14. Bagnai, Alberto & Mongeau Ospina, Christian Alexander, 2016. "“Asymmetric asymmetries” in Eurozone markets gasoline pricing," The Journal of Economic Asymmetries, Elsevier, vol. 13(C), pages 89-99.
    15. Kristoufek, Ladislav, 2019. "Are the crude oil markets really becoming more efficient over time? Some new evidence," Energy Economics, Elsevier, vol. 82(C), pages 253-263.
    16. Ladislav Kristoufek & Karel Janda & David Zilberman, 2015. "Co-movements of Ethanol Related Prices: Evidence from Brazil and the USA," CAMA Working Papers 2015-11, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    17. Karol Szomolanyi & Martin Lukacik & Adriana Lukacikova, 2022. "Estimation of asymmetric responses of U.S. retail fuel prices to changes in input prices based on a linear exponential adjustment cost approach," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 30(2), pages 757-779, June.
    18. Noel, Michael D. & Qiang, Hongjie, 2019. "The role of information in retail gasoline price dispersion," Energy Economics, Elsevier, vol. 80(C), pages 173-187.
    19. Chen, Chaoyi & Polemis, Michael & Stengos, Thanasis, 2019. "Can exchange rate pass-through explain the asymmetric gasoline puzzle? Evidence from a pooled panel threshold analysis of the EU," Energy Economics, Elsevier, vol. 81(C), pages 1-12.
    20. Kang, Wensheng & de Gracia, Fernando Perez & Ratti, Ronald A., 2019. "The asymmetric response of gasoline prices to oil price shocks and policy uncertainty," Energy Economics, Elsevier, vol. 77(C), pages 66-79.
    21. Hamid Baghestani & Jorg Bley, 2020. "Do directional predictions of US gasoline prices reveal asymmetries?," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 44(2), pages 348-360, April.
    22. Jonathan E. Ogbuabor & God'stime O. Eigbiremolen & Charles O. Manasseh & Ifeoma C. Mba, 2018. "Asymmetric Price Transmission and Rent‐seeking in Road Fuel Markets: A Comparative Study of South Africa and Selected Eurozone Countries," African Development Review, African Development Bank, vol. 30(3), pages 278-290, September.
    23. Cook, Steven & Fosten, Jack, 2019. "Replicating rockets and feathers," Energy Economics, Elsevier, vol. 82(C), pages 139-151.
    24. Bentour, El Mostafa, 2015. "On the removal of energy products subsidies in an importing oil country: impacts on prices in Morocco," MPRA Paper 63635, University Library of Munich, Germany.

  22. Jaroslav Pavlicek & Ladislav Kristoufek, 2014. "Can Google searches help nowcast and forecast unemployment rates in the Visegrad Group countries?," Papers 1408.6639, arXiv.org.

    Cited by:

    1. Tuhkuri, Joonas, 2016. "Forecasting Unemployment with Google Searches," ETLA Working Papers 35, The Research Institute of the Finnish Economy.
    2. Georg von Graevenitz & Christian Helmers & Valentine Millot & Oliver Turnbull, 2016. "Does Online Search Predict Sales? Evidence from Big Data for Car Markets in Germany and the UK," Working Paper series, University of East Anglia, Centre for Competition Policy (CCP) 2016-07, Centre for Competition Policy, University of East Anglia, Norwich, UK..

  23. Pavla Blahova & Karel Janda & Ladislav Kristoufek, 2014. "The Perspectives for Genetically Modified Cellulosic Ethanol in the Czech Republic," Working Papers IES 2014/02, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Jan 2014.

    Cited by:

    1. Karel Janda & Jan Málek & Lukáš Rečka, 2017. "Vliv obnovitelných zdrojů na českou soustavu přenosu elektřiny [The Impact of Renewable Energy Sources on the Czech Electricity Transmission System]," Politická ekonomie, Prague University of Economics and Business, vol. 2017(6), pages 728-750.
    2. Karel Janda & Jan Malek & Lukas Recka, 2017. "The Influence of Renewable Energy Sources on the Czech Electricity Transmission System," Working Papers IES 2017/06, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Mar 2017.
    3. Ondřej Filip & Karel Janda & Ladislav Krištoufek, 2018. "Ceny biopaliv a souvisejících komodit: analýza s použitím metod minimální kostry grafu a hierarchických stromů [Prices of Biofuels and Related Commodities: an Analysis Using Methods of Minimum Span," Politická ekonomie, Prague University of Economics and Business, vol. 2018(2), pages 218-239.

  24. Jana Hortová & Ladislav Kristoufek, 2014. "Price elasticity of household water demand in the Czech Republic," Working Papers IES 2014/38, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Dec 2014.

    Cited by:

    1. Milan Ščasný & Šarlota Smutná, 2019. "Estimation of Price and Income Elasticity of Residential Water Demand in the Czech Republic over Three Decades," Working Papers IES 2019/13, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Jun 2019.

  25. Ladislav Kristoufek, 2014. "What are the main drivers of the Bitcoin price? Evidence from wavelet coherence analysis," Papers 1406.0268, arXiv.org.

    Cited by:

    1. David Garcia & Claudio Juan Tessone & Pavlin Mavrodiev & Nicolas Perony, 2014. "The digital traces of bubbles: feedback cycles between socio-economic signals in the Bitcoin economy," Papers 1408.1494, arXiv.org.
    2. Fang, Libing & Bouri, Elie & Gupta, Rangan & Roubaud, David, 2019. "Does global economic uncertainty matter for the volatility and hedging effectiveness of Bitcoin?," International Review of Financial Analysis, Elsevier, vol. 61(C), pages 29-36.
    3. Jordan Evans & Christopher C. Klein, 2018. "Do Major Currency Trading Volumes Explain the Rise of Bitcoin’s Price?," Journal for Economic Educators, Middle Tennessee State University, Business and Economic Research Center, vol. 18(1), pages 39-45, Spring.
    4. Christian Conrad & Anessa Custovic & Eric Ghysels, 2018. "Long- and Short-Term Cryptocurrency Volatility Components: A GARCH-MIDAS Analysis," JRFM, MDPI, vol. 11(2), pages 1-12, May.
    5. Alessandra Cretarola & Gianna Fig`a-Talamanca, 2017. "A confidence-based model for asset and derivative prices in the BitCoin market," Papers 1702.00215, arXiv.org.
    6. Anna Iwona Piotrowska & Dariusz Piotrowski, 2017. "Barriers to the functioning of the bitcoin system ? user assessment," Proceedings of Economics and Finance Conferences 4807736, International Institute of Social and Economic Sciences.
    7. Osamah Al-Khazali & Elie Bouri & David Roubaud, 2018. "The impact of positive and negative macroeconomic news surprises: Gold versus Bitcoin," Economics Bulletin, AccessEcon, vol. 38(1), pages 373-382.
    8. Bouoiyour, Jamal & Selmi, Refk, 2014. "What Bitcoin Looks Like?," MPRA Paper 58091, University Library of Munich, Germany.
    9. Elie Bouri & Mahamitra Das & Rangan Gupta & David Roubaud, 2018. "Spillovers between Bitcoin and other assets during bear and bull markets," Applied Economics, Taylor & Francis Journals, vol. 50(55), pages 5935-5949, November.
    10. Alessandra Cretarola & Gianna Fig`a-Talamanca & Marco Patacca, 2017. "A sentiment-based model for the BitCoin: theory, estimation and option pricing," Papers 1709.08621, arXiv.org.
    11. Elie Bouri & Naji Jalkh & Peter Molnár & David Roubaud, 2017. "Bitcoin for energy commodities before and after the December 2013 crash: diversifier, hedge or safe haven?," Applied Economics, Taylor & Francis Journals, vol. 49(50), pages 5063-5073, October.
    12. Fantazzini, Dean & Nigmatullin, Erik & Sukhanovskaya, Vera & Ivliev, Sergey, 2016. "Everything you always wanted to know about bitcoin modelling but were afraid to ask," MPRA Paper 71946, University Library of Munich, Germany, revised 2016.
    13. Frode Kjærland & Aras Khazal & Erlend A. Krogstad & Frans B. G. Nordstrøm & Are Oust, 2018. "An Analysis of Bitcoin’s Price Dynamics," JRFM, MDPI, vol. 11(4), pages 1-18, October.
    14. Panagiotidis, Theodore & Stengos, Thanasis & Vravosinos, Orestis, 2018. "On the determinants of bitcoin returns: A LASSO approach," Finance Research Letters, Elsevier, vol. 27(C), pages 235-240.
    15. Boido, Claudio & Aliano, Mauro, 2023. "Digital art and non-fungible-token: Bubble or revolution?," Finance Research Letters, Elsevier, vol. 52(C).
    16. Luisanna Cocco & Michele Marchesi, 2016. "Modeling and Simulation of the Economics of Mining in the Bitcoin Market," Papers 1605.01354, arXiv.org.
    17. Abeer ElBahrawy & Laura Alessandretti & Andrea Baronchelli, 2019. "Wikipedia and Digital Currencies: Interplay Between Collective Attention and Market Performance," Papers 1902.04517, arXiv.org, revised Mar 2019.
    18. Nektarios Aslanidis & Aurelio F. Bariviera & Oscar Martinez-Iba~nez, 2018. "An analysis of cryptocurrencies conditional cross correlations," Papers 1811.08365, arXiv.org, revised Feb 2019.
    19. Abeer ElBahrawy & Laura Alessandretti & Anne Kandler & Romualdo Pastor-Satorras & Andrea Baronchelli, 2017. "Evolutionary dynamics of the cryptocurrency market," Papers 1705.05334, arXiv.org, revised Nov 2017.
    20. Thomas Walther & Tony Klein, 2018. "Exogenous Drivers of Cryptocurrency Volatility - A Mixed Data Sampling Approach To Forecasting," Working Papers on Finance 1815, University of St. Gallen, School of Finance.
    21. Zhou, Siwen, 2018. "Exploring the Driving Forces of the Bitcoin Exchange Rate Dynamics: An EGARCH Approach," MPRA Paper 89445, University Library of Munich, Germany.
    22. Bouoiyour, Jamal & Selmi, Refk, 2014. "What Does Crypto-currency Look Like? Gaining Insight into Bitcoin Phenomenon," MPRA Paper 57907, University Library of Munich, Germany.
    23. Baumöhl, Eduard, 2018. "Are cryptocurrencies connected to forex? A quantile cross-spectral approach," EconStor Preprints 174884, ZBW - Leibniz Information Centre for Economics.
    24. Bação Pedro & Duarte António Portugal & Sebastião Helder & Redzepagic Srdjan, 2018. "Information Transmission Between Cryptocurrencies: Does Bitcoin Rule the Cryptocurrency World?," Scientific Annals of Economics and Business, Sciendo, vol. 65(2), pages 97-117, June.
    25. Frode Kj rland & Maria Meland & Are Oust & Vilde yen, 2018. "How can Bitcoin Price Fluctuations be Explained?," International Journal of Economics and Financial Issues, Econjournals, vol. 8(3), pages 323-332.
    26. Adam Hayes, 2018. "Bitcoin price and its marginal cost of production: support for a fundamental value," Papers 1805.07610, arXiv.org.
    27. Toan Luu Duc Huynh, 2019. "Spillover Risks on Cryptocurrency Markets: A Look from VAR-SVAR Granger Causality and Student’s-t Copulas," JRFM, MDPI, vol. 12(2), pages 1-19, April.
    28. Jamal Bouoiyour & Refk Selmi, 2015. "What Does Bitcoin Look Like?," Post-Print hal-01879683, HAL.
    29. Mark Mizraki, 2015. "Conversation with Mark Mizruchi:“There is Very Little Organizational Theory Left in Sociology Departments”," Journal of Economic Sociology, National Research University Higher School of Economics, vol. 16(3), pages 14-25.
    30. Paulo Ferreira & Éder Pereira, 2019. "Contagion Effect in Cryptocurrency Market," JRFM, MDPI, vol. 12(3), pages 1-8, July.
    31. Ke Wu & Spencer Wheatley & Didier Sornette, 2018. "Classification of cryptocurrency coins and tokens by the dynamics of their market capitalisations," Papers 1803.03088, arXiv.org, revised May 2018.
    32. Byström, Hans & Krygier, Dominika, 2018. "What Drives Bitcoin Volatility?," Working Papers 2018:24, Lund University, Department of Economics.
    33. Zura Kakushadze & Jim Kyung-Soo Liew, 2018. "CryptoRuble: From Russia with Love," Papers 1801.05760, arXiv.org.
    34. Zhang, Wei & Wang, Pengfei & Li, Xiao & Shen, Dehua, 2018. "Quantifying the cross-correlations between online searches and Bitcoin market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 657-672.
    35. Beate Sauer, 2016. "Virtual Currencies, the Money Market, and Monetary Policy," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 22(2), pages 117-130, May.
    36. Jamal Bouoiyour & Refk Selmi & Aviral Kumar Tiwari, 2015. "Is Bitcoin Business Income or Speculative Bubble? Unconditional vs. Conditional Frequency Domain Analysis," Post-Print hal-01879684, HAL.
    37. Nino Antulov-Fantulin & Dijana Tolic & Matija Piskorec & Zhang Ce & Irena Vodenska, 2018. "Inferring short-term volatility indicators from Bitcoin blockchain," Papers 1809.07856, arXiv.org.
    38. Charles Hoffreumon & Nicolas van Zeebroeck, 2018. "Forecasting short-term transaction fees on a smart contracts platform," Working Papers TIMES² 2018-028, ULB -- Universite Libre de Bruxelles.
    39. Joerg Osterrieder & Julian Lorenz, 2017. "A Statistical Risk Assessment Of Bitcoin And Its Extreme Tail Behavior," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 12(01), pages 1-19, March.
    40. Zhang, Wei & Wang, Pengfei & Li, Xiao & Shen, Dehua, 2018. "The inefficiency of cryptocurrency and its cross-correlation with Dow Jones Industrial Average," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 658-670.
    41. Jaroslav Bukovina & Matus Marticek, 2016. "Sentiment and Bitcoin Volatility," MENDELU Working Papers in Business and Economics 2016-58, Mendel University in Brno, Faculty of Business and Economics.
    42. Jamal Bouoiyour & Refk Selmi & Aviral Kumar Tiwari, 2015. "Is Bitcoin Business Income Or Speculative Foolery? New Ideas Through An Improved Frequency Domain Analysis," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 10(01), pages 1-23.
    43. Lim, Siok Jin & Masih, Mansur, 2017. "Exploring portfolio diversification opportunities in Islamic capital markets through bitcoin: evidence from MGARCH-DCC and Wavelet approaches," MPRA Paper 79752, University Library of Munich, Germany.
    44. Stübinger, Johannes, 2018. "Statistical arbitrage with optimal causal paths on high-frequencydata of the S&P 500," FAU Discussion Papers in Economics 01/2018, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    45. Ahmed M. Khedr & Ifra Arif & Pravija Raj P V & Magdi El‐Bannany & Saadat M. Alhashmi & Meenu Sreedharan, 2021. "Cryptocurrency price prediction using traditional statistical and machine‐learning techniques: A survey," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 28(1), pages 3-34, January.
    46. Panagiotidis, Theodore & Stengos, Thanasis & Vravosinos, Orestis, 2019. "The effects of markets, uncertainty and search intensity on bitcoin returns," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 220-242.

  26. Ladislav Kristoufek, 2014. "On the interplay between short and long term memory in the power-law cross-correlations setting," Papers 1409.6444, arXiv.org, revised Dec 2014.

    Cited by:

    1. Qin, Jing & Ge, Jintian & Lu, Xinsheng, 2018. "The effectiveness of the monetary policy in China: New evidence from long-range cross-correlation analysis and the components of multifractality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 1026-1037.
    2. Ladislav Kristoufek, 2016. "Power-law cross-correlations estimation under heavy tails," Papers 1602.05385, arXiv.org, revised Apr 2016.
    3. Kristoufek, Ladislav, 2015. "Finite sample properties of power-law cross-correlations estimators," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 513-525.
    4. Ladislav Kristoufek, 2018. "Power-law cross-correlations: Issues, solutions and future challenges," Papers 1806.01616, arXiv.org.
    5. Zhang, Wei & Wang, Pengfei & Li, Xiao & Shen, Dehua, 2018. "The inefficiency of cryptocurrency and its cross-correlation with Dow Jones Industrial Average," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 658-670.

  27. Ladislav Kristoufek, 2014. "Finite sample properties of power-law cross-correlations estimators," Papers 1409.6857, arXiv.org.

    Cited by:

    1. Ladislav Kristoufek, 2018. "Power-law cross-correlations: Issues, solutions and future challenges," Papers 1806.01616, arXiv.org.
    2. Zhang, Wei & Wang, Pengfei & Li, Xiao & Shen, Dehua, 2018. "The inefficiency of cryptocurrency and its cross-correlation with Dow Jones Industrial Average," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 658-670.

  28. Ladislav Kristoufek, 2013. "Testing power-law cross-correlations: Rescaled covariance test," Papers 1307.4727, arXiv.org, revised Aug 2013.

    Cited by:

    1. Kristoufek, Ladislav & Vosvrda, Miloslav, 2014. "Measuring capital market efficiency: Long-term memory, fractal dimension and approximate entropy," FinMaP-Working Papers 18, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    2. Qin, Jing & Ge, Jintian & Lu, Xinsheng, 2018. "The effectiveness of the monetary policy in China: New evidence from long-range cross-correlation analysis and the components of multifractality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 1026-1037.
    3. Ladislav Kristoufek, 2014. "Leverage effect in energy futures," Papers 1403.0064, arXiv.org.
    4. Ladislav Kristoufek, 2016. "Power-law cross-correlations estimation under heavy tails," Papers 1602.05385, arXiv.org, revised Apr 2016.
    5. Kristoufek, Ladislav, 2014. "Measuring correlations between non-stationary series with DCCA coefficient," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 402(C), pages 291-298.
    6. Ladislav Kristoufek, 2018. "Power-law cross-correlations: Issues, solutions and future challenges," Papers 1806.01616, arXiv.org.
    7. Zhang, Wei & Wang, Pengfei & Li, Xiao & Shen, Dehua, 2018. "Quantifying the cross-correlations between online searches and Bitcoin market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 657-672.
    8. Machado Filho, A. & da Silva, M.F. & Zebende, G.F., 2014. "Autocorrelation and cross-correlation in time series of homicide and attempted homicide," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 400(C), pages 12-19.
    9. Zhang, Wei & Wang, Pengfei & Li, Xiao & Shen, Dehua, 2018. "The inefficiency of cryptocurrency and its cross-correlation with Dow Jones Industrial Average," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 658-670.

  29. Ladislav Kristoufek & Miloslav Vosvrda, 2013. "Commodity futures and market efficiency," Papers 1309.1492, arXiv.org.

    Cited by:

    1. Cagli, Efe Caglar & Taskin, Dilvin & Evrim Mandaci, Pınar, 2019. "The short- and long-run efficiency of energy, precious metals, and base metals markets: Evidence from the exponential smooth transition autoregressive models," Energy Economics, Elsevier, vol. 84(C).
    2. Kristoufek, Ladislav & Vosvrda, Miloslav, 2014. "Measuring capital market efficiency: Long-term memory, fractal dimension and approximate entropy," FinMaP-Working Papers 18, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    3. Sattarhoff, Cristina & Gronwald, Marc, 2022. "Measuring informational efficiency of the European carbon market — A quantitative evaluation of higher order dependence," International Review of Financial Analysis, Elsevier, vol. 84(C).
    4. David, S.A. & Inácio, C.M.C. & Quintino, D.D. & Machado, J.A.T., 2020. "Measuring the Brazilian ethanol and gasoline market efficiency using DFA-Hurst and fractal dimension," Energy Economics, Elsevier, vol. 85(C).
    5. Benedetto, F. & Giunta, G. & Mastroeni, L., 2016. "On the predictability of energy commodity markets by an entropy-based computational method," Energy Economics, Elsevier, vol. 54(C), pages 302-312.
    6. Sensoy, Ahmet & Tabak, Benjamin M., 2016. "Dynamic efficiency of stock markets and exchange rates," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 353-371.
    7. Polyzos, Efstathios & Wang, Fang, 2022. "Twitter and market efficiency in energy markets: Evidence using LDA clustered topic extraction," Energy Economics, Elsevier, vol. 114(C).
    8. Yang, Chen & Lv, Fei & Fang, Libing & Shang, Xingxing, 2020. "The pricing efficiency of crude oil futures in the Shanghai International Exchange," Finance Research Letters, Elsevier, vol. 36(C).
    9. Fernandes, Leonardo H.S. & Araújo, Fernando H.A., 2020. "Taxonomy of commodities assets via complexity-entropy causality plane," Chaos, Solitons & Fractals, Elsevier, vol. 137(C).
    10. Kuruppuarachchi, Duminda & Premachandra, I.M. & Roberts, Helen, 2019. "A novel market efficiency index for energy futures and their term structure risk premiums," Energy Economics, Elsevier, vol. 77(C), pages 23-33.
    11. Corzo Santamaría, Teresa & Martin-Bujack, Karin & Portela, Jose & Sáenz-Diez, Rocio, 2022. "Early market efficiency testing among hydrogen players," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 723-742.
    12. Duan, Kun & Li, Zeming & Urquhart, Andrew & Ye, Jinqiang, 2021. "Dynamic efficiency and arbitrage potential in Bitcoin: A long-memory approach," International Review of Financial Analysis, Elsevier, vol. 75(C).
    13. Lee, Minhyuk & Song, Jae Wook & Kim, Sondo & Chang, Woojin, 2018. "Asymmetric market efficiency using the index-based asymmetric-MFDFA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 1278-1294.
    14. Yang Liu & Liyan Han & Libo Yin, 2018. "Does news uncertainty matter for commodity futures markets? Heterogeneity in energy and non‐energy sectors," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(10), pages 1246-1261, October.
    15. Go, You-How & Lau, Wee-Yeap, 2017. "Investor demand, market efficiency and spot-futures relation: Further evidence from crude palm oil," Resources Policy, Elsevier, vol. 53(C), pages 135-146.
    16. Górska, Anna & Krawiec, Monika, 2017. "Analiza efektywności informacyjnej w formie słabej na rynkach „soft commodities” z wykorzystaniem wybranych testów statystycznych," Problems of World Agriculture / Problemy Rolnictwa Światowego, Warsaw University of Life Sciences, vol. 17(32, Part ), September.
    17. Huang, Menghao & Shao, Wei & Wang, Jian, 2023. "Correlations between the crude oil market and capital markets under the Russia–Ukraine conflict: A perspective of crude oil importing and exporting countries," Resources Policy, Elsevier, vol. 80(C).
    18. Zunino, Luciano & Bariviera, Aurelio F. & Guercio, M. Belén & Martinez, Lisana B. & Rosso, Osvaldo A., 2016. "Monitoring the informational efficiency of European corporate bond markets with dynamical permutation min-entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 1-9.
    19. Tokic, Damir, 2015. "The 2014 oil bust: Causes and consequences," Energy Policy, Elsevier, vol. 85(C), pages 162-169.
    20. George P. Papaioannou & Christos Dikaiakos & Akylas C. Stratigakos & Panos C. Papageorgiou & Konstantinos F. Krommydas, 2019. "Testing the Efficiency of Electricity Markets Using a New Composite Measure Based on Nonlinear TS Tools," Energies, MDPI, vol. 12(4), pages 1-30, February.
    21. Ladislav Kristoufek & Miloslav Vosvrda, 2015. "Gold, currencies and market efficiency," Papers 1510.08615, arXiv.org.
    22. Ghazani, Majid Mirzaee & Ebrahimi, Seyed Babak, 2019. "Testing the adaptive market hypothesis as an evolutionary perspective on market efficiency: Evidence from the crude oil prices," Finance Research Letters, Elsevier, vol. 30(C), pages 60-68.
    23. Sukpitak, Jessada & Hengpunya, Varagorn, 2016. "The influence of trading volume on market efficiency: The DCCA approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 458(C), pages 259-265.
    24. Sensoy, Ahmet & Tabak, Benjamin M., 2015. "Time-varying long term memory in the European Union stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 147-158.
    25. Fernandes, Leonardo H.S. & de Araújo, Fernando H.A. & Silva, Igor E.M., 2020. "The (in)efficiency of NYMEX energy futures: A multifractal analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 556(C).
    26. Ikram Jebabli & David Roubaud, 2018. "Time-varying efficiency in food and energy markets: Evidence and implications," Post-Print hal-02330557, HAL.
    27. de Araujo, Fernando Henrique Antunes & Bejan, Lucian & Stosic, Borko & Stosic, Tatijana, 2020. "An analysis of Brazilian agricultural commodities using permutation – information theory quantifiers: The influence of food crisis," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    28. Li, Daye & Nishimura, Yusaku & Men, Ming, 2016. "The long memory and the transaction cost in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 442(C), pages 312-320.
    29. Teng, Yue & Shang, Pengjian, 2017. "Transfer entropy coefficient: Quantifying level of information flow between financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 60-70.
    30. DIMA, Bogdan & DIMA, Ştefana Maria & IOAN, Roxana, 2021. "Remarks on the behaviour of financial market efficiency during the COVID-19 pandemic. The case of VIX," Finance Research Letters, Elsevier, vol. 43(C).
    31. Sultan Alturki & Alexander Kurov, 2022. "Market inefficiencies surrounding energy announcements," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(1), pages 172-188, January.
    32. Liu, Li & Wang, Yudong & Wu, Chongfeng & Wu, Wenfeng, 2016. "Disentangling the determinants of real oil prices," Energy Economics, Elsevier, vol. 56(C), pages 363-373.
    33. Phélippé-Guinvarc'h, Martial & Cordier, Jean, 2015. "Machine Learning for Semi-Strong Efficiency Test of Inter-Market Wheat Futures," MPRA Paper 68410, University Library of Munich, Germany.
    34. Manley, Bruce & Niquidet, Kurt, 2017. "How does real option value compare with Faustmann value when log prices follow fractional Brownian motion?," Forest Policy and Economics, Elsevier, vol. 85(P1), pages 76-84.
    35. Pu, Yingjian & Yang, Baochen, 2022. "The commodity futures' historical basis in trading strategy and portfolio investment," Energy Economics, Elsevier, vol. 105(C).
    36. Delbianco, Fernando & Tohmé, Fernando & Stosic, Tatijana & Stosic, Borko, 2016. "Multifractal behavior of commodity markets: Fuel versus non-fuel products," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 573-580.
    37. Lahmiri, Salim & Bekiros, Stelios, 2021. "The effect of COVID-19 on long memory in returns and volatility of cryptocurrency and stock markets," Chaos, Solitons & Fractals, Elsevier, vol. 151(C).
    38. Ma, Pengcheng & Li, Daye & Li, Shuo, 2016. "Efficiency and cross-correlation in equity market during global financial crisis: Evidence from China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 163-176.
    39. Jale, Jader S. & Júnior, Sílvio F.A.X. & Stošić, Tatijana & Stošić, Borko & Ferreira, Tiago A.E., 2019. "Information flow between Ibovespa and constituent companies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 233-239.
    40. C. A. Tapia Cortez & J. Coulton & C. Sammut & S. Saydam, 2018. "Determining the chaotic behaviour of copper prices in the long-term using annual price data," Palgrave Communications, Palgrave Macmillan, vol. 4(1), pages 1-13, December.
    41. Williams Ohemeng & Bo Sjo & Michael Danquah, 2016. "Market Efficiency and Price Discovery in Cocoa Markets," Journal of African Business, Taylor & Francis Journals, vol. 17(2), pages 209-224, May.
    42. Storhas, Dominik P. & De Mello, Lurion & Singh, Abhay Kumar, 2020. "Multiscale lead-lag relationships in oil and refined product return dynamics: A symbolic wavelet transfer entropy approach," Energy Economics, Elsevier, vol. 92(C).
    43. Kristoufek, Ladislav, 2019. "Are the crude oil markets really becoming more efficient over time? Some new evidence," Energy Economics, Elsevier, vol. 82(C), pages 253-263.
    44. Fousekis, Panos & Tzaferi, Dimitra, 2022. "Price multifractality and informational efficiency in the futures markets of the US soybean complex," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 66, pages 68-84.
    45. Liu, Tie-Ying & Lee, Chien-Chiang, 2018. "Will the energy price bubble burst?," Energy, Elsevier, vol. 150(C), pages 276-288.
    46. Cao, K.H. & Qi, H.S. & Tsai, C.H. & Woo, C.K. & Zarnikau, J., 2021. "Energy trading efficiency in the US Midcontinent electricity markets," Applied Energy, Elsevier, vol. 302(C).
    47. Christian Mandl & Selvaprabu Nadarajah & Stefan Minner & Srinagesh Gavirneni, 2022. "Data‐driven storage operations: Cross‐commodity backtest and structured policies," Production and Operations Management, Production and Operations Management Society, vol. 31(6), pages 2438-2456, June.
    48. Wang, Xiaoyang, 2022. "Efficient markets are more connected: An entropy-based analysis of the energy, industrial metal and financial markets," Energy Economics, Elsevier, vol. 111(C).
    49. Lars Tegtmeier, 2021. "Testing the Efficiency of Globally Listed Private Equity Markets," JRFM, MDPI, vol. 14(7), pages 1-16, July.
    50. Krzysztof Borowski & Malgorzata Lukasik, 2015. "Analysis of Selected Seasonality Effects in the Following Agricultural Markets: Corn, Wheat, Coffee, Cocoa, Sugar, Cotton and Soybeans," Eurasian Journal of Business and Management, Eurasian Publications, vol. 3(2), pages 12-37.
    51. Lima, Cristiane Rocha Albuquerque & de Melo, Gabriel Rivas & Stosic, Borko & Stosic, Tatijana, 2019. "Cross-correlations between Brazilian biofuel and food market: Ethanol versus sugar," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 687-693.
    52. Sukpitak, Jessada & Hengpunya, Varagorn, 2016. "Efficiency of Thai stock markets: Detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 458(C), pages 204-209.
    53. Assaf, Ata & Kristoufek, Ladislav & Demir, Ender & Kumar Mitra, Subrata, 2021. "Market efficiency in the art markets using a combination of long memory, fractal dimension, and approximate entropy measures," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 71(C).
    54. Cerqueti, Roy & Fanelli, Viviana & Rotundo, Giulia, 2019. "Long run analysis of crude oil portfolios," Energy Economics, Elsevier, vol. 79(C), pages 183-205.
    55. Urquhart, Andrew, 2016. "The inefficiency of Bitcoin," Economics Letters, Elsevier, vol. 148(C), pages 80-82.
    56. Kristoufek, Ladislav, 2018. "On Bitcoin markets (in)efficiency and its evolution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 257-262.
    57. Shao Ying-Hui & Liu Ying-Lin & Yang Yan-Hong, 2022. "The short-term effect of COVID-19 pandemic on China's crude oil futures market: A study based on multifractal analysis," Papers 2204.05199, arXiv.org.
    58. F. Benedetto & L. Mastroeni & P. Vellucci, 2021. "Modeling the flow of information between financial time-series by an entropy-based approach," Annals of Operations Research, Springer, vol. 299(1), pages 1235-1252, April.
    59. Zhang, Wei & Wang, Pengfei & Li, Xiao & Shen, Dehua, 2018. "The inefficiency of cryptocurrency and its cross-correlation with Dow Jones Industrial Average," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 658-670.
    60. Okorie, David Iheke & Lin, Boqiang, 2021. "Adaptive market hypothesis: The story of the stock markets and COVID-19 pandemic," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    61. Xiaokang Hou & Shah Fahad & Peipei Zhao & Beibei Yan & Tianjun Liu, 2022. "The Trilogy of the Chinese Apple Futures Market: Price Discovery, Risk-Hedging and Cointegration," Sustainability, MDPI, vol. 14(19), pages 1-16, October.
    62. Roy Cerqueti & Viviana Fanelli, 2021. "Long memory and crude oil’s price predictability," Annals of Operations Research, Springer, vol. 299(1), pages 895-906, April.
    63. Stosic, Darko & Stosic, Dusan & Ludermir, Teresa & Stosic, Tatijana, 2016. "Correlations of multiscale entropy in the FX market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 52-61.
    64. Arık, Evren & Mutlu, Elif, 2014. "Chinese steel market in the post-futures period," Resources Policy, Elsevier, vol. 42(C), pages 10-17.
    65. Duan, Kun & Gao, Yang & Mishra, Tapas & Satchell, Stephen, 2023. "Efficiency dynamics across segmented Bitcoin Markets: Evidence from a decomposition strategy," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 83(C).
    66. Taylor, Nick, 2017. "Timing strategy performance in the crude oil futures market," Energy Economics, Elsevier, vol. 66(C), pages 480-492.
    67. Lya Paola Sierra & Luis Eduardo Gir n & Carolina Osorio, 2017. "Has Financialization in Commodity Markets Affected the Predictability in Metal Markets? The Efficient Markets Hypotheses for Metal Returns," International Journal of Economics and Financial Issues, Econjournals, vol. 7(4), pages 15-22.
    68. Vasile Brătian & Ana-Maria Acu & Camelia Oprean-Stan & Emil Dinga & Gabriela-Mariana Ionescu, 2021. "Efficient or Fractal Market Hypothesis? A Stock Indexes Modelling Using Geometric Brownian Motion and Geometric Fractional Brownian Motion," Mathematics, MDPI, vol. 9(22), pages 1-20, November.

  30. Ladislav Kristoufek & Petra Lunackova, 2013. "Long-term memory in electricity prices: Czech market evidence," Papers 1309.0582, arXiv.org.

    Cited by:

    1. Bennedsen, Mikkel, 2017. "A rough multi-factor model of electricity spot prices," Energy Economics, Elsevier, vol. 63(C), pages 301-313.
    2. Fan, Qingju, 2016. "Asymmetric multiscale detrended fluctuation analysis of California electricity spot price," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 442(C), pages 252-260.
    3. Mikkel Bennedsen, 2015. "Rough electricity: a new fractal multi-factor model of electricity spot prices," CREATES Research Papers 2015-42, Department of Economics and Business Economics, Aarhus University.
    4. Fan, Qingju & Li, Dan, 2015. "Multifractal cross-correlation analysis in electricity spot market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 429(C), pages 17-27.
    5. Luňáčková, Petra & Průša, Jan & Janda, Karel, 2017. "The merit order effect of Czech photovoltaic plants," Energy Policy, Elsevier, vol. 106(C), pages 138-147.
    6. Karahan, Cenk C. & Odabaşı, Attila & Tiryaki, C. Sani, 2024. "Wired together: Integration and efficiency in European electricity markets," Energy Economics, Elsevier, vol. 133(C).

  31. Ladislav Kristoufek, 2013. "Measuring correlations between non-stationary series with DCCA coefficient," Papers 1310.3984, arXiv.org.

    Cited by:

    1. Ladislav Kristoufek, 2015. "Power-law correlations in finance-related Google searches, and their cross-correlations with volatility and traded volume: Evidence from the Dow Jones Industrial components," Papers 1502.00225, arXiv.org.
    2. da Silva, Marcus Fernandes & Leão Pereira, Éder Johnson de Area & da Silva Filho, Aloisio Machado & Nunes de Castro, Arleys Pereira & Miranda, José Garcia Vivas & Zebende, Gilney Figueira, 2015. "Quantifying cross-correlation between Ibovespa and Brazilian blue-chips: The DCCA approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 124-129.
    3. Li, Jianxuan & Shi, Yingying & Cao, Guangxi, 2018. "Topology structure based on detrended cross-correlation coefficient of exchange rate network of the belt and road countries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 1140-1151.
    4. Ladislav Kristoufek, 2014. "Leverage effect in energy futures," Papers 1403.0064, arXiv.org.
    5. Ladislav Kristoufek, 2013. "Detrending moving-average cross-correlation coefficient: Measuring cross-correlations between non-stationary series," Papers 1311.0657, arXiv.org.
    6. Paulo Ferreira, 2017. "Portuguese and Brazilian stock market integration: a non-linear and detrended approach," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 16(1), pages 49-63, April.
    7. Ladislav Kristoufek & Paulo Ferreira, 2018. "Capital asset pricing model in Portugal: Evidence from fractal regressions," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 17(3), pages 173-183, November.
    8. Nascimento Filho, A.S. & Pereira, E.J.A.L. & Ferreira, Paulo & Murari, T.B. & Moret, M.A., 2018. "Cross-correlation analysis on Brazilian gasoline retail market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 550-557.
    9. Erdem, Orhan & Ceyhan, Elvan & Varli, Yusuf, 2014. "A new correlation coefficient for bivariate time-series data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 414(C), pages 274-284.
    10. Kristoufek, Ladislav, 2015. "Finite sample properties of power-law cross-correlations estimators," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 513-525.
    11. Stefano Ferretti, 2023. "On the Modeling and Simulation of Portfolio Allocation Schemes: an Approach Based on Network Community Detection," Computational Economics, Springer;Society for Computational Economics, vol. 62(3), pages 969-1005, October.
    12. Zhang, Wei & Li, Yi & Zhang, Zuochao & Shen, Dehua, 2018. "The dynamic cross-correlations between foreign news, local news and stock returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 861-872.
    13. Zhang, Wei & Wang, Pengfei & Li, Xiao & Shen, Dehua, 2018. "Quantifying the cross-correlations between online searches and Bitcoin market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 657-672.
    14. Ferreira, Paulo & Loures, Luís & Nunes, José & Brito, Paulo, 2018. "Are renewable energy stocks a possibility to diversify portfolios considering an environmentally friendly approach? The view of DCCA correlation coefficient," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 675-681.
    15. Zhang, Wei & Wang, Pengfei & Li, Xiao & Shen, Dehua, 2018. "The inefficiency of cryptocurrency and its cross-correlation with Dow Jones Industrial Average," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 658-670.

  32. Ladislav Kristoufek, 2013. "Can Google Trends search queries contribute to risk diversification?," Papers 1310.1444, arXiv.org.

    Cited by:

    1. Ladislav Kristoufek, 2015. "Power-law correlations in finance-related Google searches, and their cross-correlations with volatility and traded volume: Evidence from the Dow Jones Industrial components," Papers 1502.00225, arXiv.org.
    2. Pavlicek, Jaroslav & Kristoufek, Ladislav, 2015. "Nowcasting unemployment rates with Google searches: Evidence from the Visegrad Group countries," FinMaP-Working Papers 34, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    3. Fantazziini, Dean, 2014. "Nowcasting and Forecasting the Monthly Food Stamps Data in the US using Online Search Data," MPRA Paper 59696, University Library of Munich, Germany.
    4. Gabriele Ranco & Ilaria Bordino & Giacomo Bormetti & Guido Caldarelli & Fabrizio Lillo & Michele Treccani, 2014. "Coupling news sentiment with web browsing data improves prediction of intra-day price dynamics," Papers 1412.3948, arXiv.org, revised Dec 2015.
    5. Zeynalov, Ayaz, 2014. "Nowcasting Tourist Arrivals to Prague: Google Econometrics," MPRA Paper 60945, University Library of Munich, Germany.
    6. Zeynalov, Ayaz, 2017. "Forecasting Tourist Arrivals in Prague: Google Econometrics," MPRA Paper 83268, University Library of Munich, Germany.
    7. Jan Jurczyk, 2015. "Measuring switching processes in financial markets with the Mean-Variance spin glass approach," Papers 1503.03986, arXiv.org.
    8. Zhang, Wei & Wang, Pengfei & Li, Xiao & Shen, Dehua, 2018. "Quantifying the cross-correlations between online searches and Bitcoin market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 657-672.
    9. Damien Challet & Ahmed Bel Hadj Ayed, 2015. "Do Google Trend data contain more predictability than price returns?," Post-Print hal-00960875, HAL.
    10. Jaroslav Pavlicek & Ladislav Kristoufek, 2014. "Can Google searches help nowcast and forecast unemployment rates in the Visegrad Group countries?," Papers 1408.6639, arXiv.org.

  33. Ladislav Kristoufek, 2013. "Detrending moving-average cross-correlation coefficient: Measuring cross-correlations between non-stationary series," Papers 1311.0657, arXiv.org.

    Cited by:

    1. Ladislav Kristoufek, 2015. "Power-law correlations in finance-related Google searches, and their cross-correlations with volatility and traded volume: Evidence from the Dow Jones Industrial components," Papers 1502.00225, arXiv.org.
    2. Qin, Jing & Ge, Jintian & Lu, Xinsheng, 2018. "The effectiveness of the monetary policy in China: New evidence from long-range cross-correlation analysis and the components of multifractality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 1026-1037.
    3. Ladislav Kristoufek, 2014. "Leverage effect in energy futures," Papers 1403.0064, arXiv.org.
    4. Ladislav Kristoufek & Paulo Ferreira, 2018. "Capital asset pricing model in Portugal: Evidence from fractal regressions," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 17(3), pages 173-183, November.
    5. Ladislav Kristoufek, 2016. "Power-law cross-correlations estimation under heavy tails," Papers 1602.05385, arXiv.org, revised Apr 2016.
    6. Ladislav Kristoufek, 2018. "Power-law cross-correlations: Issues, solutions and future challenges," Papers 1806.01616, arXiv.org.
    7. Baumöhl, Eduard, 2018. "Are cryptocurrencies connected to forex? A quantile cross-spectral approach," EconStor Preprints 174884, ZBW - Leibniz Information Centre for Economics.
    8. Wang, Luo-Qing & Xu, Yong-Xiang, 2018. "Assessing the relevance of individual characteristics for the structure of similarity networks in new social strata in Shanghai," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 881-889.

  34. Ladislav Kristoufek, 2013. "Fractal Markets Hypothesis and the Global Financial Crisis: Wavelet Power Evidence," Papers 1310.1446, arXiv.org.

    Cited by:

    1. Domino, Krzysztof & Błachowicz, Tomasz, 2014. "The use of copula functions for modeling the risk of investment in shares traded on the Warsaw Stock Exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 77-85.
    2. Kaijian He & Rui Zha & Jun Wu & Kin Keung Lai, 2016. "Multivariate EMD-Based Modeling and Forecasting of Crude Oil Price," Sustainability, MDPI, vol. 8(4), pages 1-11, April.
    3. David Procházka & Jiří Pelák, 2016. "Ekonomické teorie účetnictví: přehled moderních přístupů a jejich reflexe při tvorbě účetních standardů [Economic Theories of Accounting: The Review of Modern Approaches and their Relevance for Sta," Politická ekonomie, Prague University of Economics and Business, vol. 2016(4), pages 451-467.
    4. Rita Sousa & Luís Aguiar-Conraria & Maria Joana Soares, 2014. "Carbon Financial Markets: a time-frequency analysis of CO2 price drivers," NIPE Working Papers 03/2014, NIPE - Universidade do Minho.
    5. David Procházka, 2014. "The Failure of Decision Usefulness Approach on an Example of the New Standard for Revenue Recognition [Selhání užitečnostního přístupu k formulaci účetních pravidel na příkladu nového standardu pro," Český finanční a účetní časopis, Prague University of Economics and Business, vol. 2014(3), pages 7-19.
    6. Fathi Abid & Bilel Kaffel, 2018. "The extent of virgin olive-oil prices’ distribution revealing the behavior of market speculators," Review of Quantitative Finance and Accounting, Springer, vol. 50(2), pages 561-590, February.
    7. Domino, Krzysztof & Błachowicz, Tomasz, 2015. "The use of copula functions for modeling the risk of investment in shares traded on world stock exchanges," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 142-151.
    8. Sousa, Rita & Aguiar-Conraria, Luís & Soares, Maria Joana, 2014. "Carbon financial markets: A time–frequency analysis of CO2 prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 414(C), pages 118-127.

  35. Ladislav Kristoufek & Karel Janda & David Zilberman, 2013. "Non-linear Price Transmission between Biofuels, Fuels and Food Commodities," CERGE-EI Working Papers wp481, The Center for Economic Research and Graduate Education - Economics Institute, Prague.

    Cited by:

    1. Deborah Bentivoglio & Adele Finco & Mirian Rumenos Piedade Bacchi, 2016. "Interdependencies between Biofuel, Fuel and Food Prices: The Case of the Brazilian Ethanol Market," Energies, MDPI, vol. 9(6), pages 1-16, June.
    2. Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2013. "Food versus Fuel: Causality and Predictability in Distribution," IEFE Working Papers 56, IEFE, Center for Research on Energy and Environmental Economics and Policy, Universita' Bocconi, Milano, Italy.
    3. Ladislav Kristoufek & Karel Janda & David Zilberman, 2015. "Co-movements of Ethanol Related Prices: Evidence from Brazil and the USA," CAMA Working Papers 2015-11, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    4. Ondřej Filip & Karel Janda & Ladislav Krištoufek, 2018. "Ceny biopaliv a souvisejících komodit: analýza s použitím metod minimální kostry grafu a hierarchických stromů [Prices of Biofuels and Related Commodities: an Analysis Using Methods of Minimum Span," Politická ekonomie, Prague University of Economics and Business, vol. 2018(2), pages 218-239.

  36. Ladislav Kristoufek & Miloslav Vosvrda, 2013. "Measuring capital market efficiency: Long-term memory, fractal dimension and approximate entropy," Papers 1307.3060, arXiv.org, revised May 2014.

    Cited by:

    1. Carmelo Reverte, 2016. "Corporate social responsibility disclosure and market valuation: evidence from Spanish listed firms," Review of Managerial Science, Springer, vol. 10(2), pages 411-435, March.
    2. Sensoy, Ahmet & Tabak, Benjamin M., 2016. "Dynamic efficiency of stock markets and exchange rates," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 353-371.
    3. Ioan Roxana, 2020. "Capital Market Correlations Structure During The Covid-19 Crisis," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 6, pages 67-79, December.
    4. Stosic, Dusan & Stosic, Darko & de Mattos Neto, Paulo S.G. & Stosic, Tatijana, 2019. "Multifractal characterization of Brazilian market sectors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 956-964.
    5. Lee, Minhyuk & Song, Jae Wook & Kim, Sondo & Chang, Woojin, 2018. "Asymmetric market efficiency using the index-based asymmetric-MFDFA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 1278-1294.
    6. Miguel Ángel Sánchez & Juan E Trinidad & José García & Manuel Fernández, 2015. "The Effect of the Underlying Distribution in Hurst Exponent Estimation," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-17, May.
    7. Flavia BARNA & Ştefana Maria DIMA & Bogdan DIMA & Lucian PAŞCA, 2016. "Fractal Market Hypothesis: The Emergent Financial Markets Case," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 50(2), pages 137-150.
    8. Anagnostidis, P. & Varsakelis, C. & Emmanouilides, C.J., 2016. "Has the 2008 financial crisis affected stock market efficiency? The case of Eurozone," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 116-128.
    9. Zunino, Luciano & Bariviera, Aurelio F. & Guercio, M. Belén & Martinez, Lisana B. & Rosso, Osvaldo A., 2016. "Monitoring the informational efficiency of European corporate bond markets with dynamical permutation min-entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 1-9.
    10. Sánchez-Granero, M.A. & Balladares, K.A. & Ramos-Requena, J.P. & Trinidad-Segovia, J.E., 2020. "Testing the efficient market hypothesis in Latin American stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    11. Ladislav Kristoufek & Miloslav Vosvrda, 2015. "Gold, currencies and market efficiency," Papers 1510.08615, arXiv.org.
    12. Sukpitak, Jessada & Hengpunya, Varagorn, 2016. "The influence of trading volume on market efficiency: The DCCA approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 458(C), pages 259-265.
    13. Auer, Benjamin R., 2016. "On the performance of simple trading rules derived from the fractal dynamics of gold and silver price fluctuations," Finance Research Letters, Elsevier, vol. 16(C), pages 255-267.
    14. Sensoy, Ahmet & Tabak, Benjamin M., 2015. "Time-varying long term memory in the European Union stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 147-158.
    15. Li, Daye & Nishimura, Yusaku & Men, Ming, 2016. "The long memory and the transaction cost in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 442(C), pages 312-320.
    16. Teng, Yue & Shang, Pengjian, 2017. "Transfer entropy coefficient: Quantifying level of information flow between financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 60-70.
    17. DIMA, Bogdan & DIMA, Ştefana Maria & IOAN, Roxana, 2021. "Remarks on the behaviour of financial market efficiency during the COVID-19 pandemic. The case of VIX," Finance Research Letters, Elsevier, vol. 43(C).
    18. Shimeng Shi & Jia Zhai & Yingying Wu, 2024. "Informational inefficiency on bitcoin futures," The European Journal of Finance, Taylor & Francis Journals, vol. 30(6), pages 642-667, April.
    19. V Dimitrova & M Fernández-Martínez & M A Sánchez-Granero & J E Trinidad Segovia, 2019. "Some comments on Bitcoin market (in)efficiency," PLOS ONE, Public Library of Science, vol. 14(7), pages 1-14, July.
    20. Ursu Iuliana, 2020. "The changing landscape of economy: social and technological progress in explaining the informational efficiency of capital markets," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 14(1), pages 940-952, July.
    21. Lahmiri, Salim, 2016. "Clustering of Casablanca stock market based on hurst exponent estimates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 310-318.
    22. Stosic, Darko & Stosic, Dusan & Ludermir, Teresa & de Oliveira, Wilson & Stosic, Tatijana, 2016. "Foreign exchange rate entropy evolution during financial crises," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 449(C), pages 233-239.
    23. Ma, Pengcheng & Li, Daye & Li, Shuo, 2016. "Efficiency and cross-correlation in equity market during global financial crisis: Evidence from China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 163-176.
    24. Kentaro Imajo & Kentaro Minami & Katsuya Ito & Kei Nakagawa, 2020. "Deep Portfolio Optimization via Distributional Prediction of Residual Factors," Papers 2012.07245, arXiv.org.
    25. Li, Daye & Kou, Zhun & Sun, Qiankun, 2015. "The scale-dependent market trend: Empirical evidences using the lagged DFA method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 433(C), pages 26-35.
    26. Rupel Nargunam & Ananya Lahiri, 2022. "Persistence in daily returns of stocks with highest market capitalization in the Indian market," Digital Finance, Springer, vol. 4(4), pages 341-374, December.
    27. Sukpitak, Jessada & Hengpunya, Varagorn, 2016. "Efficiency of Thai stock markets: Detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 458(C), pages 204-209.
    28. Karen Balladares & José Pedro Ramos-Requena & Juan Evangelista Trinidad-Segovia & Miguel Angel Sánchez-Granero, 2021. "Statistical Arbitrage in Emerging Markets: A Global Test of Efficiency," Mathematics, MDPI, vol. 9(2), pages 1-20, January.
    29. Assaf, Ata & Kristoufek, Ladislav & Demir, Ender & Kumar Mitra, Subrata, 2021. "Market efficiency in the art markets using a combination of long memory, fractal dimension, and approximate entropy measures," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 71(C).
    30. Kristoufek, Ladislav, 2018. "On Bitcoin markets (in)efficiency and its evolution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 257-262.
    31. A. Gómez-Águila & J. E. Trinidad-Segovia & M. A. Sánchez-Granero, 2022. "Improvement in Hurst exponent estimation and its application to financial markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-21, December.
    32. Zhang, Wei & Wang, Pengfei & Li, Xiao & Shen, Dehua, 2018. "The inefficiency of cryptocurrency and its cross-correlation with Dow Jones Industrial Average," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 658-670.
    33. José Pedro Ramos-Requena & Juan Evangelista Trinidad-Segovia & Miguel Ángel Sánchez-Granero, 2020. "Some Notes on the Formation of a Pair in Pairs Trading," Mathematics, MDPI, vol. 8(3), pages 1-17, March.
    34. Dima, Bogdan & Dima, Ştefana Maria, 2017. "Mutual information and persistence in the stochastic volatility of market returns: An emergent market example," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 36-59.
    35. Trinidad Segovia, J.E. & Fernández-Martínez, M. & Sánchez-Granero, M.A., 2019. "A novel approach to detect volatility clusters in financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    36. Subhamitra Patra & Gourishankar S. Hiremath, 2022. "An Entropy Approach to Measure the Dynamic Stock Market Efficiency," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 20(2), pages 337-377, June.
    37. Schadner, Wolfgang, 2021. "On the persistence of market sentiment: A multifractal fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    38. Vasile Brătian & Ana-Maria Acu & Camelia Oprean-Stan & Emil Dinga & Gabriela-Mariana Ionescu, 2021. "Efficient or Fractal Market Hypothesis? A Stock Indexes Modelling Using Geometric Brownian Motion and Geometric Fractional Brownian Motion," Mathematics, MDPI, vol. 9(22), pages 1-20, November.

  37. Ladislav Kristoufek, 2013. "Mixed-correlated ARFIMA processes for power-law cross-correlations," Papers 1307.6046, arXiv.org, revised Aug 2013.

    Cited by:

    1. Abry, Patrice & Didier, Gustavo, 2018. "Wavelet eigenvalue regression for n-variate operator fractional Brownian motion," Journal of Multivariate Analysis, Elsevier, vol. 168(C), pages 75-104.
    2. Rong, Lei & Shang, Pengjian, 2018. "New irreversibility measure and complexity analysis based on singular value decomposition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 913-924.
    3. Kakinaka, Shinji & Umeno, Ken, 2021. "Exploring asymmetric multifractal cross-correlations of price–volatility and asymmetric volatility dynamics in cryptocurrency markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    4. Ladislav Kristoufek & Petra Lunackova, 2015. "Rockets and Feathers Meet Joseph: Reinvestigating the Oil-gasoline Asymmetry on the International Markets," Working Papers IES 2015/02, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Feb 2015.
    5. Kristoufek, Ladislav, 2015. "Can the bivariate Hurst exponent be higher than an average of the separate Hurst exponents?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 431(C), pages 124-127.
    6. Teng, Yue & Shang, Pengjian, 2018. "Detrended fluctuation analysis based on higher-order moments of financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 311-322.
    7. Wu, Yue & Shang, Pengjian & Chen, Shijian, 2019. "Modified multifractal large deviation spectrum based on CID for financial market system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1331-1342.
    8. Kristoufek, Ladislav, 2014. "Measuring correlations between non-stationary series with DCCA coefficient," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 402(C), pages 291-298.
    9. Xi, Caiping & Zhang, Shuning & Xiong, Gang & Zhao, Huichang & Yang, Yonghong, 2017. "The application of the multifractal cross-correlation analysis methods in radar target detection within sea clutter," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 839-854.
    10. Teng, Yue & Shang, Pengjian, 2017. "Transfer entropy coefficient: Quantifying level of information flow between financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 60-70.
    11. Kristoufek, Ladislav, 2015. "Finite sample properties of power-law cross-correlations estimators," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 513-525.
    12. Kristoufek, Ladislav, 2015. "On the interplay between short and long term memory in the power-law cross-correlations setting," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 421(C), pages 218-222.
    13. Ladislav Kristoufek, 2014. "Spectrum-based estimators of the bivariate Hurst exponent," Papers 1408.6637, arXiv.org, revised Nov 2014.
    14. Ladislav Kristoufek, 2018. "Power-law cross-correlations: Issues, solutions and future challenges," Papers 1806.01616, arXiv.org.
    15. Fernández-Martínez, M. & Sánchez-Granero, M.A. & Casado Belmonte, M.P. & Trinidad Segovia, J.E., 2020. "A note on power-law cross-correlated processes," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    16. Cao, Guangxi & Shi, Yingying, 2017. "Simulation analysis of multifractal detrended methods based on the ARFIMA process," Chaos, Solitons & Fractals, Elsevier, vol. 105(C), pages 235-243.
    17. Stan, Cristina & Marmureanu, Luminita & Marin, Cristina & Cristescu, Constantin P., 2020. "Investigation of multifractal cross-correlation surfaces of Hurst exponents for some atmospheric pollutants," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    18. Wang, Fang & Wang, Lin & Chen, Yuming, 2018. "Quantifying the range of cross-correlated fluctuations using a q–L dependent AHXA coefficient," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 494(C), pages 454-464.

  38. Ladislav Kristoufek & Karel Janda & David zilberman, 2012. "Correlations between biofuels and related commodities: A taxonomy perspective," CAMA Working Papers 2012-29, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.

    Cited by:

    1. Lukas Vacha & Karel Janda & Ladislav Kristoufek & David Zilberman, 2012. "Time-Frequency Dynamics of Biofuels-Fuels-Food System," Papers 1209.0900, arXiv.org.
    2. Nazlioglu, Saban & Erdem, Cumhur & Soytas, Ugur, 2013. "Volatility spillover between oil and agricultural commodity markets," Energy Economics, Elsevier, vol. 36(C), pages 658-665.
    3. Shahzad, Syed Jawad Hussain & Hernandez, Jose Arreola & Al-Yahyaee, Khamis Hamed & Jammazi, Rania, 2018. "Asymmetric risk spillovers between oil and agricultural commodities," Energy Policy, Elsevier, vol. 118(C), pages 182-198.
    4. Paulus, Michal & Kristoufek, Ladislav, 2015. "Worldwide clustering of the corruption perception," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 351-358.
    5. Ouyang, Ruolan & Zhuang, Chengkai & Wang, Tingting & Zhang, Xuan, 2022. "Network analysis of risk transmission among energy futures: An industrial chain perspective," Energy Economics, Elsevier, vol. 107(C).
    6. de Araujo, Fernando Henrique Antunes & Bejan, Lucian & Stosic, Borko & Stosic, Tatijana, 2020. "An analysis of Brazilian agricultural commodities using permutation – information theory quantifiers: The influence of food crisis," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    7. David Roubaud & Bouri Elie & Qiang Ji, 2018. "Dynamic network of implied volatility transmission among US equities, strategic commodities, and BRICS equities," Post-Print hal-02081506, HAL.
    8. Wang, Gang-Jin & Xie, Chi, 2015. "Correlation structure and dynamics of international real estate securities markets: A network perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 176-193.
    9. Marcio Genovevo da Costa & Nils Donner, 2016. "Cointegration between Equity- and Agricultural Markets: Implications for Portfolio Diversification," Journal of Management and Sustainability, Canadian Center of Science and Education, vol. 6(1), pages 24-44, March.
    10. Benes, Ondrej & Janda, Karel, 2022. "Environmental Dimensions of Biofuels," EconStor Preprints 259403, ZBW - Leibniz Information Centre for Economics.
    11. Bouri, Elie & Lucey, Brian & Saeed, Tareq & Vo, Xuan Vinh, 2021. "The realized volatility of commodity futures: Interconnectedness and determinants#," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 139-151.

  39. Kristoufek, Ladislav & Janda, Karel & Zilberman, David, 2012. "Relationship Between Prices of Food, Fuel and Biofuel," 131st Seminar, September 18-19, 2012, Prague, Czech Republic 135793, European Association of Agricultural Economists.

    Cited by:

    1. Gautier Marti & Frank Nielsen & Miko{l}aj Bi'nkowski & Philippe Donnat, 2017. "A review of two decades of correlations, hierarchies, networks and clustering in financial markets," Papers 1703.00485, arXiv.org, revised Nov 2020.
    2. Anna Górska & Monika Krawiec, 2021. "Analysis of Interrelationships between Markets of Fuels in the Visegrad Group Countries from 2016 to 2020," Energies, MDPI, vol. 14(20), pages 1-14, October.
    3. Palacio-Ciro, Santiago & Vasco-Correa, Carlos Andrés, 2020. "Biofuels policy in Colombia: A reconfiguration to the sugar and palm sectors?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).

  40. Ladislav Kristoufek & Karel Janda & David Zilberman, 2012. "Mutual Responsiveness of Biofuels, Fuels and Food Prices," CAMA Working Papers 2012-38, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.

    Cited by:

    1. Lukas Vacha & Karel Janda & Ladislav Kristoufek & David Zilberman, 2012. "Time-Frequency Dynamics of Biofuels-Fuels-Food System," Papers 1209.0900, arXiv.org.
    2. Ladislav Kristoufek & Karel Janda & David Zilberman, 2013. "Non-linear Price Transmission between Biofuels, Fuels and Food Commodities," CERGE-EI Working Papers wp481, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    3. Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2013. "Biofuels and Food Prices: Searching for the Causal Link," Working Papers 239, University of Milano-Bicocca, Department of Economics, revised Mar 2013.
    4. Deborah Bentivoglio & Adele Finco & Mirian Rumenos Piedade Bacchi, 2016. "Interdependencies between Biofuel, Fuel and Food Prices: The Case of the Brazilian Ethanol Market," Energies, MDPI, vol. 9(6), pages 1-16, June.
    5. Bentivoglio, Deborah & Finco, Adele & Bacchi, Mirian, 2015. "Examining Price Transmission between Fuels and Food Prices: the Brazilian Sugar-Ethanol Market," 2015 Conference, August 9-14, 2015, Milan, Italy 211327, International Association of Agricultural Economists.
    6. Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2013. "Food versus Fuel: Causality and Predictability in Distribution," IEFE Working Papers 56, IEFE, Center for Research on Energy and Environmental Economics and Policy, Universita' Bocconi, Milano, Italy.
    7. Serra, Teresa & Zilberman, David, 2013. "Biofuel-related price transmission literature: A review," Energy Economics, Elsevier, vol. 37(C), pages 141-151.
    8. Pavel Ciaian & d'Artis Kancs & Miroslava Rajcaniova, 2012. "Bioenergy and Global Land Use Change," EERI Research Paper Series EERI_RP_2012_12, Economics and Econometrics Research Institute (EERI), Brussels.
    9. Karel JANDA & Jakub KOURILEK & Sarah TRABELSI, 2017. "Price Co Movement between Biodiesel and Natural Gas," Journal of Advanced Research in Management, ASERS Publishing, vol. 8(1), pages 7-16.
    10. Papież, Monika, 2014. "A dynamic analysis of causality between prices of corn, crude oil and ethanol," MPRA Paper 56540, University Library of Munich, Germany.
    11. Janda, Karel & Kourilek, Jakub, 2016. "Description of Biofuels and Shale Gas Development," MPRA Paper 74885, University Library of Munich, Germany.

  41. Ladislav Kristoufek & Miloslav Vosvrda, 2012. "Measuring capital market efficiency: Global and local correlations structure," Papers 1208.1298, arXiv.org.

    Cited by:

    1. Khalfaoui, Rabeh, 2018. "Oil–gold time varying nexus: A time–frequency analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 86-104.
    2. Kristoufek, Ladislav & Vosvrda, Miloslav, 2014. "Measuring capital market efficiency: Long-term memory, fractal dimension and approximate entropy," FinMaP-Working Papers 18, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    3. Sattarhoff, Cristina & Gronwald, Marc, 2022. "Measuring informational efficiency of the European carbon market — A quantitative evaluation of higher order dependence," International Review of Financial Analysis, Elsevier, vol. 84(C).
    4. David, S.A. & Inácio, C.M.C. & Quintino, D.D. & Machado, J.A.T., 2020. "Measuring the Brazilian ethanol and gasoline market efficiency using DFA-Hurst and fractal dimension," Energy Economics, Elsevier, vol. 85(C).
    5. Sensoy, Ahmet & Tabak, Benjamin M., 2016. "Dynamic efficiency of stock markets and exchange rates," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 353-371.
    6. Tiwari, Aviral Kumar & Kumar, Satish & Pathak, Rajesh & Roubaud, David, 2019. "Testing the oil price efficiency using various measures of long-range dependence," Energy Economics, Elsevier, vol. 84(C).
    7. Ioan Roxana, 2020. "Capital Market Correlations Structure During The Covid-19 Crisis," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 6, pages 67-79, December.
    8. Kuruppuarachchi, Duminda & Premachandra, I.M. & Roberts, Helen, 2019. "A novel market efficiency index for energy futures and their term structure risk premiums," Energy Economics, Elsevier, vol. 77(C), pages 23-33.
    9. Aviral Kumar Tiwari & R.K. Jana & Debojyoti Das & David Roubaud, 2018. "Informational efficiency of Bitcoin—An extension," Post-Print hal-02091763, HAL.
    10. Cristiana Vaz & Rui Pascoal & Helder Sebastião, 2021. "Price Appreciation and Roughness Duality in Bitcoin: A Multifractal Analysis," Mathematics, MDPI, vol. 9(17), pages 1-18, August.
    11. Aslam, Faheem & Hunjra, Ahmed Imran & Memon, Bilal Ahmed & Zhang, Mingda, 2024. "Interplay of multifractal dynamics between shadow policy rates and energy markets," The North American Journal of Economics and Finance, Elsevier, vol. 71(C).
    12. Omane-Adjepong, Maurice & Alagidede, Paul & Akosah, Nana Kwame, 2019. "Wavelet time-scale persistence analysis of cryptocurrency market returns and volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 105-120.
    13. Lee, Minhyuk & Song, Jae Wook & Kim, Sondo & Chang, Woojin, 2018. "Asymmetric market efficiency using the index-based asymmetric-MFDFA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 1278-1294.
    14. Miguel Ángel Sánchez & Juan E Trinidad & José García & Manuel Fernández, 2015. "The Effect of the Underlying Distribution in Hurst Exponent Estimation," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-17, May.
    15. Bhandari, Avishek, 2020. "Long Memory and Correlation Structures of Select Stock Returns Using Novel Wavelet and Fractal Connectivity Networks," MPRA Paper 101946, University Library of Munich, Germany.
    16. Yang Liu & Liyan Han & Libo Yin, 2018. "Does news uncertainty matter for commodity futures markets? Heterogeneity in energy and non‐energy sectors," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(10), pages 1246-1261, October.
    17. Lee, Min-Jae & Choi, Sun-Yong, 2024. "Insights into the dynamics of market efficiency spillover of financial assets in different equity markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 641(C).
    18. Ayoub Ammy-Driss & Matthieu Garcin, 2021. "Efficiency of the financial markets during the COVID-19 crisis: time-varying parameters of fractional stable dynamics," Working Papers hal-02903655, HAL.
    19. Zhuang, Xiaoyang & Wei, Yu & Ma, Feng, 2015. "Multifractality, efficiency analysis of Chinese stock market and its cross-correlation with WTI crude oil price," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 430(C), pages 101-113.
    20. Huang, Menghao & Shao, Wei & Wang, Jian, 2023. "Correlations between the crude oil market and capital markets under the Russia–Ukraine conflict: A perspective of crude oil importing and exporting countries," Resources Policy, Elsevier, vol. 80(C).
    21. Jasman Tuyon & Zamri Ahmada, 2016. "Behavioural finance perspectives on Malaysian stock market efficiency," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 16(1), pages 43-61, March.
    22. Li, Yiying & Ren, Xiaohang & Taghizadeh-Hesary, Farhad, 2023. "Vulnerability of sustainable markets to fossil energy shocks," Resources Policy, Elsevier, vol. 85(PB).
    23. Anagnostidis, P. & Varsakelis, C. & Emmanouilides, C.J., 2016. "Has the 2008 financial crisis affected stock market efficiency? The case of Eurozone," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 116-128.
    24. Zunino, Luciano & Bariviera, Aurelio F. & Guercio, M. Belén & Martinez, Lisana B. & Rosso, Osvaldo A., 2016. "Monitoring the informational efficiency of European corporate bond markets with dynamical permutation min-entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 1-9.
    25. George P. Papaioannou & Christos Dikaiakos & Akylas C. Stratigakos & Panos C. Papageorgiou & Konstantinos F. Krommydas, 2019. "Testing the Efficiency of Electricity Markets Using a New Composite Measure Based on Nonlinear TS Tools," Energies, MDPI, vol. 12(4), pages 1-30, February.
    26. Ayoub Ammy-Driss & Matthieu Garcin, 2020. "Efficiency of the financial markets during the COVID-19 crisis: time-varying parameters of fractional stable dynamics," Papers 2007.10727, arXiv.org, revised Nov 2021.
    27. Ladislav Kristoufek & Miloslav Vosvrda, 2015. "Gold, currencies and market efficiency," Papers 1510.08615, arXiv.org.
    28. Paulo Ferreira & Éder J.A.L. Pereira & Hernane B.B. Pereira, 2020. "From Big Data to Econophysics and Its Use to Explain Complex Phenomena," JRFM, MDPI, vol. 13(7), pages 1-10, July.
    29. Ma, Feng & Wei, Yu & Huang, Dengshi & Chen, Yixiang, 2014. "Which is the better forecasting model? A comparison between HAR-RV and multifractality volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 405(C), pages 171-180.
    30. Shahzad, Syed Jawad Hussain & Hernandez, Jose Areola & Hanif, Waqas & Kayani, Ghulam Mujtaba, 2018. "Intraday return inefficiency and long memory in the volatilities of forex markets and the role of trading volume," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 433-450.
    31. Sukpitak, Jessada & Hengpunya, Varagorn, 2016. "The influence of trading volume on market efficiency: The DCCA approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 458(C), pages 259-265.
    32. Matthieu Garcin, 2021. "Forecasting with fractional Brownian motion: a financial perspective," Working Papers hal-03230167, HAL.
    33. Aloosh, Arash & Choi, Hyung-Eun & Ouzan, Samuel, 2023. "The tail wagging the dog: How do meme stocks affect market efficiency?," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 68-78.
    34. Natália Costa & César Silva & Paulo Ferreira, 2019. "Long-Range Behaviour and Correlation in DFA and DCCA Analysis of Cryptocurrencies," IJFS, MDPI, vol. 7(3), pages 1-12, September.
    35. Snezana Radukic & Zoran Mastilo & Zorana Kostic & Ljubisa Vladusic, 2019. "Measuring of The Goods and Labor Markets Efficiency: Comparative Study of Western Balkan Countries," Montenegrin Journal of Economics, Economic Laboratory for Transition Research (ELIT), vol. 15(2), pages 95-109.
    36. Sensoy, Ahmet & Tabak, Benjamin M., 2015. "Time-varying long term memory in the European Union stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 147-158.
    37. Ikram Jebabli & David Roubaud, 2018. "Time-varying efficiency in food and energy markets: Evidence and implications," Post-Print hal-02330557, HAL.
    38. Majid Mirzaee Ghazani & Mohammad Ali Jafari, 2021. "Cryptocurrencies, gold, and WTI crude oil market efficiency: a dynamic analysis based on the adaptive market hypothesis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-26, December.
    39. Li, Daye & Nishimura, Yusaku & Men, Ming, 2016. "The long memory and the transaction cost in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 442(C), pages 312-320.
    40. Avishek Bhandari & Bandi Kamaiah, 2020. "Long memory in select stock returns using an alternative wavelet log-scale alignment approach," Papers 2004.08550, arXiv.org.
    41. DIMA, Bogdan & DIMA, Ştefana Maria & IOAN, Roxana, 2021. "Remarks on the behaviour of financial market efficiency during the COVID-19 pandemic. The case of VIX," Finance Research Letters, Elsevier, vol. 43(C).
    42. Guo, Yaoqi & Yao, Shanshan & Cheng, Hui & Zhu, Wensong, 2020. "China's copper futures market efficiency analysis: Based on nonlinear Granger causality and multifractal methods," Resources Policy, Elsevier, vol. 68(C).
    43. Rui Pascoal & Ana Margarida Monteiro, 2013. "Market Efficiency, Roughness and Long Memory in the PSI20 Index Returns: Wavelet and Entropy Analysis," GEMF Working Papers 2013-27, GEMF, Faculty of Economics, University of Coimbra.
    44. Lahmiri, Salim, 2016. "Clustering of Casablanca stock market based on hurst exponent estimates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 310-318.
    45. Ferreira, Paulo, 2018. "Long-range dependencies of Eastern European stock markets: A dynamic detrended analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 454-470.
    46. Ammy-Driss, Ayoub & Garcin, Matthieu, 2023. "Efficiency of the financial markets during the COVID-19 crisis: Time-varying parameters of fractional stable dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    47. Auer, Benjamin R., 2016. "On time-varying predictability of emerging stock market returns," Emerging Markets Review, Elsevier, vol. 27(C), pages 1-13.
    48. Kristoufek, Ladislav & Vosvrda, Miloslav, 2014. "Commodity futures and market efficiency," Energy Economics, Elsevier, vol. 42(C), pages 50-57.
    49. Aurelio F. Bariviera, 2020. "One model is not enough: heterogeneity in cryptocurrencies' multifractal profiles," Papers 2003.09720, arXiv.org, revised Jun 2020.
    50. Lagunas Puls, Sergio, 2022. "Fractalidad implícita en el comercio internacional [Implicit fractality in international trade]," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 33(1), pages 226-241, June.
    51. Ma, Pengcheng & Li, Daye & Li, Shuo, 2016. "Efficiency and cross-correlation in equity market during global financial crisis: Evidence from China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 163-176.
    52. Flori, Andrea, 2019. "News and subjective beliefs: A Bayesian approach to Bitcoin investments," Research in International Business and Finance, Elsevier, vol. 50(C), pages 336-356.
    53. Ashok Chanabasangouda Patil & Shailesh Rastogi, 2020. "Multifractal Analysis of Market Efficiency across Structural Breaks: Implications for the Adaptive Market Hypothesis," JRFM, MDPI, vol. 13(10), pages 1-18, October.
    54. Todea, Alexandru & Pleşoianu, Anita, 2013. "The influence of foreign portfolio investment on informational efficiency: Empirical evidence from Central and Eastern European stock markets," Economic Modelling, Elsevier, vol. 33(C), pages 34-41.
    55. Nils Bundi & Marc Wildi, 2019. "Bitcoin and market-(in)efficiency: a systematic time series approach," Digital Finance, Springer, vol. 1(1), pages 47-65, November.
    56. Benjamin Rainer Auer, 2018. "Are standard asset pricing factors long-range dependent?," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 42(1), pages 66-88, January.
    57. Nikolaos A. Kyriazis, 2019. "A Survey on Efficiency and Profitable Trading Opportunities in Cryptocurrency Markets," JRFM, MDPI, vol. 12(2), pages 1-17, April.
    58. Li, Daye & Kou, Zhun & Sun, Qiankun, 2015. "The scale-dependent market trend: Empirical evidences using the lagged DFA method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 433(C), pages 26-35.
    59. Ibarra-Valdez, C. & Alvarez, J. & Alvarez-Ramirez, J., 2016. "Randomness confidence bands of fractal scaling exponents for financial price returns," Chaos, Solitons & Fractals, Elsevier, vol. 83(C), pages 119-124.
    60. Matthieu Garcin, 2021. "Forecasting with fractional Brownian motion: a financial perspective," Papers 2105.09140, arXiv.org, revised Sep 2021.
    61. Ferreira, Paulo & Kristoufek, Ladislav & Pereira, Eder Johnson de Area Leão, 2020. "DCCA and DMCA correlations of cryptocurrency markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    62. Aslam, Faheem & Zil-e-huma, & Bibi, Rashida & Ferreira, Paulo, 2022. "Cross-correlations between economic policy uncertainty and precious and industrial metals: A multifractal cross-correlation analysis," Resources Policy, Elsevier, vol. 75(C).
    63. Sukpitak, Jessada & Hengpunya, Varagorn, 2016. "Efficiency of Thai stock markets: Detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 458(C), pages 204-209.
    64. Assaf, Ata & Kristoufek, Ladislav & Demir, Ender & Kumar Mitra, Subrata, 2021. "Market efficiency in the art markets using a combination of long memory, fractal dimension, and approximate entropy measures," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 71(C).
    65. Kristoufek, Ladislav, 2018. "On Bitcoin markets (in)efficiency and its evolution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 257-262.
    66. David Schröder, 2020. "The role of market efficiency on implied cost of capital estimates: an international perspective," Annals of Finance, Springer, vol. 16(4), pages 463-499, December.
    67. Zhang, Wei & Wang, Pengfei & Li, Xiao & Shen, Dehua, 2018. "The inefficiency of cryptocurrency and its cross-correlation with Dow Jones Industrial Average," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 658-670.
    68. José Pedro Ramos-Requena & Juan Evangelista Trinidad-Segovia & Miguel Ángel Sánchez-Granero, 2020. "Some Notes on the Formation of a Pair in Pairs Trading," Mathematics, MDPI, vol. 8(3), pages 1-17, March.
    69. Martínez Patiño, Manuel Andrés & Ariza Garzón, Miller Janny & Cadena Lozano, Javier Bernardo, 2021. "Relevancia del patrón de persistencia de Hurst en la gestión de portafolios de renta variable|| Relevance of Hurst's pattern in equity portfolio management," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 32(1), pages 66-82, December.
    70. Dima, Bogdan & Dima, Ştefana Maria, 2017. "Mutual information and persistence in the stochastic volatility of market returns: An emergent market example," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 36-59.
    71. Tiwari, Aviral Kumar & Abakah, Emmanuel Joel Aikins & Mefteh-Wali, Salma & Owusu, Patrick, 2023. "Measuring price efficiency in petroleum markets: New insights using various long-range dependence techniques," Resources Policy, Elsevier, vol. 82(C).
    72. Ferreira, Paulo, 2018. "Efficiency or speculation? A time-varying analysis of European sovereign debt," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1295-1308.
    73. Paulo Ferreira & Luís Carlos Loures, 2020. "An Econophysics Study of the S&P Global Clean Energy Index," Sustainability, MDPI, vol. 12(2), pages 1-9, January.
    74. Bhandari, Avishek, 2020. "Long memory and fractality among global equity markets: A multivariate wavelet approach," MPRA Paper 99653, University Library of Munich, Germany.
    75. Subhamitra Patra & Gourishankar S. Hiremath, 2022. "An Entropy Approach to Measure the Dynamic Stock Market Efficiency," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 20(2), pages 337-377, June.
    76. Schadner, Wolfgang, 2021. "On the persistence of market sentiment: A multifractal fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    77. Karahan, Cenk C. & Odabaşı, Attila & Tiryaki, C. Sani, 2024. "Wired together: Integration and efficiency in European electricity markets," Energy Economics, Elsevier, vol. 133(C).
    78. Andrea Flori, 2019. "Cryptocurrencies In Finance: Review And Applications," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 22(05), pages 1-22, August.
    79. Vasile Brătian & Ana-Maria Acu & Camelia Oprean-Stan & Emil Dinga & Gabriela-Mariana Ionescu, 2021. "Efficient or Fractal Market Hypothesis? A Stock Indexes Modelling Using Geometric Brownian Motion and Geometric Fractional Brownian Motion," Mathematics, MDPI, vol. 9(22), pages 1-20, November.
    80. Mahata, Ajit & Bal, Debi Prasad & Nurujjaman, Md, 2020. "Identification of short-term and long-term time scales in stock markets and effect of structural break," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    81. Ferreira, Paulo & Quintino, Derick & Wundervald, Bruna & Dionísio, Andreia & Aslam, Faheem & Cantarinha, Ana, 2021. "Is Brazilian music getting more predictable? A statistical physics approach for different music genres," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 583(C).

  42. Ladislav Kristoufek, 2012. "Multifractal Height Cross-Correlation Analysis: A New Method for Analyzing Long-Range Cross-Correlations," Papers 1201.3473, arXiv.org, revised Jan 2012.

    Cited by:

    1. Kristoufek, Ladislav, 2013. "Mixed-correlated ARFIMA processes for power-law cross-correlations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(24), pages 6484-6493.
    2. Ladislav Kristoufek, 2013. "Detrending moving-average cross-correlation coefficient: Measuring cross-correlations between non-stationary series," Papers 1311.0657, arXiv.org.
    3. Ladislav Kristoufek, 2016. "Power-law cross-correlations estimation under heavy tails," Papers 1602.05385, arXiv.org, revised Apr 2016.
    4. Kristoufek, Ladislav, 2014. "Measuring correlations between non-stationary series with DCCA coefficient," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 402(C), pages 291-298.
    5. Wang, Xuan & Guo, Kun & Lu, Xiaolin, 2016. "The long-run dynamic relationship between exchange rate and its attention index: Based on DCCA and TOP method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 453(C), pages 108-115.
    6. Fan, Xiaoqian & Yuan, Ying & Zhuang, Xintian & Jin, Xiu, 2017. "Long memory of abnormal investor attention and the cross-correlations between abnormal investor attention and trading volume, volatility respectively," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 323-333.
    7. Kristoufek, Ladislav, 2015. "Finite sample properties of power-law cross-correlations estimators," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 513-525.
    8. Ladislav Kristoufek, 2014. "Spectrum-based estimators of the bivariate Hurst exponent," Papers 1408.6637, arXiv.org, revised Nov 2014.
    9. Morales, Raffaello & Di Matteo, T. & Aste, Tomaso, 2013. "Non-stationary multifractality in stock returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(24), pages 6470-6483.
    10. Zebende, G.F. & da Silva, M.F. & Machado Filho, A., 2013. "DCCA cross-correlation coefficient differentiation: Theoretical and practical approaches," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(8), pages 1756-1761.
    11. Ladislav Kristoufek, 2013. "Testing power-law cross-correlations: Rescaled covariance test," Papers 1307.4727, arXiv.org, revised Aug 2013.
    12. Ladislav Kristoufek, 2012. "Fractal Markets Hypothesis and the Global Financial Crisis: Scaling, Investment Horizons and Liquidity," Papers 1203.4979, arXiv.org.
    13. Yao, Can-Zhong & Liu, Cheng & Ju, Wei-Jia, 2020. "Multifractal analysis of the WTI crude oil market, US stock market and EPU," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 550(C).
    14. Cao, Guangxi & Zhang, Minjia & Li, Qingchen, 2017. "Volatility-constrained multifractal detrended cross-correlation analysis: Cross-correlation among Mainland China, US, and Hong Kong stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 472(C), pages 67-76.

  43. Ladislav Kristoufek, 2012. "How are rescaled range analyses affected by different memory and distributional properties? A Monte Carlo study," Papers 1201.3511, arXiv.org.

    Cited by:

    1. Kristoufek, Ladislav & Vosvrda, Miloslav, 2014. "Measuring capital market efficiency: Long-term memory, fractal dimension and approximate entropy," FinMaP-Working Papers 18, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    2. David, S.A. & Inácio, C.M.C. & Quintino, D.D. & Machado, J.A.T., 2020. "Measuring the Brazilian ethanol and gasoline market efficiency using DFA-Hurst and fractal dimension," Energy Economics, Elsevier, vol. 85(C).
    3. Ladislav Kristoufek, 2014. "Leverage effect in energy futures," Papers 1403.0064, arXiv.org.
    4. Hull, Matthew & McGroarty, Frank, 2014. "Do emerging markets become more efficient as they develop? Long memory persistence in equity indices," Emerging Markets Review, Elsevier, vol. 18(C), pages 45-61.
    5. Anagnostidis, P. & Varsakelis, C. & Emmanouilides, C.J., 2016. "Has the 2008 financial crisis affected stock market efficiency? The case of Eurozone," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 116-128.
    6. Zunino, Luciano & Bariviera, Aurelio F. & Guercio, M. Belén & Martinez, Lisana B. & Rosso, Osvaldo A., 2016. "Monitoring the informational efficiency of European corporate bond markets with dynamical permutation min-entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 1-9.
    7. Auer, Benjamin R., 2016. "On the performance of simple trading rules derived from the fractal dynamics of gold and silver price fluctuations," Finance Research Letters, Elsevier, vol. 16(C), pages 255-267.
    8. Benjamin R Auer, 2016. "Pure return persistence, Hurst exponents and hedge fund selection – A practical note," Journal of Asset Management, Palgrave Macmillan, vol. 17(5), pages 319-330, September.
    9. Ladislav Kristoufek & Miloslav Vosvrda, 2012. "Measuring capital market efficiency: Global and local correlations structure," Papers 1208.1298, arXiv.org.
    10. Auer, Benjamin R., 2016. "On time-varying predictability of emerging stock market returns," Emerging Markets Review, Elsevier, vol. 27(C), pages 1-13.
    11. Kristoufek, Ladislav & Vosvrda, Miloslav, 2014. "Commodity futures and market efficiency," Energy Economics, Elsevier, vol. 42(C), pages 50-57.
    12. Kristoufek, Ladislav, 2019. "Are the crude oil markets really becoming more efficient over time? Some new evidence," Energy Economics, Elsevier, vol. 82(C), pages 253-263.
    13. Benjamin Rainer Auer, 2018. "Are standard asset pricing factors long-range dependent?," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 42(1), pages 66-88, January.
    14. Ladislav Kristoufek, 2013. "Testing power-law cross-correlations: Rescaled covariance test," Papers 1307.4727, arXiv.org, revised Aug 2013.
    15. Auer, Benjamin R. & Hoffmann, Andreas, 2016. "Do carry trade returns show signs of long memory?," The Quarterly Review of Economics and Finance, Elsevier, vol. 61(C), pages 201-208.

  44. Lukas Vacha & Karel Janda & Ladislav Kristoufek & David Zilberman, 2012. "Time-Frequency Dynamics of Biofuels-Fuels-Food System," Papers 1209.0900, arXiv.org.

    Cited by:

    1. Capitani, Daniel Henrique Dario & Gaio, Luiz Eduardo, 2023. "Volatility Transmissionin Agricultural Markets: Evidence from the Russia-Ukraine Conflict," International Journal of Food and Agricultural Economics (IJFAEC), Alanya Alaaddin Keykubat University, Department of Economics and Finance, vol. 11(2), April.
    2. Capitani, Daniel Henrique Dario & Tonin, Julyerme M. & Cruz, Jose Cesar, 2017. "Integration and hedging efficiency between the Brazilian and the U.S. ethanol markets," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258520, Agricultural and Applied Economics Association.
    3. Ladislav Kristoufek, 2013. "Fractal Markets Hypothesis and the Global Financial Crisis: Wavelet Power Evidence," Papers 1310.1446, arXiv.org.
    4. Piroli, Giuseppe & Rajcaniova, Miroslava & Ciaian, Pavel & Kancs, d׳Artis, 2015. "From a rise in B to a fall in C? SVAR analysis of environmental impact of biofuels," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 921-930.
    5. Tiwari, Aviral Kumar & Nasreen, Samia & Shahbaz, Muhammad & Hammoudeh, Shawkat, 2020. "Time-frequency causality and connectedness between international prices of energy, food, industry, agriculture and metals," Energy Economics, Elsevier, vol. 85(C).
    6. Pick Schen Yip & Robert Brooks & Hung Xuan Do & Duc Khuong Nguyen, 2019. "Dynamic Volatility Spillover Effect between Oil and Agricultural Products," Working Papers 2019-009, Department of Research, Ipag Business School.
    7. Ofentse, Goetswamang Phankie, 2022. "Evaluation of the prospects of hedging Botswana's maize prices against the Johannesburg Stock Exchange Commodity Market Derivative," Research Theses 334751, Collaborative Masters Program in Agricultural and Applied Economics.
    8. Semih Emre Cekin & Besma Hkiri & Aviral Kumar Tiwari & Rangan Gupta, 2019. "The Relationship between Monetary Policy and Uncertainty in Advanced Economies: Evidence from Time- and Frequency-Domains," Working Papers 201904, University of Pretoria, Department of Economics.
    9. Pavla BLAHOVA & Karel JANDA & Ladislav KRISTOUFEK, 2014. "The perspectives for genetically modified cellulosic biofuels in the Central European conditions," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 60(6), pages 247-259.
    10. Wei Su, Chi & Wang, Xiao-Qing & Tao, Ran & Oana-Ramona, Lobonţ, 2019. "Do oil prices drive agricultural commodity prices? Further evidence in a global bio-energy context," Energy, Elsevier, vol. 172(C), pages 691-701.
    11. Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2013. "Biofuels and Food Prices: Searching for the Causal Link," Working Papers 239, University of Milano-Bicocca, Department of Economics, revised Mar 2013.
    12. Guo, Jin & Tanaka, Tetsuji, 2022. "Energy security versus food security: An analysis of fuel ethanol- related markets using the spillover index and partial wavelet coherence approaches," Energy Economics, Elsevier, vol. 112(C).
    13. Manuel Monge & Luis A. Gil-Alana, 2020. "The Lithium Industry and Analysis of the Beta Term Structure of Oil Companies," Risks, MDPI, vol. 8(4), pages 1-17, December.
    14. Chowdhury, Mohammad Ashraful Ferdous & Meo, Muhammad Saeed & Uddin, Ajim & Haque, Md. Mahmudul, 2021. "Asymmetric effect of energy price on commodity price: New evidence from NARDL and time frequency wavelet approaches," Energy, Elsevier, vol. 231(C).
    15. Urom, Christian & Mzoughi, Hela & Abid, Ilyes & Brahim, Mariem, 2021. "Green markets integration in different time scales: A regional analysis," Energy Economics, Elsevier, vol. 98(C).
    16. Dong, Minyi & Chang, Chun-Ping & Gong, Qiang & Chu, Yin, 2019. "Revisiting global economic activity and crude oil prices: A wavelet analysis," Economic Modelling, Elsevier, vol. 78(C), pages 134-149.
    17. Deborah Bentivoglio & Adele Finco & Mirian Rumenos Piedade Bacchi, 2016. "Interdependencies between Biofuel, Fuel and Food Prices: The Case of the Brazilian Ethanol Market," Energies, MDPI, vol. 9(6), pages 1-16, June.
    18. Bentivoglio, Deborah & Finco, Adele & Bacchi, Mirian, 2015. "Examining Price Transmission between Fuels and Food Prices: the Brazilian Sugar-Ethanol Market," 2015 Conference, August 9-14, 2015, Milan, Italy 211327, International Association of Agricultural Economists.
    19. Štěpán Chrz & Karel Janda & Ladislav Krištoufek, 2014. "Modelování provázanosti trhů potravin, biopaliv a fosilních paliv [Modeling Interconnections within Food, Biofuel, and Fossil Fuel Markets]," Politická ekonomie, Prague University of Economics and Business, vol. 2014(1), pages 117-140.
    20. Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2013. "Food versus Fuel: Causality and Predictability in Distribution," IEFE Working Papers 56, IEFE, Center for Research on Energy and Environmental Economics and Policy, Universita' Bocconi, Milano, Italy.
    21. Zhang, Chuanguo & Qu, Xuqin, 2015. "The effect of global oil price shocks on China's agricultural commodities," Energy Economics, Elsevier, vol. 51(C), pages 354-364.
    22. Pal, Debdatta & Mitra, Subrata K., 2017. "Time-frequency contained co-movement of crude oil and world food prices: A wavelet-based analysis," Energy Economics, Elsevier, vol. 62(C), pages 230-239.
    23. Cheng, Sheng & Cao, Yan, 2019. "On the relation between global food and crude oil prices: An empirical investigation in a nonlinear framework," Energy Economics, Elsevier, vol. 81(C), pages 422-432.
    24. Ondrej Filip & Karel Janda & Ladislav Kristoufek & David Zilberman, 2017. "Food versus Fuel: An Updated and Expanded Evidence," Working Papers IES 2017/26, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Nov 2017.
    25. Nigatu, Getachew & Adjemian, Michael K., 2016. "The U.S. Role in the Price Determination of Major Agricultural Commodities," 2017 Allied Social Sciences Association (ASSA) Annual Meeting, January 6-8, 2017, Chicago, Illinois 250119, Agricultural and Applied Economics Association.
    26. Tan Ngoc Vu & Duc Hong Vo & Chi Minh Ho & Loan Thi-Hong Van, 2019. "Modeling the Impact of Agricultural Shocks on Oil Price in the US: A New Approach," JRFM, MDPI, vol. 12(3), pages 1-27, September.
    27. Sun, Xiaolei & Yao, Xiaoyang & Wang, Jun, 2017. "Dynamic interaction between economic policy uncertainty and financial stress: A multi-scale correlation framework," Finance Research Letters, Elsevier, vol. 21(C), pages 214-221.
    28. Abid, Fathi & Kaffel, Bilel, 2018. "Time–frequency wavelet analysis of the interrelationship between the global macro assets and the fear indexes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1028-1045.
    29. Capitani, Daniel Henrique Dario, 2014. "Biofuels versus food: How much Brazilian ethanol production can affect domestic food prices," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170267, Agricultural and Applied Economics Association.
    30. Xiangcai Meng, 2018. "Does Agricultural Commodity Price Co-move with Oil Price in the Time-Frequency Space? Evidence from the Republic of Korea," International Journal of Energy Economics and Policy, Econjournals, vol. 8(4), pages 125-133.
    31. Gołębiewski, Jarosław & Kucher, Oleg, 2020. "Development Of The Biofuel Market In The Ukraine," Roczniki (Annals), Polish Association of Agricultural Economists and Agribusiness - Stowarzyszenie Ekonomistow Rolnictwa e Agrobiznesu (SERiA), vol. 2020(1).
    32. Karel Janda & Ladislav Kristoufek, 2019. "The relationship between fuel and food prices: Methods, outcomes, and lessons for commodity price risk management," CAMA Working Papers 2019-20, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    33. Xiao Jing Cai & Zheng Fang & Youngho Chang & Shuairu Tian & Shigeyuki Hamori, 2020. "Co-movements in commodity markets and implications in diversification benefits," Empirical Economics, Springer, vol. 58(2), pages 393-425, February.
    34. Monika Roman & Aleksandra Górecka & Joanna Domagała, 2020. "The Linkages between Crude Oil and Food Prices," Energies, MDPI, vol. 13(24), pages 1-18, December.
    35. Fan He & Xuansen He, 2019. "A Continuous Differentiable Wavelet Shrinkage Function for Economic Data Denoising," Computational Economics, Springer;Society for Computational Economics, vol. 54(2), pages 729-761, August.
    36. Fernandez-Perez, Adrian & Frijns, Bart & Tourani-Rad, Alireza, 2016. "Contemporaneous interactions among fuel, biofuel and agricultural commodities," Energy Economics, Elsevier, vol. 58(C), pages 1-10.
    37. Ladislav Kristoufek & Karel Janda & David Zilberman, 2015. "Co-movements of Ethanol Related Prices: Evidence from Brazil and the USA," CAMA Working Papers 2015-11, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    38. Giray GOZGOR & Cahit MEMIS, 2015. "Price volatility spillovers among agricultural commodity and crude oil markets: Evidence from the range-based estimator," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 61(5), pages 214-221.
    39. Mensi, Walid & Tiwari, Aviral & Bouri, Elie & Roubaud, David & Al-Yahyaee, Khamis H., 2017. "The dependence structure across oil, wheat, and corn: A wavelet-based copula approach using implied volatility indexes," Energy Economics, Elsevier, vol. 66(C), pages 122-139.
    40. Jiang, Yonghong & Lao, Jiashun & Mo, Bin & Nie, He, 2018. "Dynamic linkages among global oil market, agricultural raw material markets and metal markets: An application of wavelet and copula approaches," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 265-279.
    41. Han, Liyan & Zhou, Yimin & Yin, Libo, 2015. "Exogenous impacts on the links between energy and agricultural commodity markets," Energy Economics, Elsevier, vol. 49(C), pages 350-358.
    42. Tanaka, Tetsuji & Guo, Jin & Wang, Xiufang, 2023. "Did biofuel production strengthen the comovements between food and fuel prices? Evidence from ethanol-related markets in the United States," Renewable Energy, Elsevier, vol. 217(C).
    43. Spencer, Simon & Bredin, Don & Conlon, Thomas, 2018. "Energy and agricultural commodities revealed through hedging characteristics: Evidence from developing and mature markets," Journal of Commodity Markets, Elsevier, vol. 9(C), pages 1-20.
    44. Capitani, Daniel H D & Gaio, Luiz Eduardo & Mattos, Fabio L. & Franco Da Silveira, Rodrigo Lanna & Cruz, Jose Cesar, 2024. "Corn ethanol expansion in Brazil: Are volatility interconnectedness changing?," 2024 Annual Meeting, July 28-30, New Orleans, LA 343612, Agricultural and Applied Economics Association.
    45. Wu, JunJie & Sexton, Steven & Zilberman, David, 2019. "Energy price shocks, household location patterns and housing crises: Theory and implications," Energy Economics, Elsevier, vol. 80(C), pages 691-706.
    46. Reboredo, Juan C. & Rivera-Castro, Miguel A. & Ugolini, Andrea, 2017. "Wavelet-based test of co-movement and causality between oil and renewable energy stock prices," Energy Economics, Elsevier, vol. 61(C), pages 241-252.
    47. Ondřej Filip & Karel Janda & Ladislav Krištoufek, 2018. "Ceny biopaliv a souvisejících komodit: analýza s použitím metod minimální kostry grafu a hierarchických stromů [Prices of Biofuels and Related Commodities: an Analysis Using Methods of Minimum Span," Politická ekonomie, Prague University of Economics and Business, vol. 2018(2), pages 218-239.
    48. Chrz, Stepan & Hruby, Zdenek & Janda, Karel & Kristoufek, Ladislav, 2013. "Provazanost trhu potravin, biopaliv a fosilnich paliv [Interconnections within food, biofuel, and fossil fuel markets]," MPRA Paper 43958, University Library of Munich, Germany.
    49. Janda, Karel & Kravec, Peter, 2022. "VECM Modelling of the Price Dynamics for Fuels, Agricultural Commodities and Biofuels," EconStor Preprints 259404, ZBW - Leibniz Information Centre for Economics.
    50. Wang, Yudong & Wu, Chongfeng & Yang, Li, 2014. "Oil price shocks and agricultural commodity prices," Energy Economics, Elsevier, vol. 44(C), pages 22-35.
    51. Sun, Xiaolei & Chen, Xiuwen & Wang, Jun & Li, Jianping, 2020. "Multi-scale interactions between economic policy uncertainty and oil prices in time-frequency domains," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    52. Ben-Salha, Ousama & Hkiri, Besma & Aloui, Chaker, 2018. "Sectoral energy consumption by source and output in the U.S.: New evidence from wavelet-based approach," Energy Economics, Elsevier, vol. 72(C), pages 75-96.
    53. Trujillo-Barrera, Andres & Pennings, Joost M.E., 2013. "Energy and Food Commodity Prices Linkage: An Examination with Mixed-Frequency Data," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150465, Agricultural and Applied Economics Association.
    54. Sousa, Rita & Aguiar-Conraria, Luís & Soares, Maria Joana, 2014. "Carbon financial markets: A time–frequency analysis of CO2 prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 414(C), pages 118-127.
    55. Janda, Karel & Krska, Stepan & Prusa, Jan, 2014. "Odhad nákladů na podporu české fotovoltaické energie [The Estimation of the Cost of Promotion of the Czech Photovoltaic Energy]," MPRA Paper 54108, University Library of Munich, Germany.

  45. Ladislav Kristoufek, 2012. "Fractal Markets Hypothesis and the Global Financial Crisis: Scaling, Investment Horizons and Liquidity," Papers 1203.4979, arXiv.org.

    Cited by:

    1. Buonocore, R.J. & Aste, T. & Di Matteo, T., 2016. "Measuring multiscaling in financial time-series," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 38-47.
    2. Ladislav Kristoufek, 2013. "Fractal Markets Hypothesis and the Global Financial Crisis: Wavelet Power Evidence," Papers 1310.1446, arXiv.org.
    3. Zhang, Guofu & Li, Jingjing, 2018. "Multifractal analysis of Shanghai and Hong Kong stock markets before and after the connect program," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 611-622.
    4. Emrah BALKAN & Umut UYAR, 2022. "The Fractal Structure of CDS Spreads: Evidence from the OECD Countries," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 106-121, April.
    5. Lee, Minhyuk & Song, Jae Wook & Kim, Sondo & Chang, Woojin, 2018. "Asymmetric market efficiency using the index-based asymmetric-MFDFA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 1278-1294.
    6. Oussama Tilfani & Paulo Ferreira & My Youssef El Boukfaoui, 2021. "Dynamic cross-correlation and dynamic contagion of stock markets: a sliding windows approach with the DCCA correlation coefficient," Empirical Economics, Springer, vol. 60(3), pages 1127-1156, March.
    7. Miguel Ángel Sánchez & Juan E Trinidad & José García & Manuel Fernández, 2015. "The Effect of the Underlying Distribution in Hurst Exponent Estimation," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-17, May.
    8. Domino, Krzysztof & Błachowicz, Tomasz, 2014. "The use of copula functions for modeling the risk of investment in shares traded on the Warsaw Stock Exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 77-85.
    9. Peter Albrecht & Svatopluk Kapounek & Zuzana Kučerová, 2023. "Economic policy uncertainty and stock markets’ co‐movements," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 3471-3487, October.
    10. Vogl, Markus, 2023. "Hurst exponent dynamics of S&P 500 returns: Implications for market efficiency, long memory, multifractality and financial crises predictability by application of a nonlinear dynamics analysis framewo," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
    11. Anagnostidis, P. & Varsakelis, C. & Emmanouilides, C.J., 2016. "Has the 2008 financial crisis affected stock market efficiency? The case of Eurozone," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 116-128.
    12. Sensoy, Ahmet & Tabak, Benjamin M., 2015. "Time-varying long term memory in the European Union stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 147-158.
    13. Ikram Jebabli & David Roubaud, 2018. "Time-varying efficiency in food and energy markets: Evidence and implications," Post-Print hal-02330557, HAL.
    14. Eric Kemp-Benedict, 2012. "Price and Quantity Trajectories: Second-order Dynamics," Papers 1204.3156, arXiv.org.
    15. Li, Daye & Nishimura, Yusaku & Men, Ming, 2016. "The long memory and the transaction cost in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 442(C), pages 312-320.
    16. Kristoufek, Ladislav, 2018. "Fractality in market risk structure: Dow Jones Industrial components case," Chaos, Solitons & Fractals, Elsevier, vol. 110(C), pages 69-75.
    17. Ladislav Kristoufek & Miloslav Vosvrda, 2012. "Measuring capital market efficiency: Global and local correlations structure," Papers 1208.1298, arXiv.org.
    18. Paritosh Chandra SINHA & Pooja AGARWAL, 2021. "COVID-19 and CAPM: a tale of reference dependence with the pharma stocks’ returns," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 0(2(627), S), pages 45-82, Summer.
    19. Ma, Pengcheng & Li, Daye & Li, Shuo, 2016. "Efficiency and cross-correlation in equity market during global financial crisis: Evidence from China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 163-176.
    20. Horta, Paulo & Lagoa, Sérgio & Martins, Luís, 2014. "The impact of the 2008 and 2010 financial crises on the Hurst exponents of international stock markets: Implications for efficiency and contagion," International Review of Financial Analysis, Elsevier, vol. 35(C), pages 140-153.
    21. Domino, Krzysztof & Błachowicz, Tomasz, 2015. "The use of copula functions for modeling the risk of investment in shares traded on world stock exchanges," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 142-151.
    22. Sifat, Imtiaz Mohammad & Thaker, Hassanudin Mohd Thas, 2020. "Predictive power of web search behavior in five ASEAN stock markets," Research in International Business and Finance, Elsevier, vol. 52(C).
    23. Sobolev, Daphne, 2017. "The effect of price volatility on judgmental forecasts: The correlated response model," International Journal of Forecasting, Elsevier, vol. 33(3), pages 605-617.
    24. Sun, Xuelian & Liu, Zixian, 2016. "Optimal portfolio strategy with cross-correlation matrix composed by DCCA coefficients: Evidence from the Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 667-679.
    25. Aslam, Faheem & Zil-e-huma, & Bibi, Rashida & Ferreira, Paulo, 2022. "Cross-correlations between economic policy uncertainty and precious and industrial metals: A multifractal cross-correlation analysis," Resources Policy, Elsevier, vol. 75(C).
    26. Ferreira, Paulo & Loures, Luís & Nunes, José & Brito, Paulo, 2018. "Are renewable energy stocks a possibility to diversify portfolios considering an environmentally friendly approach? The view of DCCA correlation coefficient," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 675-681.
    27. L.J. Basson & Sune Ferreira-Schenk & Zandri Dickason-Koekemoer, 2022. "Fractal Dimension Option Hedging Strategy Implementation During Turbulent Market Conditions in Developing and Developed Countries," International Journal of Economics and Financial Issues, Econjournals, vol. 12(2), pages 84-95, March.
    28. Deniz Erer & Elif Erer & Selim Güngör, 2023. "The aggregate and sectoral time-varying market efficiency during crisis periods in Turkey: a comparative analysis with COVID-19 outbreak and the global financial crisis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-25, December.

  46. Jozef Barunik & Ladislav Kristoufek, 2012. "On Hurst exponent estimation under heavy-tailed distributions," Papers 1201.4786, arXiv.org.

    Cited by:

    1. Fernández-Martínez, M. & Sánchez-Granero, M.A. & Trinidad Segovia, J.E., 2013. "Measuring the self-similarity exponent in Lévy stable processes of financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(21), pages 5330-5345.
    2. Kristoufek, Ladislav & Vosvrda, Miloslav, 2014. "Measuring capital market efficiency: Long-term memory, fractal dimension and approximate entropy," FinMaP-Working Papers 18, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    3. Ladislav Kristoufek, 2015. "Power-law correlations in finance-related Google searches, and their cross-correlations with volatility and traded volume: Evidence from the Dow Jones Industrial components," Papers 1502.00225, arXiv.org.
    4. Buonocore, R.J. & Aste, T. & Di Matteo, T., 2016. "Measuring multiscaling in financial time-series," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 38-47.
    5. Kristoufek, Ladislav, 2013. "Mixed-correlated ARFIMA processes for power-law cross-correlations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(24), pages 6484-6493.
    6. Ferreira, Paulo & Kristoufek, Ladislav, 2017. "What is new about covered interest parity condition in the European Union? Evidence from fractal cross-correlation regressions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 554-566.
    7. Dutta, Srimonti & Ghosh, Dipak & Chatterjee, Sucharita, 2016. "Multifractal detrended Cross Correlation Analysis of Foreign Exchange and SENSEX fluctuation in Indian perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 463(C), pages 188-201.
    8. Tiwari, Aviral Kumar & Umar, Zaghum & Alqahtani, Faisal, 2021. "Existence of long memory in crude oil and petroleum products: Generalised Hurst exponent approach," Research in International Business and Finance, Elsevier, vol. 57(C).
    9. Barunik, Jozef & Aste, Tomaso & Di Matteo, T. & Liu, Ruipeng, 2012. "Understanding the source of multifractality in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(17), pages 4234-4251.
    10. Hiremath, Gourishankar S. & Kattuman, Paul, 2017. "Foreign portfolio flows and emerging stock market: Is the midnight bell ringing in India?," Research in International Business and Finance, Elsevier, vol. 42(C), pages 544-558.
    11. Sensoy, Ahmet & Tabak, Benjamin M., 2016. "Dynamic efficiency of stock markets and exchange rates," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 353-371.
    12. Raffaello Morales & T. Di Matteo & Ruggero Gramatica & Tomaso Aste, 2011. "Dynamical Hurst exponent as a tool to monitor unstable periods in financial time series," Papers 1109.0465, arXiv.org.
    13. Zunino, Luciano & Tabak, Benjamin M. & Serinaldi, Francesco & Zanin, Massimiliano & Pérez, Darío G. & Rosso, Osvaldo A., 2011. "Commodity predictability analysis with a permutation information theory approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(5), pages 876-890.
    14. Zhang, Guofu & Li, Jingjing, 2018. "Multifractal analysis of Shanghai and Hong Kong stock markets before and after the connect program," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 611-622.
    15. Riccardo Junior Buonocore & Tomaso Aste & Tiziana Di Matteo, 2015. "Measuring multiscaling in financial time-series," Papers 1509.05471, arXiv.org, revised Sep 2015.
    16. Lahmiri, Salim, 2017. "On fractality and chaos in Moroccan family business stock returns and volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 29-39.
    17. Ladislav Kristoufek, 2014. "Leverage effect in energy futures," Papers 1403.0064, arXiv.org.
    18. Mynhardt, H. R. & Plastun, Alex & Makarenko, Inna, 2014. "Behavior of Financial Markets Efficiency During the Financial Market Crisis: 2007-2009," MPRA Paper 58942, University Library of Munich, Germany.
    19. Song, Wanqing & Li, Ming & Li, Yuanyuan & Cattani, Carlo & Chi, Chi-Hung, 2019. "Fractional Brownian motion: Difference iterative forecasting models," Chaos, Solitons & Fractals, Elsevier, vol. 123(C), pages 347-355.
    20. Corzo Santamaría, Teresa & Martin-Bujack, Karin & Portela, Jose & Sáenz-Diez, Rocio, 2022. "Early market efficiency testing among hydrogen players," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 723-742.
    21. Ioannis P. Antoniades & Giuseppe Brandi & L. G. Magafas & T. Di Matteo, 2020. "The use of scaling properties to detect relevant changes in financial time series: a new visual warning tool," Papers 2010.08890, arXiv.org, revised Dec 2020.
    22. Aslan, Aylin & Sensoy, Ahmet, 2020. "Intraday efficiency-frequency nexus in the cryptocurrency markets," Finance Research Letters, Elsevier, vol. 35(C).
    23. Jiang, Yonghong & Nie, He & Ruan, Weihua, 2018. "Time-varying long-term memory in Bitcoin market," Finance Research Letters, Elsevier, vol. 25(C), pages 280-284.
    24. Morales, Raffaello & Di Matteo, T. & Gramatica, Ruggero & Aste, Tomaso, 2012. "Dynamical generalized Hurst exponent as a tool to monitor unstable periods in financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(11), pages 3180-3189.
    25. Ladislav Kristoufek, 2013. "Detrending moving-average cross-correlation coefficient: Measuring cross-correlations between non-stationary series," Papers 1311.0657, arXiv.org.
    26. Kristoufek, Ladislav, 2010. "On spurious anti-persistence in the US stock indices," Chaos, Solitons & Fractals, Elsevier, vol. 43(1), pages 68-78.
    27. Chiarucci, Riccardo & Loffredo, Maria I. & Ruzzenenti, Franco, 2017. "Evidences for a structural change in the oil market before a financial crisis: The flat horizon effect," Research in International Business and Finance, Elsevier, vol. 42(C), pages 912-921.
    28. Ferreira, Paulo & Kristoufek, Ladislav, 2020. "Uncovered interest rate parity through the lens of fractal methods: Evidence from the European Union," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 553(C).
    29. Ludwig O. Dittrich & Pavel Srbek, 2020. "Is Violation of the Random Walk Assumption an Exception or a Rule in Capital Markets?," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 48(4), pages 491-501, December.
    30. Pakrashi, Vikram & Kelly, Joe & Harkin, Julie & Farrell, Aidan, 2013. "Hurst exponent footprints from activities on a large structural system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(8), pages 1803-1817.
    31. Estefanía Montoya-Cruz & José Pedro Ramos-Requena & Juan Evangelista Trinidad-Segovia & Miguel Ángel Sánchez-Granero, 2020. "Exploring Arbitrage Strategies in Corporate Social Responsibility Companies," Sustainability, MDPI, vol. 12(16), pages 1-17, August.
    32. Martin Rypdal & Espen Sirnes & Ola L{o}vsletten & Kristoffer Rypdal, 2012. "Assessing market uncertainty by means of a time-varying intermittency parameter for asset price fluctuations," Papers 1202.4877, arXiv.org.
    33. Wei, Yu & Wang, Yudong & Huang, Dengshi, 2011. "A copula–multifractal volatility hedging model for CSI 300 index futures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4260-4272.
    34. John Goddard & Enrico Onali, 2014. "Self-affinity in financial asset returns," Papers 1401.7170, arXiv.org.
    35. Ladislav Kristoufek & Paulo Ferreira, 2018. "Capital asset pricing model in Portugal: Evidence from fractal regressions," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 17(3), pages 173-183, November.
    36. Guglielmo Maria Caporale & Luis A. Gil-Alana & Alex Plastun, 2017. "Long Memory and Data Frequency in Financial Markets," CESifo Working Paper Series 6396, CESifo.
    37. Ladislav KRISTOUFEK & Petra LUNACKOVA, 2013. "Long-term Memory in Electricity Prices: Czech Market Evidence," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(5), pages 407-424, November.
    38. Ladislav Kristoufek, 2016. "Power-law cross-correlations estimation under heavy tails," Papers 1602.05385, arXiv.org, revised Apr 2016.
    39. Gómez-Águila, A. & Sánchez-Granero, M.A., 2021. "A theoretical framework for the TTA algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 582(C).
    40. Jia, Zhanliang & Cui, Meilan & Li, Handong, 2012. "Research on the relationship between the multifractality and long memory of realized volatility in the SSECI," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(3), pages 740-749.
    41. Anagnostidis, P. & Varsakelis, C. & Emmanouilides, C.J., 2016. "Has the 2008 financial crisis affected stock market efficiency? The case of Eurozone," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 116-128.
    42. Lahmiri, Salim, 2018. "Generalized Hurst exponent estimates differentiate EEG signals of healthy and epileptic patients," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 378-385.
    43. Zunino, Luciano & Bariviera, Aurelio F. & Guercio, M. Belén & Martinez, Lisana B. & Rosso, Osvaldo A., 2016. "Monitoring the informational efficiency of European corporate bond markets with dynamical permutation min-entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 1-9.
    44. Ramos-Requena, J.P. & Trinidad-Segovia, J.E. & Sánchez-Granero, M.A., 2017. "Introducing Hurst exponent in pair trading," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 488(C), pages 39-45.
    45. Ladislav Kristoufek & Miloslav Vosvrda, 2015. "Gold, currencies and market efficiency," Papers 1510.08615, arXiv.org.
    46. Un, Kuok Sin & Ausloos, Marcel, 2022. "Equity premium prediction: Taking into account the role of long, even asymmetric, swings in stock market behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P1).
    47. Auer, Benjamin R., 2016. "On the performance of simple trading rules derived from the fractal dynamics of gold and silver price fluctuations," Finance Research Letters, Elsevier, vol. 16(C), pages 255-267.
    48. Benjamin R Auer, 2016. "Pure return persistence, Hurst exponents and hedge fund selection – A practical note," Journal of Asset Management, Palgrave Macmillan, vol. 17(5), pages 319-330, September.
    49. Ailie Charteris & Conrad Alexander Steyn, 2023. "The Bank of Japan’s exchange traded fund purchases: a help or hindrance to market efficiency?," Journal of Asset Management, Palgrave Macmillan, vol. 24(3), pages 225-240, May.
    50. Sensoy, Ahmet & Tabak, Benjamin M., 2015. "Time-varying long term memory in the European Union stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 147-158.
    51. Ikram Jebabli & David Roubaud, 2018. "Time-varying efficiency in food and energy markets: Evidence and implications," Post-Print hal-02330557, HAL.
    52. Kristoufek, Ladislav, 2012. "How are rescaled range analyses affected by different memory and distributional properties? A Monte Carlo study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(17), pages 4252-4260.
    53. Sensoy, A., 2013. "Effects of monetary policy on the long memory in interest rates: Evidence from an emerging market," Chaos, Solitons & Fractals, Elsevier, vol. 57(C), pages 85-88.
    54. Li, Daye & Nishimura, Yusaku & Men, Ming, 2016. "The long memory and the transaction cost in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 442(C), pages 312-320.
    55. Emilian DOBRESCU, 2016. "Controversies over the Size of the Public Budget," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 5-34, December.
    56. Kristoufek, Ladislav, 2015. "Finite sample properties of power-law cross-correlations estimators," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 513-525.
    57. Kristoufek, Ladislav, 2018. "Fractality in market risk structure: Dow Jones Industrial components case," Chaos, Solitons & Fractals, Elsevier, vol. 110(C), pages 69-75.
    58. Lahmiri, Salim, 2016. "Clustering of Casablanca stock market based on hurst exponent estimates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 310-318.
    59. Ladislav Kristoufek, 2018. "Power-law cross-correlations: Issues, solutions and future challenges," Papers 1806.01616, arXiv.org.
    60. Morales, Raffaello & Di Matteo, T. & Aste, Tomaso, 2013. "Non-stationary multifractality in stock returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(24), pages 6470-6483.
    61. Ladislav Kristoufek & Miloslav Vosvrda, 2012. "Measuring capital market efficiency: Global and local correlations structure," Papers 1208.1298, arXiv.org.
    62. Li, Daye & Nishimura, Yusaku & Men, Ming, 2016. "Why the long-term auto-correlation has not been eliminated by arbitragers: Evidences from NYMEX," Energy Economics, Elsevier, vol. 59(C), pages 167-178.
    63. Auer, Benjamin R., 2016. "On time-varying predictability of emerging stock market returns," Emerging Markets Review, Elsevier, vol. 27(C), pages 1-13.
    64. Kristoufek, Ladislav & Vosvrda, Miloslav, 2014. "Commodity futures and market efficiency," Energy Economics, Elsevier, vol. 42(C), pages 50-57.
    65. Ma, Pengcheng & Li, Daye & Li, Shuo, 2016. "Efficiency and cross-correlation in equity market during global financial crisis: Evidence from China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 163-176.
    66. Lee, Hojin & Chang, Woojin, 2015. "Multifractal regime detecting method for financial time series," Chaos, Solitons & Fractals, Elsevier, vol. 70(C), pages 117-129.
    67. Georgia Zournatzidou & Dimitrios Farazakis & Ioannis Mallidis & Christos Floros, 2024. "Stochastic Patterns of Bitcoin Volatility: Evidence across Measures," Mathematics, MDPI, vol. 12(11), pages 1-16, May.
    68. Maiorino, Enrico & Livi, Lorenzo & Giuliani, Alessandro & Sadeghian, Alireza & Rizzi, Antonello, 2015. "Multifractal characterization of protein contact networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 302-313.
    69. Song, Wanqing & Duan, Shouwu & Zio, Enrico & Kudreyko, Aleksey, 2022. "Multifractional and long-range dependent characteristics for remaining useful life prediction of cracking gas compressor," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    70. Sensoy, Ahmet & Hacihasanoglu, Erk, 2014. "Time-varying long range dependence in energy futures markets," Energy Economics, Elsevier, vol. 46(C), pages 318-327.
    71. Antoniades, I.P. & Brandi, Giuseppe & Magafas, L. & Di Matteo, T., 2021. "The use of scaling properties to detect relevant changes in financial time series: A new visual warning tool," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    72. Domino, Krzysztof & Błachowicz, Tomasz, 2015. "The use of copula functions for modeling the risk of investment in shares traded on world stock exchanges," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 142-151.
    73. Lotfalinezhad, Hamze & Maleki, Ali, 2020. "TTA, a new approach to estimate Hurst exponent with less estimation error and computational time," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 553(C).
    74. Ju Zhang & Qingwu Hu & Shaohua Wang & Mingyao Ai, 2017. "Variation Trend Analysis of Runoff and Sediment Time Series Based on the R / S Analysis of Simulated Loess Tilled Slopes in the Loess Plateau, China," Sustainability, MDPI, vol. 10(1), pages 1-17, December.
    75. José Antonio Climent Hernández & Luis Fernando Hoyos Reyes & Domingo Rodríguez Benavides, 2017. "The a-stable processes and their relationship with theexponent of self-similarity: Exchange rates of USADollar, Canadian Dollar, Euro and Yen," Contaduría y Administración, Accounting and Management, vol. 62(5), pages 11-12, Diciembre.
    76. José Pedro Ramos-Requena & Juan Evangelista Trinidad-Segovia & Miguel Ángel Sánchez-Granero, 2020. "An Alternative Approach to Measure Co-Movement between Two Time Series," Mathematics, MDPI, vol. 8(2), pages 1-24, February.
    77. Kristoufek, Ladislav, 2019. "Are the crude oil markets really becoming more efficient over time? Some new evidence," Energy Economics, Elsevier, vol. 82(C), pages 253-263.
    78. Todea, Alexandru & Pleşoianu, Anita, 2013. "The influence of foreign portfolio investment on informational efficiency: Empirical evidence from Central and Eastern European stock markets," Economic Modelling, Elsevier, vol. 33(C), pages 34-41.
    79. Vacha, Lukas & Barunik, Jozef & Vosvrda, Miloslav, 2012. "How do skilled traders change the structure of the market," International Review of Financial Analysis, Elsevier, vol. 23(C), pages 66-71.
    80. Silvio M. Duarte Queiros & Evaldo M. F. Curado & Fernando D. Nobre, 2011. "Minding impacting events in a model of stochastic variance," Papers 1102.4819, arXiv.org, revised Feb 2011.
    81. Mulligan, Robert F., 2017. "The multifractal character of capacity utilization over the business cycle: An application of Hurst signature analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 63(C), pages 147-152.
    82. M. Fern'andez-Mart'inez & M. A S'anchez-Granero & Mar'ia Jos'e Mu~noz Torrecillas & Bill McKelvey, 2016. "A comparison among some Hurst exponent approaches to predict nascent bubbles in $500$ company stocks," Papers 1601.04188, arXiv.org.
    83. Avci-Surucu, Ezgi & Aydogan, A. Kursat & Akgul, Doganbey, 2016. "Bidding structure, market efficiency and persistence in a multi-time tariff setting," Energy Economics, Elsevier, vol. 54(C), pages 77-87.
    84. Benjamin Rainer Auer, 2018. "Are standard asset pricing factors long-range dependent?," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 42(1), pages 66-88, January.
    85. Li, Daye & Kou, Zhun & Sun, Qiankun, 2015. "The scale-dependent market trend: Empirical evidences using the lagged DFA method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 433(C), pages 26-35.
    86. Song, Wanqing & Cattani, Carlo & Chi, Chi-Hung, 2020. "Multifractional Brownian motion and quantum-behaved particle swarm optimization for short term power load forecasting: An integrated approach," Energy, Elsevier, vol. 194(C).
    87. Ladislav Kristoufek, 2013. "Testing power-law cross-correlations: Rescaled covariance test," Papers 1307.4727, arXiv.org, revised Aug 2013.
    88. Gu, Gao-Feng & Xiong, Xiong & Zhang, Yong-Jie & Chen, Wei & Zhang, Wei & Zhou, Wei-Xing, 2016. "Stylized facts of price gaps in limit order books," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 48-58.
    89. Yanping Hu & Xu Yang & Xin Gao & Jingxiao Zhang & Lanxin Kang, 2024. "Analysis of Spatio-Temporal Evolution and Driving Factors of Eco-Environmental Quality during Highway Construction Based on RSEI," Land, MDPI, vol. 13(4), pages 1-20, April.
    90. Wang, Jian & Yan, Yan & Chen, Wenbing & Shao, Wei & Wang, Jian & Tang, Weiwei, 2021. "Equity-linked securities option pricing by fractional Brownian motion," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).
    91. Stan, Cristina & Marmureanu, Luminita & Marin, Cristina & Cristescu, Constantin P., 2020. "Investigation of multifractal cross-correlation surfaces of Hurst exponents for some atmospheric pollutants," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    92. Tsionas, Mike G., 2021. "Bayesian analysis of static and dynamic Hurst parameters under stochastic volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 567(C).
    93. Sukpitak, Jessada & Hengpunya, Varagorn, 2016. "Efficiency of Thai stock markets: Detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 458(C), pages 204-209.
    94. Wu, Liang & Chen, Lei & Ding, Yiming & Zhao, Tongzhou, 2018. "Testing for the source of multifractality in water level records," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 824-839.
    95. Pavel Srbek, 2018. "Odhad Hurstova exponentu v časových řadách denních výnosů akciových indexů [Estimation of the Hurst Exponent in Time Series of Daily Returns of Stock Indices]," Politická ekonomie, Prague University of Economics and Business, vol. 2018(4), pages 508-524.
    96. Karen Balladares & José Pedro Ramos-Requena & Juan Evangelista Trinidad-Segovia & Miguel Angel Sánchez-Granero, 2021. "Statistical Arbitrage in Emerging Markets: A Global Test of Efficiency," Mathematics, MDPI, vol. 9(2), pages 1-20, January.
    97. Gao-Feng Gu & Xiong Xiong & Yong-Jie Zhang & Wei Chen & Wei Zhang & Wei-Xing Zhou, 2014. "Stylized facts of price gaps in limit order books: Evidence from Chinese stocks," Papers 1405.1247, arXiv.org.
    98. Ladislav Kristoufek, 2012. "Fractal Markets Hypothesis and the Global Financial Crisis: Scaling, Investment Horizons and Liquidity," Papers 1203.4979, arXiv.org.
    99. Kristoufek, Ladislav, 2018. "On Bitcoin markets (in)efficiency and its evolution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 257-262.
    100. A. Gómez-Águila & J. E. Trinidad-Segovia & M. A. Sánchez-Granero, 2022. "Improvement in Hurst exponent estimation and its application to financial markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-21, December.
    101. Mukli, Peter & Nagy, Zoltan & Eke, Andras, 2015. "Multifractal formalism by enforcing the universal behavior of scaling functions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 417(C), pages 150-167.
    102. Ding, Liang & Luo, Yi & Lin, Yan & Huang, Yirong, 2021. "Revisiting the relations between Hurst exponent and fractional differencing parameter for long memory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    103. Dima, Bogdan & Dima, Ştefana Maria, 2017. "Mutual information and persistence in the stochastic volatility of market returns: An emergent market example," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 36-59.
    104. Auer, Benjamin R. & Hoffmann, Andreas, 2016. "Do carry trade returns show signs of long memory?," The Quarterly Review of Economics and Finance, Elsevier, vol. 61(C), pages 201-208.
    105. Mulligan, Robert F., 2014. "Multifractality of sectoral price indices: Hurst signature analysis of Cantillon effects in disequilibrium factor markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 403(C), pages 252-264.
    106. A. Sensoy & Benjamin M. Tabak, 2013. "How much random does European Union walk? A time-varying long memory analysis," Working Papers Series 342, Central Bank of Brazil, Research Department.

  47. Ladislav Kristoufek & Karel Janda & David Zilberman, 2012. "Regime-Dependent Topological Properties of Biofuels Networks," CAMA Working Papers 2012-49, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.

    Cited by:

    1. Lukas Vacha & Karel Janda & Ladislav Kristoufek & David Zilberman, 2012. "Time-Frequency Dynamics of Biofuels-Fuels-Food System," Papers 1209.0900, arXiv.org.
    2. Gautier Marti & Frank Nielsen & Miko{l}aj Bi'nkowski & Philippe Donnat, 2017. "A review of two decades of correlations, hierarchies, networks and clustering in financial markets," Papers 1703.00485, arXiv.org, revised Nov 2020.
    3. Tiwari, Aviral Kumar & Nasreen, Samia & Shahbaz, Muhammad & Hammoudeh, Shawkat, 2020. "Time-frequency causality and connectedness between international prices of energy, food, industry, agriculture and metals," Energy Economics, Elsevier, vol. 85(C).
    4. Pavla BLAHOVA & Karel JANDA & Ladislav KRISTOUFEK, 2014. "The perspectives for genetically modified cellulosic biofuels in the Central European conditions," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 60(6), pages 247-259.
    5. Karel Janda & Ladislav Krištoufek, 2019. "The Relationship Between Fuel and Food Prices: Methods and Outcomes," Annual Review of Resource Economics, Annual Reviews, vol. 11(1), pages 195-216, October.
    6. Manuel Monge & Luis A. Gil-Alana, 2020. "The Lithium Industry and Analysis of the Beta Term Structure of Oil Companies," Risks, MDPI, vol. 8(4), pages 1-17, December.
    7. Paulus, Michal & Kristoufek, Ladislav, 2015. "Worldwide clustering of the corruption perception," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 351-358.
    8. Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2013. "Food versus Fuel: Causality and Predictability in Distribution," IEFE Working Papers 56, IEFE, Center for Research on Energy and Environmental Economics and Policy, Universita' Bocconi, Milano, Italy.
    9. de Araujo, Fernando Henrique Antunes & Bejan, Lucian & Stosic, Borko & Stosic, Tatijana, 2020. "An analysis of Brazilian agricultural commodities using permutation – information theory quantifiers: The influence of food crisis," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    10. Dániel Fróna & János Szenderák & Mónika Harangi-Rákos, 2019. "The Challenge of Feeding the World," Sustainability, MDPI, vol. 11(20), pages 1-18, October.
    11. Lahmiri, Salim, 2016. "Clustering of Casablanca stock market based on hurst exponent estimates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 310-318.
    12. Caporin, Massimiliano & Naeem, Muhammad Abubakr & Arif, Muhammad & Hasan, Mudassar & Vo, Xuan Vinh & Hussain Shahzad, Syed Jawad, 2021. "Asymmetric and time-frequency spillovers among commodities using high-frequency data," Resources Policy, Elsevier, vol. 70(C).
    13. Karel Janda & Ladislav Kristoufek, 2019. "The relationship between fuel and food prices: Methods, outcomes, and lessons for commodity price risk management," CAMA Working Papers 2019-20, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    14. Pereira, Hernane Borges de Barros & Rosário, Raphael Silva do & Pereira, Eder Johnson de Area Leão & Moreira, Davidson Martins & Ferreira, Paulo & Miranda, José Garcia Vivas, 2022. "Network dynamic and stability on European Union," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 587(C).
    15. Ladislav Kristoufek & Karel Janda & David Zilberman, 2015. "Co-movements of Ethanol Related Prices: Evidence from Brazil and the USA," CAMA Working Papers 2015-11, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    16. Giray GOZGOR & Cahit MEMIS, 2015. "Price volatility spillovers among agricultural commodity and crude oil markets: Evidence from the range-based estimator," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 61(5), pages 214-221.
    17. FRÓNA Dániel, 2020. "Factors Affecting Food Security," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(1), pages 39-49, July.
    18. Lima, Cristiane Rocha Albuquerque & de Melo, Gabriel Rivas & Stosic, Borko & Stosic, Tatijana, 2019. "Cross-correlations between Brazilian biofuel and food market: Ethanol versus sugar," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 687-693.
    19. Ondřej Filip & Karel Janda & Ladislav Krištoufek, 2018. "Ceny biopaliv a souvisejících komodit: analýza s použitím metod minimální kostry grafu a hierarchických stromů [Prices of Biofuels and Related Commodities: an Analysis Using Methods of Minimum Span," Politická ekonomie, Prague University of Economics and Business, vol. 2018(2), pages 218-239.

  48. Jozef Barunik & Lukas Vacha & Ladislav Krištoufek, 2011. "Comovement of Central European stock markets using wavelet coherence: Evidence from high-frequency data," Working Papers IES 2011/22, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Jun 2011.

    Cited by:

    1. Mensi, Walid & Hkiri, Besma & Al-Yahyaee, Khamis H. & Kang, Sang Hoon, 2018. "Analyzing time–frequency co-movements across gold and oil prices with BRICS stock markets: A VaR based on wavelet approach," International Review of Economics & Finance, Elsevier, vol. 54(C), pages 74-102.
    2. McNevin, Bruce D. & Nix, Joan, 2018. "The beta heuristic from a time/frequency perspective: A wavelet analysis of the market risk of sectors," Economic Modelling, Elsevier, vol. 68(C), pages 570-585.
    3. Ijaz Younis & Cheng Longsheng & Muhammad Farhan Basheer & Ahmed Shafique Joyo, 2020. "Stock market comovements among Asian emerging economies: A wavelet-based approach," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-23, October.
    4. Semih Emre Cekin & Besma Hkiri & Aviral Kumar Tiwari & Rangan Gupta, 2019. "The Relationship between Monetary Policy and Uncertainty in Advanced Economies: Evidence from Time- and Frequency-Domains," Working Papers 201904, University of Pretoria, Department of Economics.
    5. Aloui, Chaker & Hkiri, Besma & Nguyen, Duc Khuong, 2016. "Real growth co-movements and business cycle synchronization in the GCC countries: Evidence from time-frequency analysis," Economic Modelling, Elsevier, vol. 52(PB), pages 322-331.
    6. Masih, Mansur & Majid, Hamdan Abdul, 2013. "Comovement of Selected International Stock Market Indices:A Continuous Wavelet Transformation and Cross Wavelet Transformation Analysis," MPRA Paper 58313, University Library of Munich, Germany.
    7. Taheri Bazkhaneh , Saleh & Ehsani , Mohammad Ali & Gilak Hakimabadi , Mohammad Taqi & Farzinvash , Asodollah, 2018. "Analysis of the Relationship between the Business Cycle and Inflation Gap in Time-Frequency Domain," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 13(3), pages 401-422, July.
    8. Jusoh, Hashim & Bacha, Obiyathulla & Masih, Abul Mansur M., 2014. "Multi-scale Lead-Lag Relationship between the Stock and Futures Markets: Malaysia as a Case Study," MPRA Paper 56954, University Library of Munich, Germany.
    9. Avishek Bhandari, 2020. "A wavelet analysis of inter-dependence, contagion and long memory among global equity markets," Papers 2003.14110, arXiv.org.
    10. Besma Hkiri & Juncal Cunado & Mehmet Balcilar & Rangan Gupta, 2019. "Time-Varying Relationship between Conventional and Unconventional Monetary Policies and Risk Aversion: International Evidence from Time- and Frequency-Domains," Working Papers 201965, University of Pretoria, Department of Economics.
    11. Avishek BHANDARI, 2017. "Wavelets based multiscale analysis of select global equity returns," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 0(4(613), W), pages 75-88, Winter.
    12. M. Kannadhasan & Debojyoti Das, 2019. "Has Co-Movement Dynamics in Brazil, Russia, India, China and South Africa (BRICS) Markets Changed After Global Financial Crisis? New Evidence from Wavelet Analysis," Asian Academy of Management Journal of Accounting and Finance (AAMJAF), Penerbit Universiti Sains Malaysia, vol. 15(1), pages 1-26.
    13. Ben-Salha, Ousama & Hkiri, Besma & Aloui, Chaker, 2018. "Sectoral energy consumption by source and output in the U.S.: New evidence from wavelet-based approach," Energy Economics, Elsevier, vol. 72(C), pages 75-96.

  49. Karel Janda & Ladislav Kristoufek & David Zilberman, 2011. "Modeling the Environmental and Socio-Economic Impacts of Biofuels," Working Papers IES 2011/33, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Oct 2011.

    Cited by:

    1. Piroli, Giuseppe & Rajcaniova, Miroslava & Ciaian, Pavel & Kancs, d׳Artis, 2015. "From a rise in B to a fall in C? SVAR analysis of environmental impact of biofuels," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 921-930.
    2. Ferede, Tadele & Gebreegziabher, Zenebe & Mekonnen, Alemu & Guta, Fantu & Levin, Jörgen & Köhlin, Gunnar, 2013. "Biofuels, Economic Growth, and the External Sector in Ethiopia: A Computable General Equilibrium Analysis," RFF Working Paper Series dp-13-08-efd, Resources for the Future.

  50. Ladislav Kristoufek, 2010. "Long-range dependence in returns and volatility of Central European Stock Indices," Working Papers IES 2010/03, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Feb 2010.

    Cited by:

    1. Kristoufek, Ladislav, 2013. "Mixed-correlated ARFIMA processes for power-law cross-correlations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(24), pages 6484-6493.
    2. Ladislav Kristoufek, 2013. "Testing power-law cross-correlations: Rescaled covariance test," Papers 1307.4727, arXiv.org, revised Aug 2013.
    3. Paulo Ferreira & Marcus Fernandes da Silva & Idaraí Santos de Santana, 2019. "Detrended Correlation Coefficients Between Exchange Rate (in Dollars) and Stock Markets in the World’s Largest Economies," Economies, MDPI, vol. 7(1), pages 1-11, February.

  51. Kristoufek, Ladislav, 2009. "Distinguishing between short and long range dependence: Finite sample properties of rescaled range and modified rescaled range," MPRA Paper 16424, University Library of Munich, Germany.

    Cited by:

    1. Gomes, Luís M. P. & Soares, Vasco J. S. & Gama, Sílvio M. A. & Matos, José A. O., 2018. "Long-term memory in Euronext stock indexes returns: an econophysics approach," Business and Economic Horizons (BEH), Prague Development Center, vol. 14(4), pages 862-881, August.

  52. Janda, Karel & Kristoufek, Ladislav & Zilberman, David, "undated". "Biofuels: review of policies and impacts," CUDARE Working Papers 120415, University of California, Berkeley, Department of Agricultural and Resource Economics.

    Cited by:

    1. Piroli, Giuseppe & Rajcaniova, Miroslava & Ciaian, Pavel & Kancs, d׳Artis, 2015. "From a rise in B to a fall in C? SVAR analysis of environmental impact of biofuels," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 921-930.
    2. Hasanov, Akram Shavkatovich & Do, Hung Xuan & Shaiban, Mohammed Sharaf, 2016. "Fossil fuel price uncertainty and feedstock edible oil prices: Evidence from MGARCH-M and VIRF analysis," Energy Economics, Elsevier, vol. 57(C), pages 16-27.

Articles

  1. Kristoufek, Ladislav & Bouri, Elie, 2023. "Exploring sources of statistical arbitrage opportunities among Bitcoin exchanges," Finance Research Letters, Elsevier, vol. 51(C).

    Cited by:

    1. Okorie, David Iheke & Bouri, Elie & Mazur, Mieszko, 2024. "NFTs versus conventional cryptocurrencies: A comparative analysis of market efficiency around COVID-19 and the Russia-Ukraine conflict," The Quarterly Review of Economics and Finance, Elsevier, vol. 95(C), pages 126-151.

  2. Nedved, Martin & Kristoufek, Ladislav, 2023. "Safe havens for Bitcoin," Finance Research Letters, Elsevier, vol. 51(C).

    Cited by:

    1. Ali, Fahad & Sensoy, Ahmet & Goodell, John W., 2023. "Identifying diversifiers, hedges, and safe havens among Asia Pacific equity markets during COVID-19: New results for ongoing portfolio allocation," International Review of Economics & Finance, Elsevier, vol. 85(C), pages 744-792.

  3. Inacio, C.M.C. & Kristoufek, L. & David, S.A., 2023. "Assessing the impact of the Russia–Ukraine war on energy prices: A dynamic cross-correlation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 626(C).

    Cited by:

    1. Ben Salem, Leila & Zayati, Montassar & Nouira, Ridha & Rault, Christophe, 2024. "Volatility spillover between oil prices and main exchange rates: Evidence from a DCC-GARCH-connectedness approach," Resources Policy, Elsevier, vol. 91(C).
    2. Zhou, Xiaoran & Enilov, Martin & Parhi, Mamata, 2024. "Does oil spin the commodity wheel? Quantile connectedness with a common factor error structure across energy and agricultural markets," Energy Economics, Elsevier, vol. 132(C).

  4. Janda, Karel & Kristoufek, Ladislav & Zhang, Binyi, 2022. "Return and volatility spillovers between Chinese and U.S. clean energy related stocks," Energy Economics, Elsevier, vol. 108(C).
    See citations under working paper version above.
  5. Tilfani, Oussama & Kristoufek, Ladislav & Ferreira, Paulo & El Boukfaoui, My Youssef, 2022. "Heterogeneity in economic relationships: Scale dependence through the multivariate fractal regression," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 588(C).

    Cited by:

    1. Nick James & Kevin Chin, 2021. "On the systemic nature of global inflation, its association with equity markets and financial portfolio implications," Papers 2111.11022, arXiv.org, revised Jan 2022.
    2. Kakinaka, Shinji & Umeno, Ken, 2022. "Asymmetric volatility dynamics in cryptocurrency markets on multi-time scales," Research in International Business and Finance, Elsevier, vol. 62(C).
    3. Un, Kuok Sin & Ausloos, Marcel, 2022. "Equity premium prediction: Taking into account the role of long, even asymmetric, swings in stock market behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P1).

  6. Kumar, Ashish & Iqbal, Najaf & Mitra, Subrata Kumar & Kristoufek, Ladislav & Bouri, Elie, 2022. "Connectedness among major cryptocurrencies in standard times and during the COVID-19 outbreak," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 77(C).

    Cited by:

    1. Kingstone Nyakurukwa & Yudhvir Seetharam, 2023. "Higher moment connectedness of cryptocurrencies: a time-frequency approach," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 47(3), pages 793-814, September.
    2. Pham, Linh & Huynh, Toan Luu Duc & Hanif, Waqas, 2023. "Time-varying asymmetric spillovers among cryptocurrency, green and fossil-fuel investments," Global Finance Journal, Elsevier, vol. 58(C).
    3. Spyros Papathanasiou & Dimitris Kenourgios & Drosos Koutsokostas & Georgios Pergeris, 2023. "Can treasury inflation-protected securities safeguard investors from outward risk spillovers? A portfolio hedging strategy through the prism of COVID-19," Journal of Asset Management, Palgrave Macmillan, vol. 24(3), pages 198-211, May.
    4. Thomas F. P. Wiesen & Lakshya Bharadwaj, 2023. "Cryptocurrency Connectedness: Does Controlling for the Cross-Correlations Matter?," Applied Economics Letters, Taylor & Francis Journals, vol. 30(20), pages 2873-2880, November.
    5. Jinxin Cui & Aktham Maghyereh, 2022. "Time–frequency co-movement and risk connectedness among cryptocurrencies: new evidence from the higher-order moments before and during the COVID-19 pandemic," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-56, December.
    6. Assaf, Ata & Mokni, Khaled & Youssef, Manel, 2023. "COVID-19 and information flow between cryptocurrencies, and conventional financial assets," The Quarterly Review of Economics and Finance, Elsevier, vol. 89(C), pages 73-81.
    7. Goswami, Mangal & Pontines, Victor & Mohammed, Yassier, 2023. "Portfolio capital flows and the US dollar exchange rate: Viewed from the lens of time and frequency dynamics of connectedness," International Review of Financial Analysis, Elsevier, vol. 89(C).
    8. Susovon Jana & Tarak N. Sahu, 2023. "Is the cryptocurrency market a hedge against stock market risk? A Wavelet and GARCH approach," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 52(3), November.
    9. Bejaoui, Azza & Frikha, Wajdi & Jeribi, Ahmed & Bariviera, Aurelio F., 2023. "Connectedness between emerging stock markets, gold, cryptocurrencies, DeFi and NFT: Some new evidence from wavelet analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 619(C).
    10. Patel, Ritesh & Kumar, Sanjeev & Bouri, Elie & Iqbal, Najaf, 2023. "Spillovers between green and dirty cryptocurrencies and socially responsible investments around the war in Ukraine," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 143-162.
    11. Elie Bouri & Matteo Foglia & Sayar Karmakar & Rangan Gupta, 2024. "Return-Volatility Nexus in the Digital Asset Class: A Dynamic Multilayer Connectedness Analysis," Working Papers 202432, University of Pretoria, Department of Economics.
    12. Gambarelli, Luca & Marchi, Gianluca & Muzzioli, Silvia, 2023. "Hedging effectiveness of cryptocurrencies in the European stock market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 84(C).
    13. Okorie, David Iheke & Bouri, Elie & Mazur, Mieszko, 2024. "NFTs versus conventional cryptocurrencies: A comparative analysis of market efficiency around COVID-19 and the Russia-Ukraine conflict," The Quarterly Review of Economics and Finance, Elsevier, vol. 95(C), pages 126-151.
    14. Ling, Aifan & Huang, Xinrui & Ling, Boya (Vivye), 2022. "Fund immunity to the COVID-19 pandemic: Evidence from Chinese equity funds," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    15. Nguyen, An Pham Ngoc & Mai, Tai Tan & Bezbradica, Marija & Crane, Martin, 2023. "Volatility and returns connectedness in cryptocurrency markets: Insights from graph-based methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 632(P1).
    16. Ghosh, Bikramaditya & Bouri, Elie & Wee, Jung Bum & Zulfiqar, Noshaba, 2023. "Return and volatility properties: Stylized facts from the universe of cryptocurrencies and NFTs," Research in International Business and Finance, Elsevier, vol. 65(C).
    17. Fernandes, Leonardo H.S. & Bouri, Elie & Silva, José W.L. & Bejan, Lucian & de Araujo, Fernando H.A., 2022. "The resilience of cryptocurrency market efficiency to COVID-19 shock," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    18. Chen, Bin-xia & Sun, Yan-lin, 2024. "Risk characteristics and connectedness in cryptocurrency markets: New evidence from a non-linear framework," The North American Journal of Economics and Finance, Elsevier, vol. 69(PA).
    19. Ali, Shoaib & Moussa, Faten & Youssef, Manel, 2023. "Connectedness between cryptocurrencies using high-frequency data: A novel insight from the Silicon Valley Banks collapse," Finance Research Letters, Elsevier, vol. 58(PB).
    20. Waqas Hanif & Hee-Un Ko & Linh Pham & Sang Hoon Kang, 2023. "Dynamic connectedness and network in the high moments of cryptocurrency, stock, and commodity markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-40, December.
    21. Inzamam Ul Haq, 2023. "Time‐frequency comovement among green financial assets and cryptocurrency uncertainties," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 52(1), February.
    22. Mei-jun, Ling & Guang-xi, Cao, 2024. "Dynamics of asymmetric multifractal cross-correlations between cryptocurrencies and global stock markets: Role of gold and portfolio implications," Chaos, Solitons & Fractals, Elsevier, vol. 182(C).
    23. Mzoughi, Hela & Amar, Amine Ben & Guesmi, Khaled & Benkraiem, Ramzi, 2024. "Blockchain markets, green finance investments, and environmental impacts," Research in International Business and Finance, Elsevier, vol. 69(C).
    24. Abubakr Naeem, Muhammad & Iqbal, Najaf & Lucey, Brian M. & Karim, Sitara, 2022. "Good versus bad information transmission in the cryptocurrency market: Evidence from high-frequency data," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    25. Aharon, David Y. & Butt, Hassan Anjum & Jaffri, Ali & Nichols, Brian, 2023. "Asymmetric volatility in the cryptocurrency market: New evidence from models with structural breaks," International Review of Financial Analysis, Elsevier, vol. 87(C).
    26. Chowdhury, Mohammad Ashraful Ferdous & Abdullah, Mohammad & Masih, Mansur, 2022. "COVID-19 government interventions and cryptocurrency market: Is there any optimum portfolio diversification?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    27. Marcin Wk{a}torek & Jaros{l}aw Kwapie'n & Stanis{l}aw Dro.zd.z, 2023. "Cryptocurrencies Are Becoming Part of the World Global Financial Market," Papers 2303.00495, arXiv.org.
    28. Umar, Zaghum & Polat, Onur & Choi, Sun-Yong & Teplova, Tamara, 2022. "Dynamic connectedness between non-fungible tokens, decentralized finance, and conventional financial assets in a time-frequency framework," Pacific-Basin Finance Journal, Elsevier, vol. 76(C).
    29. Dora Almeida & Andreia Dionísio & Paulo Ferreira & Isabel Vieira, 2023. "Impact of the COVID-19 Pandemic on Cryptocurrency Markets: A DCCA Analysis," FinTech, MDPI, vol. 2(2), pages 1-17, May.
    30. Kim, Hyeonoh & Ha, Chang Yong & Ahn, Kwangwon, 2022. "Preference heterogeneity in Bitcoin and its forks' network," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    31. Elie Bouri & Afees A. Salisu & Rangan Gupta, 2023. "The predictive power of Bitcoin prices for the realized volatility of US stock sector returns," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-22, December.
    32. Al-Shboul, Mohammad & Assaf, Ata & Mokni, Khaled, 2023. "Does economic policy uncertainty drive the dynamic spillover among traditional currencies and cryptocurrencies? The role of the COVID-19 pandemic," Research in International Business and Finance, Elsevier, vol. 64(C).
    33. Shaen Corbet & Les Oxley, 2023. "Investigating the Academic Response to Cryptocurrencies: Insights from Research Diversification as Separated by Journal Ranking," Review of Corporate Finance, now publishers, vol. 3(4), pages 487-528, September.
    34. Chen, Ruoyu & Iqbal, Najaf & Irfan, Muhammad & Shahzad, Farrukh & Fareed, Zeeshan, 2022. "Does financial stress wreak havoc on banking, insurance, oil, and gold markets? New empirics from the extended joint connectedness of TVP-VAR model," Resources Policy, Elsevier, vol. 77(C).
    35. Li, Xingyi & Gan, Kai & Zhou, Qi, 2023. "Dynamic volatility connectedness among cryptocurrencies and China's financial assets in standard times and during the COVID-19 pandemic," Finance Research Letters, Elsevier, vol. 51(C).
    36. Elie Bouri & Afees A. Salisu & Rangan Gupta, 2022. "Bitcoin Prices and the Realized Volatility of US Sectoral Stock Returns," Working Papers 202224, University of Pretoria, Department of Economics.
    37. Xu, Fang & Bouri, Elie & Cepni, Oguzhan, 2022. "Blockchain and crypto-exposed US companies and major cryptocurrencies: The role of jumps and co-jumps," Finance Research Letters, Elsevier, vol. 50(C).
    38. Wu, Xinyu & Yin, Xuebao & Umar, Zaghum & Iqbal, Najaf, 2023. "Volatility forecasting in the Bitcoin market: A new proposed measure based on the VS-ACARR approach," The North American Journal of Economics and Finance, Elsevier, vol. 67(C).
    39. Yousaf, Imran & Jareño, Francisco & Martínez-Serna, María-Isabel, 2023. "Extreme spillovers between insurance tokens and insurance stocks: Evidence from the quantile connectedness approach," Journal of Behavioral and Experimental Finance, Elsevier, vol. 39(C).

  7. Kubal, Jan & Kristoufek, Ladislav, 2022. "Exploring the relationship between Bitcoin price and network’s hashrate within endogenous system," International Review of Financial Analysis, Elsevier, vol. 84(C).

    Cited by:

    1. Podhorsky, Andrea, 2023. "Taxing bitcoin: Incentivizing the difficulty adjustment mechanism to reduce electricity usage," International Review of Financial Analysis, Elsevier, vol. 86(C).
    2. Ma, Rui & Xie, Xiao qin & Liu, Bin & Zhou, Fengjiao & Samsurijan, Mohamad Shaharudin bin, 2023. "Transmission to green economic development and the dependence on natural resources in China," Resources Policy, Elsevier, vol. 86(PB).
    3. Jiri Kukacka & Ladislav Kristoufek, 2023. "Fundamental and speculative components of the cryptocurrency pricing dynamics," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-23, December.
    4. Kim, Daehan & Ryu, Doojin & Webb, Robert I., 2023. "Determination of equilibrium transaction fees in the Bitcoin network: A rank-order contest," International Review of Financial Analysis, Elsevier, vol. 86(C).

  8. Syed Jawad Hussain Shahzad & Elie Bouri & Ladislav Kristoufek & Tareq Saeed, 2021. "Impact of the COVID-19 outbreak on the US equity sectors: Evidence from quantile return spillovers," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-23, December.

    Cited by:

    1. Tedeschi, Marco & Foglia, Matteo & Bouri, Elie & Dai, Peng-Fei, 2024. "How does climate policy uncertainty affect financial markets? Evidence from Europe," Economics Letters, Elsevier, vol. 234(C).
    2. Choi, Sun-Yong, 2022. "Dynamic volatility spillovers between industries in the US stock market: Evidence from the COVID-19 pandemic and Black Monday," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    3. Aloui, Riadh & Ben Jabeur, Sami & Mefteh-Wali, Salma, 2022. "Tail-risk spillovers from China to G7 stock market returns during the COVID-19 outbreak: A market and sectoral analysis," Research in International Business and Finance, Elsevier, vol. 62(C).
    4. Wang, Dong & Li, Ping & Huang, Lixin, 2022. "Time-frequency volatility spillovers between major international financial markets during the COVID-19 pandemic," Finance Research Letters, Elsevier, vol. 46(PA).
    5. Naeem, Muhammad Abubakr & Karim, Sitara & Tiwari, Aviral Kumar, 2022. "Quantifying systemic risk in US industries using neural network quantile regression," Research in International Business and Finance, Elsevier, vol. 61(C).
    6. Yen-Chang Chen & Ying-Sing Liu, 2023. "Market Efficiency and Stock Investment Loss Aversion Guide During COVID-19 Pandemic Events: The Case for Applying Data Mining," SAGE Open, , vol. 13(4), pages 21582440231, December.
    7. Wei, Zhengyuan & He, Qingxia & Zhou, Qili & Wang, Ge, 2023. "Measuring dependence structure and extreme risk spillovers in stock markets: An APARCH-EVT-DMC approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 632(P1).
    8. Ali, Shoaib & Al-Nassar, Nassar S. & Naveed, Muhammad, 2024. "Bridging the gap: Uncovering static and dynamic relationships between digital assets and BRICS equity markets," Global Finance Journal, Elsevier, vol. 60(C).
    9. Rubbaniy, Ghulame & Khalid, Ali Awais & Syriopoulos, Konstantinos & Samitas, Aristeidis, 2022. "Safe-haven properties of soft commodities during times of Covid-19," Journal of Commodity Markets, Elsevier, vol. 27(C).
    10. Abuzayed, Bana & Bouri, Elie & Al-Fayoumi, Nedal & Jalkh, Naji, 2021. "Systemic risk spillover across global and country stock markets during the COVID-19 pandemic," Economic Analysis and Policy, Elsevier, vol. 71(C), pages 180-197.
    11. Guo, Qingran & Ahmed, Khalid & Ding, Cuicui & Khan, Bareerah, 2024. "How the pandemic-led volatility in the natural resource commodity indices affect U.S and China markets," Resources Policy, Elsevier, vol. 90(C).
    12. Wang, Kai-Hua & Kan, Jia-Min & Qiu, Lianhong & Xu, Shulin, 2023. "Climate policy uncertainty, oil price and agricultural commodity: From quantile and time perspective," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 256-272.
    13. Nekhili, Ramzi & Foglia, Matteo & Bouri, Elie, 2023. "European bank credit risk transmission during the credit Suisse collapse," Finance Research Letters, Elsevier, vol. 58(PB).
    14. Gu, Jianqiang & Yue, Xiao-Guang & Nosheen, Safia & Naveed -ul-Haq, & Shi, Lei, 2022. "Does more stringencies in government policies during pandemic impact stock returns? Fresh evidence from GREF countries, a new emerging green bloc," Resources Policy, Elsevier, vol. 76(C).
    15. Abakah, Emmanuel Joel Aikins & Abdullah, Mohammad & Yousaf, Imran & Kumar Tiwari, Aviral & Li, Yanshuang, 2024. "Economic sanctions sentiment and global stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 91(C).
    16. Guglielmo Maria Caporale & Luis Alberiko Gil-Alana & Emmanuel Joel Aikins Abakah, 2023. "US policy responses to the COVID-19 pandemic and sectoral stock indices: A fractional integration approach," Applied Economics, Taylor & Francis Journals, vol. 55(3), pages 283-292, January.
    17. Su, Chi-Wei & Yuan, Xi & Umar, Muhammad & Chang, Tsangyao, 2022. "Dynamic price linkage of energies in transformation: Evidence from quantile connectedness," Resources Policy, Elsevier, vol. 78(C).
    18. Hernandez, Jose Arreola & Shahzad, Syed Jawad Hussain & Sadorsky, Perry & Uddin, Gazi Salah & Bouri, Elie & Kang, Sang Hoon, 2022. "Regime specific spillovers across US sectors and the role of oil price volatility," Energy Economics, Elsevier, vol. 107(C).
    19. Virginie Terraza & Aslı Boru İpek & Mohammad Mahdi Rounaghi, 2024. "The nexus between the volatility of Bitcoin, gold, and American stock markets during the COVID-19 pandemic: evidence from VAR-DCC-EGARCH and ANN models," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-34, December.
    20. Naeem, Muhammad Abubakr & Karim, Sitara & Uddin, Gazi Salah & Junttila, Juha, 2022. "Small fish in big ponds: Connections of green finance assets to commodity and sectoral stock markets," International Review of Financial Analysis, Elsevier, vol. 83(C).
    21. Nguyen, An Pham Ngoc & Mai, Tai Tan & Bezbradica, Marija & Crane, Martin, 2023. "Volatility and returns connectedness in cryptocurrency markets: Insights from graph-based methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 632(P1).
    22. Long, Shaobo & Tian, Hao & Li, Zixuan, 2022. "Dynamic spillovers between uncertainties and green bond markets in the US, Europe, and China: Evidence from the quantile VAR framework," International Review of Financial Analysis, Elsevier, vol. 84(C).
    23. Muhammad Abubakr Naeem & Sitara Karim & Aviral Kumar Tiwari, 2023. "Risk Connectedness Between Green and Conventional Assets with Portfolio Implications," Computational Economics, Springer;Society for Computational Economics, vol. 62(2), pages 609-637, August.
    24. Shahzad, Syed Jawad Hussain & Naeem, Muhammad Abubakr & Peng, Zhe & Bouri, Elie, 2021. "Asymmetric volatility spillover among Chinese sectors during COVID-19," International Review of Financial Analysis, Elsevier, vol. 75(C).
    25. Urom, Christian, 2023. "Time–frequency dependence and connectedness between financial technology and green assets," International Economics, Elsevier, vol. 175(C), pages 139-157.
    26. Chen, Jinyu & Liang, Zhipeng & Ding, Qian & Liu, Zhenhua, 2022. "Extreme spillovers among fossil energy, clean energy, and metals markets: Evidence from a quantile-based analysis," Energy Economics, Elsevier, vol. 107(C).
    27. Su, Chi-Wei & Pang, Li-Dong & Qin, Meng & Lobonţ, Oana-Ramona & Umar, Muhammad, 2023. "The spillover effects among fossil fuel, renewables and carbon markets: Evidence under the dual dilemma of climate change and energy crises," Energy, Elsevier, vol. 274(C).
    28. Mahdi Ghaemi Asl & Oluwasegun B. Adekoya & Muhammad Mahdi Rashidi, 2023. "Quantiles dependence and dynamic connectedness between distributed ledger technology and sectoral stocks: enhancing the supply chain and investment decisions with digital platforms," Annals of Operations Research, Springer, vol. 327(1), pages 435-464, August.
    29. Yuan, Xi & Qin, Meng & Zhong, Yifan & Nicoleta-Claudia, Moldovan, 2023. "Financial roles in green investment based on the quantile connectedness," Energy Economics, Elsevier, vol. 117(C).
    30. Guangxi Cao & Fei Xie, 2024. "Extreme risk spillovers across energy and carbon markets: Evidence from the quantile extended joint connectedness approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(2), pages 2155-2175, April.
    31. Zhang, Xiaoming & Tian, Yiming & Lee, Chien-Chiang, 2024. "Enforcement actions and systemic risk," Emerging Markets Review, Elsevier, vol. 59(C).
    32. Yousaf, Imran & Arfaoui, Nadia & Gubareva, Mariya, 2024. "Spillovers and hedging effectiveness between oil and US equity sectors: Evidence from the COVID pre- and post-vaccination phases," Research in International Business and Finance, Elsevier, vol. 69(C).
    33. Chen, Yan & Wang, Gang-Jin & Zhu, You & Xie, Chi & Uddin, Gazi Salah, 2023. "Quantile connectedness and the determinants between FinTech and traditional financial institutions: Evidence from China," Global Finance Journal, Elsevier, vol. 58(C).
    34. Ahelegbey, Daniel Felix & Cerchiello, Paola & Scaramozzino, Roberta, 2022. "Network based evidence of the financial impact of Covid-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 81(C).
    35. Zhou, Shuai & Qian, Yudan & Farmanesh, Panteha, 2022. "The economic cost of environmental laws: Volatility transmission mechanism and remedies," Resources Policy, Elsevier, vol. 79(C).
    36. Pham, Son Duy & Nguyen, Thao Thac Thanh & Do, Hung Xuan, 2023. "Natural gas and the utility sector nexus in the U.S.: Quantile connectedness and portfolio implications," Energy Economics, Elsevier, vol. 120(C).
    37. Florin-Teodor Boldeanu & Adriana Veronica Litră & José Antonio Clemente-Almendros & Ileana Tache, 2022. "The link Between Stock Exchange Sectors and Indices: Implications During the COVID-19 Pandemic," SAGE Open, , vol. 12(4), pages 21582440221, December.
    38. Pham, Linh & Cepni, Oguzhan, 2022. "Extreme directional spillovers between investor attention and green bond markets," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 186-210.
    39. Zhang, Hongwei & Zhang, Yubo & Gao, Wang & Li, Yingli, 2023. "Extreme quantile spillovers and drivers among clean energy, electricity and energy metals markets," International Review of Financial Analysis, Elsevier, vol. 86(C).
    40. Cynthia Sari DEWI & Florentina KURNIASARI & Helena DEWI & Eko ENDARTO & Nurhuda NIZAR, 2021. "Return Spillover Between The U.S., Japanese, And Indonesian Stock Market During Covid-19," Business Excellence and Management, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 11(5), pages 196-207, October.
    41. Nammouri, Hela & Chlibi, Souhir & Labidi, Oussama, 2022. "Co-movements in sector price indexes during the COVID-19 crisis: Evidence from the US," Finance Research Letters, Elsevier, vol. 46(PA).
    42. Osman, Myriam Ben & Urom, Christian & Guesmi, Khaled & Benkraiem, Ramzi, 2024. "Economic sentiment and the cryptocurrency market in the post-COVID-19 era," International Review of Financial Analysis, Elsevier, vol. 91(C).

  9. Ji, Qiang & Bouri, Elie & Kristoufek, Ladislav & Lucey, Brian, 2021. "Realised volatility connectedness among Bitcoin exchange markets," Finance Research Letters, Elsevier, vol. 38(C).

    Cited by:

    1. Ma, Yu & Luan, Zhiqian, 2022. "Ethereum synchronicity, upside volatility and Bitcoin crash risk," Finance Research Letters, Elsevier, vol. 46(PA).
    2. Kumar, Anoop S & Padakandla, Steven Raj, 2022. "Testing the safe-haven properties of gold and bitcoin in the backdrop of COVID-19: A wavelet quantile correlation approach," Finance Research Letters, Elsevier, vol. 47(PB).
    3. Kristoufek, Ladislav & Bouri, Elie, 2023. "Exploring sources of statistical arbitrage opportunities among Bitcoin exchanges," Finance Research Letters, Elsevier, vol. 51(C).
    4. Adedeji Daniel Gbadebo, 2023. "Dynamic Asymmetric Causality of Bitcoin’s Price-Volume Relation," SAGE Open, , vol. 13(4), pages 21582440231, December.
    5. Al Guindy, Mohamed, 2021. "Cryptocurrency price volatility and investor attention," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 556-570.
    6. Kumar, Ashish & Iqbal, Najaf & Mitra, Subrata Kumar & Kristoufek, Ladislav & Bouri, Elie, 2022. "Connectedness among major cryptocurrencies in standard times and during the COVID-19 outbreak," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 77(C).
    7. Sofiane Aboura, 2022. "A note on the Bitcoin and Fed Funds rate," Empirical Economics, Springer, vol. 63(5), pages 2577-2603, November.
    8. Sun, Chuanwang & Min, Jialin & Sun, Jiacheng & Gong, Xu, 2023. "The role of China's crude oil futures in world oil futures market and China's financial market," Energy Economics, Elsevier, vol. 120(C).
    9. Alessio Brini & Jimmie Lenz, 2024. "A Comparison of Cryptocurrency Volatility-benchmarking New and Mature Asset Classes," Papers 2404.04962, arXiv.org.
    10. Chen, Baifan & Huang, Jionghao & Liu, Danhe & Xia, Xiaohua, 2024. "Time-frequency return connectedness between Chinese coal futures and international stock indices," International Review of Economics & Finance, Elsevier, vol. 89(PB), pages 316-333.
    11. Carol Alexander & Daniel Heck & Andreas Kaeck, 2021. "The Role of Binance in Bitcoin Volatility Transmission," Papers 2107.00298, arXiv.org, revised Aug 2021.
    12. Li, Zhenghui & Mo, Bin & Nie, He, 2023. "Time and frequency dynamic connectedness between cryptocurrencies and financial assets in China," International Review of Economics & Finance, Elsevier, vol. 86(C), pages 46-57.

  10. Kukacka, Jiri & Kristoufek, Ladislav, 2021. "Does parameterization affect the complexity of agent-based models?," Journal of Economic Behavior & Organization, Elsevier, vol. 192(C), pages 324-356.

    Cited by:

    1. Bornholdt, Stefan, 2022. "A q-spin Potts model of markets: Gain–loss asymmetry in stock indices as an emergent phenomenon," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 588(C).
    2. Jiri Kukacka & Ladislav Kristoufek, 2023. "Fundamental and speculative components of the cryptocurrency pricing dynamics," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-23, December.
    3. Stefan Bornholdt, 2021. "A q-spin Potts model of markets: Gain-loss asymmetry in stock indices as an emergent phenomenon," Papers 2112.06290, arXiv.org.
    4. Zila, Eric & Kukacka, Jiri, 2023. "Moment set selection for the SMM using simple machine learning," Journal of Economic Behavior & Organization, Elsevier, vol. 212(C), pages 366-391.

  11. Assaf, Ata & Kristoufek, Ladislav & Demir, Ender & Kumar Mitra, Subrata, 2021. "Market efficiency in the art markets using a combination of long memory, fractal dimension, and approximate entropy measures," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 71(C).

    Cited by:

    1. Guglielmo Maria Caporale & Luis A. Gil-Alana & Alex Plastun & Ahniia Havrylina, 2022. "Persistence in the Passion Investment Market," CESifo Working Paper Series 9586, CESifo.
    2. Aloosh, Arash & Choi, Hyung-Eun & Ouzan, Samuel, 2023. "The tail wagging the dog: How do meme stocks affect market efficiency?," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 68-78.
    3. Shimeng Shi & Jia Zhai & Yingying Wu, 2024. "Informational inefficiency on bitcoin futures," The European Journal of Finance, Taylor & Francis Journals, vol. 30(6), pages 642-667, April.
    4. Xie, Jun & Fang, Yuying & Gao, Bin & Tan, Chunzhi, 2023. "Availability heuristic and expected returns," Finance Research Letters, Elsevier, vol. 51(C).
    5. Emmanuel Joel Aikins Abakah & Aviral Kumar Tiwari & Emmanuel Kwesi Arthur & Luis Alberiko Gil-Alana, 2023. "The influence of economic policy uncertainty shocks on art market," Applied Economics, Taylor & Francis Journals, vol. 55(29), pages 3404-3421, June.
    6. Plastun, Alex & Bouri, Elie & Havrylina, Ahniia & Ji, Qiang, 2022. "Calendar anomalies in passion investments: Price patterns and profit opportunities," Research in International Business and Finance, Elsevier, vol. 61(C).

  12. Kristoufek, Ladislav, 2021. "Tethered, or Untethered? On the interplay between stablecoins and major cryptoassets," Finance Research Letters, Elsevier, vol. 43(C).

    Cited by:

    1. Yosra Ghabri & Luu Duc Toan Huynh & Muhammad Ali Nasir, 2024. "Volatility spillovers, hedging and safe‐havens under pandemics: All that glitters is not gold!," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(2), pages 1318-1344, April.
    2. Fernandez-Mejia, Julian, 2024. "Extremely stablecoins," Finance Research Letters, Elsevier, vol. 63(C).
    3. Duan, Kun & Urquhart, Andrew, 2023. "The instability of stablecoins," Finance Research Letters, Elsevier, vol. 52(C).
    4. Yousaf, Imran & Jareño, Francisco & Esparcia, Carlos, 2022. "Tail connectedness between lending/borrowing tokens and commercial bank stocks," International Review of Financial Analysis, Elsevier, vol. 84(C).
    5. Wu, Gabriel Shui Tang & Leung, Pak Ho, 2023. "Do asset-backed stablecoins spread crypto volatility to traditional financial assets? Evidence from Tether," Economics Letters, Elsevier, vol. 229(C).
    6. Chang, Lei & Baloch, Zulfiqar Ali & Saydaliev, Hayot Berk & Hyder, Mansoor & Dilanchiev, Azer, 2022. "Testing oil price volatility during Covid-19: Global economic impact," Resources Policy, Elsevier, vol. 78(C).
    7. Aiman Hairudin & Azhar Mohamad, 2024. "The isotropy of cryptocurrency volatility," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(3), pages 3779-3810, July.
    8. Gadzinski, Gregory & Castello, Alessio & Mazzorana, Florie, 2023. "Stablecoins: Does design affect stability?," Finance Research Letters, Elsevier, vol. 53(C).
    9. Łęt, Blanka & Sobański, Konrad & Świder, Wojciech & Włosik, Katarzyna, 2023. "What drives the popularity of stablecoins? Measuring the frequency dynamics of connectedness between volatile and stable cryptocurrencies," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    10. Sood, Kirti & Singh, Simarjeet & Behl, Abhishek & Sindhwani, Rahul & Kaur, Sandeepa & Pereira, Vijay, 2023. "Identification and prioritization of the risks in the mass adoption of artificial intelligence-driven stable coins: The quest for optimal resource utilization," Resources Policy, Elsevier, vol. 81(C).
    11. Díaz, Antonio & Esparcia, Carlos & Huélamo, Diego, 2023. "Stablecoins as a tool to mitigate the downside risk of cryptocurrency portfolios," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    12. Jalan, Akanksha & Matkovskyy, Roman & Yarovaya, Larisa, 2021. "“Shiny” crypto assets: A systemic look at gold-backed cryptocurrencies during the COVID-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 78(C).
    13. Jin, Feng & Li, Jingwei & Xue, Yi, 2023. "Preferring stablecoin over dollar: Evidence from a survey of Ethereum platform traders," Journal of International Money and Finance, Elsevier, vol. 131(C).
    14. Yousaf, Imran & Pham, Linh & Goodell, John W., 2024. "Dynamic spillovers between leading cryptocurrencies and derivatives tokens: Insights from a quantile VAR approach," International Review of Financial Analysis, Elsevier, vol. 94(C).
    15. Lennart Ante & Ingo Fiedler & Jan Marius Willruth & Fred Steinmetz, 2023. "A Systematic Literature Review of Empirical Research on Stablecoins," FinTech, MDPI, vol. 2(1), pages 1-14, January.
    16. Dora Almeida & Andreia Dionísio & Paulo Ferreira & Isabel Vieira, 2023. "Impact of the COVID-19 Pandemic on Cryptocurrency Markets: A DCCA Analysis," FinTech, MDPI, vol. 2(2), pages 1-17, May.
    17. Lyons, Richard K. & Viswanath-Natraj, Ganesh, 2023. "What keeps stablecoins stable?," Journal of International Money and Finance, Elsevier, vol. 131(C).
    18. Yousaf, Imran & Jareño, Francisco & Martínez-Serna, María-Isabel, 2023. "Extreme spillovers between insurance tokens and insurance stocks: Evidence from the quantile connectedness approach," Journal of Behavioral and Experimental Finance, Elsevier, vol. 39(C).

  13. Hussain Shahzad, Syed Jawad & Bouri, Elie & Roubaud, David & Kristoufek, Ladislav, 2020. "Safe haven, hedge and diversification for G7 stock markets: Gold versus bitcoin," Economic Modelling, Elsevier, vol. 87(C), pages 212-224.

    Cited by:

    1. Chiang, Thomas C., 2022. "The effects of economic uncertainty, geopolitical risk and pandemic upheaval on gold prices," Resources Policy, Elsevier, vol. 76(C).
    2. Ihsan Erdem Kayral & Ahmed Jeribi & Sahar Loukil, 2023. "Are Bitcoin and Gold a Safe Haven during COVID-19 and the 2022 Russia–Ukraine War?," JRFM, MDPI, vol. 16(4), pages 1-22, April.
    3. Kumah, Seyram Pearl & Odei-Mensah, Jones, 2021. "Are Cryptocurrencies and African stock markets integrated?," The Quarterly Review of Economics and Finance, Elsevier, vol. 81(C), pages 330-341.
    4. Bouri, Elie & Gkillas, Konstantinos & Gupta, Rangan & Pierdzioch, Christian, 2021. "Forecasting power of infectious diseases-related uncertainty for gold realized variance," Finance Research Letters, Elsevier, vol. 42(C).
    5. Mensi, Walid & Shafiullah, Muhammad & Vo, Xuan Vinh & Kang, Sang Hoon, 2021. "Volatility spillovers between strategic commodity futures and stock markets and portfolio implications: Evidence from developed and emerging economies," Resources Policy, Elsevier, vol. 71(C).
    6. Zhu, Xuehong & Niu, Zibo & Zhang, Hongwei & Huang, Jiaxin & Zuo, Xuguang, 2022. "Can gold and bitcoin hedge against the COVID-19 related news sentiment risk? New evidence from a NARDL approach," Resources Policy, Elsevier, vol. 79(C).
    7. Xu, Lei & Kinkyo, Takuji, 2023. "Hedging effectiveness of bitcoin and gold: Evidence from G7 stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 85(C).
    8. Xiafei Li & Dongxin Li & Xuhui Zhang & Guiwu Wei & Lan Bai & Yu Wei, 2021. "Forecasting regular and extreme gold price volatility: The roles of asymmetry, extreme event, and jump," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1501-1523, December.
    9. Dwita Mariana, Christy & Ekaputra, Irwan Adi & Husodo, Zaäfri Ananto, 2021. "Are Bitcoin and Ethereum safe-havens for stocks during the COVID-19 pandemic?," Finance Research Letters, Elsevier, vol. 38(C).
    10. Tarchella, Salma & Khalfaoui, Rabeh & Hammoudeh, Shawkat, 2024. "The safe haven, hedging, and diversification properties of oil, gold, and cryptocurrency for the G7 equity markets: Evidence from the pre- and post-COVID-19 periods," Research in International Business and Finance, Elsevier, vol. 67(PB).
    11. Rubbaniy, Ghulame & Khalid, Ali Awais & Syriopoulos, Konstantinos & Samitas, Aristeidis, 2022. "Safe-haven properties of soft commodities during times of Covid-19," Journal of Commodity Markets, Elsevier, vol. 27(C).
    12. Assaf, Ata & Mokni, Khaled & Youssef, Manel, 2023. "COVID-19 and information flow between cryptocurrencies, and conventional financial assets," The Quarterly Review of Economics and Finance, Elsevier, vol. 89(C), pages 73-81.
    13. Konstantinos Gkillas & Elie Bouri & Rangan Gupta & David Roubaud, 2020. "Spillovers in Higher-Order Moments of Crude Oil, Gold, and Bitcoin," Working Papers 202068, University of Pretoria, Department of Economics.
    14. Mohamed Yousfi & Abderrazak Dhaoui & Houssam Bouzgarrou, 2021. "Risk Spillover during the COVID-19 Global Pandemic and Portfolio Management," JRFM, MDPI, vol. 14(5), pages 1-29, May.
    15. Jiang, Yonghong & Lie, Jiayi & Wang, Jieru & Mu, Jinqi, 2021. "Revisiting the roles of cryptocurrencies in stock markets: A quantile coherency perspective," Economic Modelling, Elsevier, vol. 95(C), pages 21-34.
    16. Salisu, Afees A. & Vo, Xuan Vinh & Lucey, Brian, 2021. "Gold and US sectoral stocks during COVID-19 pandemic," Research in International Business and Finance, Elsevier, vol. 57(C).
    17. Baur, Dirk G. & Oll, Josua, 2022. "Bitcoin investments and climate change: A financial and carbon intensity perspective," Finance Research Letters, Elsevier, vol. 47(PA).
    18. Akhtaruzzaman, Md & Banerjee, Ameet Kumar & Ghardallou, Wafa & Umar, Zaghum, 2022. "Is greenness an optimal hedge for sectoral stock indices?," Economic Modelling, Elsevier, vol. 117(C).
    19. Chunling Li & Nosherwan Khaliq & Leslie Chinove & Usama Khaliq & József Popp & Judit Oláh, 2023. "Cryptocurrency Acceptance Model to Analyze Consumers’ Usage Intention: Evidence From Pakistan," SAGE Open, , vol. 13(1), pages 21582440231, March.
    20. Parthajit Kayal & Purnima Rohilla, 2021. "Bitcoin in the economics and finance literature: a survey," SN Business & Economics, Springer, vol. 1(7), pages 1-21, July.
    21. Wen, Danyan & Wang, Yudong & Ma, Chaoqun & Zhang, Yaojie, 2020. "Information transmission between gold and financial assets: Mean, volatility, or risk spillovers?," Resources Policy, Elsevier, vol. 69(C).
    22. Zhang, Dingxuan & Sun, Yuying & Duan, Hongbo & Hong, Yongmiao & Wang, Shouyang, 2023. "Speculation or currency? Multi-scale analysis of cryptocurrencies—The case of Bitcoin," International Review of Financial Analysis, Elsevier, vol. 88(C).
    23. Takuji Kinkyo, 2022. "Hedging capabilities of Bitcoin for Asian currencies," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 1769-1784, April.
    24. Kaczmarek, Tomasz & Będowska-Sójka, Barbara & Grobelny, Przemysław & Perez, Katarzyna, 2022. "False Safe Haven Assets: Evidence From the Target Volatility Strategy Based on Recurrent Neural Network," Research in International Business and Finance, Elsevier, vol. 60(C).
    25. Ghulam Mujtaba & Asima Siddique & Nader Naifar & Syed Jawad Hussain Shahzad, 2024. "Hedge and safe haven role of commodities for the US and Chinese equity markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(2), pages 2381-2414, April.
    26. Seyed Alireza Athari & Ngo Thai Hung, 2022. "Time–frequency return co-movement among asset classes around the COVID-19 outbreak: portfolio implications," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 46(4), pages 736-756, October.
    27. Ngo, Vu Minh & Nguyen, Phuc Van & Hoang, Yen Hai, 2024. "The impacts of geopolitical risks on gold, oil and financial reserve management," Resources Policy, Elsevier, vol. 90(C).
    28. Dirk G. Baur & Thomas Dimpfl, 2021. "The volatility of Bitcoin and its role as a medium of exchange and a store of value," Empirical Economics, Springer, vol. 61(5), pages 2663-2683, November.
    29. Tiwari, Aviral Kumar & Abakah, Emmanuel Joel Aikins & Karikari, Nana Kwasi & Gil-Alana, Luis Alberiko, 2022. "The outbreak of COVID-19 and stock market liquidity: Evidence from emerging and developed equity markets," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    30. Morema, Kgotso & Bonga-Bonga, Lumengo, 2020. "The impact of oil and gold price fluctuations on the South African equity market: Volatility spillovers and financial policy implications," Resources Policy, Elsevier, vol. 68(C).
    31. Elie Bouri & Rangan Gupta & Chi keung marco Lau & David Roubaud, 2021. "Risk aversion and Bitcoin returns in extreme quantiles," Economics Bulletin, AccessEcon, vol. 41(3), pages 1374-1386.
    32. Nezir Köse & Hakan Yildirim & Emre Ünal & Boqiang Lin, 2024. "The Bitcoin price and Bitcoin price uncertainty: Evidence of Bitcoin price volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(4), pages 673-695, April.
    33. Ishtiaq Ahmad Bajwa & Shafiq Ur Rehman & Abid Iqbal & Zaheer Anwer & Murtaza Ashiq & Muhammad Ajmal Khan, 2022. "Past, Present and Future of FinTech Research: A Bibliometric Analysis," SAGE Open, , vol. 12(4), pages 21582440221, October.
    34. Papadamou, Stephanos & Kyriazis, Nikolaos A. & Tzeremes, Panayiotis G., 2021. "Non-linear causal linkages of EPU and gold with major cryptocurrencies during bull and bear markets," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    35. Beckmann, Joscha & Geldner, Teo & Wüstenfeld, Jan, 2024. "The relevance of media sentiment for small and large scale bitcoin investors," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 92(C).
    36. Ha, Le Thanh & Nham, Nguyen Thi Hong, 2022. "An application of a TVP-VAR extended joint connected approach to explore connectedness between WTI crude oil, gold, stock and cryptocurrencies during the COVID-19 health crisis," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    37. Patel, Ritesh & Kumar, Sanjeev & Bouri, Elie & Iqbal, Najaf, 2023. "Spillovers between green and dirty cryptocurrencies and socially responsible investments around the war in Ukraine," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 143-162.
    38. Maghyereh, Aktham & Abdoh, Hussein, 2020. "Tail dependence between Bitcoin and financial assets: Evidence from a quantile cross-spectral approach," International Review of Financial Analysis, Elsevier, vol. 71(C).
    39. Chemkha, Rahma & BenSaïda, Ahmed & Ghorbel, Ahmed & Tayachi, Tahar, 2021. "Hedge and safe haven properties during COVID-19: Evidence from Bitcoin and gold," The Quarterly Review of Economics and Finance, Elsevier, vol. 82(C), pages 71-85.
    40. Maghyereh, Aktham & Abdoh, Hussein, 2021. "Time–frequency quantile dependence between Bitcoin and global equity markets," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    41. Su, Chi-Wei & Yang, Shengjie & Qin, Meng & Lobonţ, Oana-Ramona, 2023. "Gold vs bitcoin: Who can resist panic in the U.S.?," Resources Policy, Elsevier, vol. 85(PA).
    42. Noman, Abu Hanifa Md & Karim, Muhammad Mahmudul & Hassan, Mohammad Kabir & Khan, Muhammad Asif & Pervin, Sajeda, 2023. "COVID-19 pandemic and the dynamics of major investable assets: What gives shelter to investors?," International Review of Economics & Finance, Elsevier, vol. 86(C), pages 14-30.
    43. Su, Chi-Wei & Qin, Meng & Tao, Ran & Umar, Muhammad, 2020. "Financial implications of fourth industrial revolution: Can bitcoin improve prospects of energy investment?," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    44. Mensi, Walid & Yousaf, Imran & Vo, Xuan Vinh & Kang, Sang Hoon, 2022. "Asymmetric spillover and network connectedness between gold, BRENT oil and EU subsector markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 76(C).
    45. Tetsuji Tanaka & Jin Guo, 2020. "International price volatility transmission and structural change: a market connectivity analysis in the beef sector," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-13, December.
    46. Hsu, Shu-Han & Cheng, Po-Keng & Yang, Yiwen, 2024. "Diversification, hedging, and safe-haven characteristics of cryptocurrencies: A structural change approach," International Review of Financial Analysis, Elsevier, vol. 93(C).
    47. Ben Khelifa, Soumaya & Guesmi, Khaled & Urom, Christian, 2021. "Exploring the relationship between cryptocurrencies and hedge funds during COVID-19 crisis," International Review of Financial Analysis, Elsevier, vol. 76(C).
    48. Virginie Terraza & Aslı Boru İpek & Mohammad Mahdi Rounaghi, 2024. "The nexus between the volatility of Bitcoin, gold, and American stock markets during the COVID-19 pandemic: evidence from VAR-DCC-EGARCH and ANN models," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-34, December.
    49. Maghyereh, Aktham & Awartani, Basel & Virk, Nader S., 2022. "Asymmetric risk transmissions between oil, gold and US equities: Recent evidence from the realized variance of the futures prices," Resources Policy, Elsevier, vol. 79(C).
    50. Soni, Rajat Kumar & Nandan, Tanuj, 2022. "Modeling Covid-19 contagious effect between asset markets and commodity futures in India," Resources Policy, Elsevier, vol. 79(C).
    51. David E. Allen, 2022. "Cryptocurrencies, Diversification and the COVID-19 Pandemic," JRFM, MDPI, vol. 15(3), pages 1-25, February.
    52. Wei Wang & Haibo Wang, 2024. "Interconnected Markets: Exploring the Dynamic Relationship Between BRICS Stock Markets and Cryptocurrency," Papers 2406.07641, arXiv.org.
    53. Kyriazis, Nikolaos & Papadamou, Stephanos & Tzeremes, Panayiotis & Corbet, Shaen, 2023. "Can cryptocurrencies provide a viable hedging mechanism for benchmark index investors?," Research in International Business and Finance, Elsevier, vol. 64(C).
    54. Adel Benhamed & Ahlem Selma Messai & Ghassen El Montasser, 2023. "On the Determinants of Bitcoin Returns and Volatility: What We Get from Gets?," Sustainability, MDPI, vol. 15(3), pages 1-21, January.
    55. Zhenghui Li & Zhiming Ao & Bin Mo, 2021. "Revisiting the Valuable Roles of Global Financial Assets for International Stock Markets: Quantile Coherence and Causality-in-Quantiles Approaches," Mathematics, MDPI, vol. 9(15), pages 1-18, July.
    56. Banerjee, Ameet Kumar & Akhtaruzzaman, Md & Sensoy, Ahmet & Goodell, John W., 2024. "Volatility spillovers and hedging strategies between impact investing and agricultural commodities," International Review of Financial Analysis, Elsevier, vol. 94(C).
    57. Akhtaruzzaman, Md & Banerjee, Ameet Kumar & Le, Van & Moussa, Faten, 2024. "Hedging precious metals with impact investing," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 651-664.
    58. Hanif, Waqas & Areola Hernandez, Jose & Troster, Victor & Kang, Sang Hoon & Yoon, Seong-Min, 2022. "Nonlinear dependence and spillovers between cryptocurrency and global/regional equity markets," Pacific-Basin Finance Journal, Elsevier, vol. 74(C).
    59. Nakagawa, Kei & Sakemoto, Ryuta, 2022. "Cryptocurrency network factors and gold," Finance Research Letters, Elsevier, vol. 46(PB).
    60. Belhassine, Olfa & Karamti, Chiraz, 2021. "Contagion and portfolio management in times of COVID-19," Economic Analysis and Policy, Elsevier, vol. 72(C), pages 73-86.
    61. Andreas Renard Widarto & Harjum Muharam & Sugeng Wahyudi & Irene Rini Demi Pangestuti, 2022. "ASEAN-5 and Crypto Hedge Fund: Dynamic Portfolio Approach," SAGE Open, , vol. 12(2), pages 21582440221, April.
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    128. Marcin Wk{a}torek & Stanis{l}aw Dro.zd.z & Jaros{l}aw Kwapie'n & Ludovico Minati & Pawe{l} O'swik{e}cimka & Marek Stanuszek, 2020. "Multiscale characteristics of the emerging global cryptocurrency market," Papers 2010.15403, arXiv.org, revised Mar 2021.
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    130. Muhammad Abubakr Naeem & Mudassar Hasan & Abraham Agyemang & Md Iftekhar Hasan Chowdhury & Faruk Balli, 2023. "Time‐frequency dynamics between fear connectedness of stocks and alternative assets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(2), pages 2188-2201, April.
    131. Umar, Muhammad & Su, Chi-Wei & Rizvi, Syed Kumail Abbas & Shao, Xue-Feng, 2021. "Bitcoin: A safe haven asset and a winner amid political and economic uncertainties in the US?," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
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  14. Bouri, Elie & Shahzad, Syed Jawad Hussain & Roubaud, David & Kristoufek, Ladislav & Lucey, Brian, 2020. "Bitcoin, gold, and commodities as safe havens for stocks: New insight through wavelet analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 77(C), pages 156-164.

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    2. Bouri, Elie & Cepni, Oguzhan & Gabauer, David & Gupta, Rangan, 2021. "Return connectedness across asset classes around the COVID-19 outbreak," International Review of Financial Analysis, Elsevier, vol. 73(C).
    3. Elgammal, Mohammed M. & Ahmed, Walid M.A. & Alshami, Abdullah, 2021. "Price and volatility spillovers between global equity, gold, and energy markets prior to and during the COVID-19 pandemic," Resources Policy, Elsevier, vol. 74(C).
    4. Ihsan Erdem Kayral & Ahmed Jeribi & Sahar Loukil, 2023. "Are Bitcoin and Gold a Safe Haven during COVID-19 and the 2022 Russia–Ukraine War?," JRFM, MDPI, vol. 16(4), pages 1-22, April.
    5. Będowska-Sójka, Barbara & Górka, Joanna & Hemmings, Danial & Zaremba, Adam, 2024. "Uncertainty and cryptocurrency returns: A lesson from turbulent times," International Review of Financial Analysis, Elsevier, vol. 94(C).
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    2. Liu, Chao & Fan, Yixin & Xie, Qiwei & Wang, Chao, 2022. "Market-based versus bank-based financial structure in China: From the perspective of financial risk," Structural Change and Economic Dynamics, Elsevier, vol. 62(C), pages 24-39.
    3. Ruan, Qingsong & Meng, Lu & Lv, Dayong, 2021. "Effect of introducing Bitcoin futures on the underlying Bitcoin market efficiency: A multifractal analysis," Chaos, Solitons & Fractals, Elsevier, vol. 153(P1).
    4. Éder Pereira & Paulo Ferreira & Derick Quintino, 2022. "Non-Fungible Tokens (NFTs) and Cryptocurrencies: Efficiency and Comovements," FinTech, MDPI, vol. 1(4), pages 1-8, October.
    5. Jaros{l}aw Kwapie'n & Marcin Wk{a}torek & Stanis{l}aw Dro.zd.z, 2021. "Cryptocurrency Market Consolidation in 2020--2021," Papers 2112.06552, arXiv.org.
    6. Nie, Chun-Xiao, 2022. "Analysis of critical events in the correlation dynamics of cryptocurrency market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 586(C).
    7. Stanis{l}aw Dro.zd.z & Jaros{l}aw Kwapie'n & Pawe{l} O'swik{e}cimka & Tomasz Stanisz & Marcin Wk{a}torek, 2020. "Complexity in economic and social systems: cryptocurrency market at around COVID-19," Papers 2009.10030, arXiv.org.
    8. James, Nick & Menzies, Max & Chan, Jennifer, 2021. "Changes to the extreme and erratic behaviour of cryptocurrencies during COVID-19," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    9. Mensi, Walid & El Khoury, Rim & Ali, Syed Riaz Mahmood & Vo, Xuan Vinh & Kang, Sang Hoon, 2023. "Quantile dependencies and connectedness between the gold and cryptocurrency markets: Effects of the COVID-19 crisis," Research in International Business and Finance, Elsevier, vol. 65(C).
    10. Nick James, 2021. "Dynamics, behaviours, and anomaly persistence in cryptocurrencies and equities surrounding COVID-19," Papers 2101.00576, arXiv.org, revised Feb 2021.
    11. James, Nick & Chin, Kevin, 2022. "On the systemic nature of global inflation, its association with equity markets and financial portfolio implications," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 593(C).
    12. González, Maria de la O. & Jareño, Francisco & Skinner, Frank S., 2021. "Asymmetric interdependencies between large capital cryptocurrency and Gold returns during the COVID-19 pandemic crisis," International Review of Financial Analysis, Elsevier, vol. 76(C).
    13. Zheng, Zhiyong & Lu, Yunfan & Zhang, Junhuan, 2022. "Multiscale complexity fluctuation behaviours of stochastic interacting cryptocurrency price model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 593(C).
    14. Derick Quintino & Cristiane Ogino & Inzamam Ul Haq & Paulo Ferreira & Márcia Oliveira, 2023. "An Analysis of Dynamic Correlations among Oil, Natural Gas and Ethanol Markets: New Evidence from the Pre- and Post-COVID-19 Crisis," Energies, MDPI, vol. 16(5), pages 1-14, February.
    15. Mokni, Khaled, 2021. "When, where, and how economic policy uncertainty predicts Bitcoin returns and volatility? A quantiles-based analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 65-73.
    16. Lahmiri, Salim & Bekiros, Stelios, 2021. "The effect of COVID-19 on long memory in returns and volatility of cryptocurrency and stock markets," Chaos, Solitons & Fractals, Elsevier, vol. 151(C).
    17. Binh Nguyen Thanh & Thai Nguyen Vu Hong & Huy Pham & Thanh Nguyen Cong & Thu Pham Thi Anh, 2023. "Are the stabilities of stablecoins connected?," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 50(3), pages 515-525, September.
    18. Kumar, Ashish & Iqbal, Najaf & Mitra, Subrata Kumar & Kristoufek, Ladislav & Bouri, Elie, 2022. "Connectedness among major cryptocurrencies in standard times and during the COVID-19 outbreak," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 77(C).
    19. Stefano Ferretti, 2023. "On the Modeling and Simulation of Portfolio Allocation Schemes: an Approach Based on Network Community Detection," Computational Economics, Springer;Society for Computational Economics, vol. 62(3), pages 969-1005, October.
    20. Rehman, Mobeen Ur & Vinh Vo, Xuan, 2020. "Cryptocurrencies and precious metals: A closer look from diversification perspective," Resources Policy, Elsevier, vol. 66(C).
    21. Cao, Guangxi & Xie, Wenhao, 2021. "The impact of the shutdown policy on the asymmetric interdependence structure and risk transmission of cryptocurrency and China’s financial market," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    22. Mingbo Zheng & Gen-Fu Feng & Xinxin Zhao & Chun-Ping Chang, 2023. "The transaction behavior of cryptocurrency and electricity consumption," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-18, December.
    23. James, Nick, 2021. "Dynamics, behaviours, and anomaly persistence in cryptocurrencies and equities surrounding COVID-19," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 570(C).
    24. Shahzad, Syed Jawad Hussain & Bouri, Elie & Ahmad, Tanveer & Naeem, Muhammad Abubakr, 2022. "Extreme tail network analysis of cryptocurrencies and trading strategies," Finance Research Letters, Elsevier, vol. 44(C).
    25. Qureshi, Saba & Aftab, Muhammad & Bouri, Elie & Saeed, Tareq, 2020. "Dynamic interdependence of cryptocurrency markets: An analysis across time and frequency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 559(C).
    26. Bouri, Elie & Saeed, Tareq & Vo, Xuan Vinh & Roubaud, David, 2021. "Quantile connectedness in the cryptocurrency market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 71(C).
    27. Marcin Wk{a}torek & Stanis{l}aw Dro.zd.z & Jaros{l}aw Kwapie'n & Ludovico Minati & Pawe{l} O'swik{e}cimka & Marek Stanuszek, 2020. "Multiscale characteristics of the emerging global cryptocurrency market," Papers 2010.15403, arXiv.org, revised Mar 2021.
    28. Walid Mensi & Mobeen Ur Rehman & Muhammad Shafiullah & Khamis Hamed Al-Yahyaee & Ahmet Sensoy, 2021. "High frequency multiscale relationships among major cryptocurrencies: portfolio management implications," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-21, December.

  16. Shahzad, Syed Jawad Hussain & Bouri, Elie & Kayani, Ghulam Mujtaba & Nasir, Rana Muhammad & Kristoufek, Ladislav, 2020. "Are clean energy stocks efficient? Asymmetric multifractal scaling behaviour," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 550(C).

    Cited by:

    1. Umar, Muhammad & Farid, Saqib & Naeem, Muhammad Abubakr, 2022. "Time-frequency connectedness among clean-energy stocks and fossil fuel markets: Comparison between financial, oil and pandemic crisis," Energy, Elsevier, vol. 240(C).
    2. Choi, Gahyun & Park, Kwangyeol & Yi, Eojin & Ahn, Kwangwon, 2023. "Price fairness: Clean energy stocks and the overall market," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
    3. Ren, Xiaohang & Xiao, Ya & Duan, Kun & Urquhart, Andrew, 2024. "Spillover effects between fossil energy and green markets: Evidence from informational inefficiency," Energy Economics, Elsevier, vol. 131(C).
    4. Naeem, Muhammad Abubakr & Bouri, Elie & Peng, Zhe & Shahzad, Syed Jawad Hussain & Vo, Xuan Vinh, 2021. "Asymmetric efficiency of cryptocurrencies during COVID19," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    5. Sharma, Gagan Deep & Sarker, Tapan & Rao, Amar & Talan, Gaurav & Jain, Mansi, 2022. "Revisiting conventional and green finance spillover in post-COVID world: Evidence from robust econometric models," Global Finance Journal, Elsevier, vol. 51(C).
    6. Yao, Can-Zhong & Mo, Yi-Na & Zhang, Ze-Kun, 2021. "A study of the efficiency of the Chinese clean energy stock market and its correlation with the crude oil market based on an asymmetric multifractal scaling behavior analysis," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    7. Kristjanpoller, Werner & Nekhili, Ramzi & Bouri, Elie, 2024. "Blockchain ETFs and the cryptocurrency and Nasdaq markets: Multifractal and asymmetric cross-correlations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 637(C).
    8. Ahmed, Walid M.A. & Sleem, Mohamed A.E., 2023. "Short- and long-run determinants of the price behavior of US clean energy stocks: A dynamic ARDL simulations approach," Energy Economics, Elsevier, vol. 124(C).
    9. Ferreira, Joaquim & Morais, Flávio, 2023. "Predict or to be predicted? A transfer entropy view between adaptive green markets, structural shocks and sentiment index," Finance Research Letters, Elsevier, vol. 56(C).
    10. Naqvi, Bushra & Rizvi, Syed Kumail Abbas & Hasnaoui, Amir & Shao, Xuefeng, 2022. "Going beyond sustainability: The diversification benefits of green energy financial products," Energy Economics, Elsevier, vol. 111(C).
    11. Wang, Zhuo & Chen, Xiaodan & Zhou, Chunyan & Zhang, Yifeng & Wei, Yu, 2024. "Examining the quantile cross-coherence between fossil energy and clean energy: Is the dependence structure changing with the COVID-19 outbreak?," International Review of Financial Analysis, Elsevier, vol. 94(C).
    12. Zhuang, Xiaoyang & Wei, Dan, 2022. "Asymmetric multifractality, comparative efficiency analysis of green finance markets: A dynamic study by index-based model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    13. Zeyi Fu & Hongli Niu & Weiqing Wang, 2023. "Market Efficiency and Cross-Correlations of Chinese New Energy Market with Other Assets: Evidence from Multifractality Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 62(3), pages 1287-1311, October.
    14. Hanif, Waqas & Arreola Hernandez, Jose & Mensi, Walid & Kang, Sang Hoon & Uddin, Gazi Salah & Yoon, Seong-Min, 2021. "Nonlinear dependence and connectedness between clean/renewable energy sector equity and European emission allowance prices," Energy Economics, Elsevier, vol. 101(C).
    15. Naeem, Muhammad Abubakr & Karim, Sitara & Farid, Saqib & Tiwari, Aviral Kumar, 2022. "Comparing the asymmetric efficiency of dirty and clean energy markets pre and during COVID-19," Economic Analysis and Policy, Elsevier, vol. 75(C), pages 548-562.
    16. Sakiru, Solarin Adebola & Gil-Alana, Luis A. & Gonzalez-Blanch, Maria Jesus, 2022. "Persistence of economic complexity in OECD countries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    17. Naeem, Muhammad Abubakr & Farid, Saqib & Ferrer, Román & Shahzad, Syed Jawad Hussain, 2021. "Comparative efficiency of green and conventional bonds pre- and during COVID-19: An asymmetric multifractal detrended fluctuation analysis," Energy Policy, Elsevier, vol. 153(C).
    18. Khurshid, Adnan & Khan, Khalid & Cifuentes-Faura, Javier & Chen, Yufeng, 2024. "Asymmetric multifractality: Comparative efficiency analysis of global technological and renewable energy prices using MFDFA and A-MFDFA approaches," Energy, Elsevier, vol. 289(C).
    19. Çelik, İsmail & Sak, Ahmet Furkan & Höl, Arife Özdemir & Vergili, Gizem, 2022. "The dynamic connectedness and hedging opportunities of implied and realized volatility: Evidence from clean energy ETFs," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
    20. Roy, Preeti & Ahmad, Wasim & Sadorsky, Perry & Phani, B.V., 2022. "What do we know about the idiosyncratic risk of clean energy equities?," Energy Economics, Elsevier, vol. 112(C).
    21. Zhang, Li & Wang, Lu & Peng, Lijuan & Luo, Keyu, 2023. "Measuring the response of clean energy stock price volatility to extreme shocks," Renewable Energy, Elsevier, vol. 206(C), pages 1289-1300.
    22. Rehman, Mobeen Ur & Nautiyal, Neeraj & Ghardallou, Wafa & Vo, Xuan Vinh & Zeitun, Rami, 2023. "Comovement and spillover among energy markets: A Comparison across different crisis periods," Economic Analysis and Policy, Elsevier, vol. 79(C), pages 277-302.
    23. Sharma, Gagan Deep & Verma, Mahesh & Shahbaz, Muhammad & Gupta, Mansi & Chopra, Ritika, 2022. "Transitioning green finance from theory to practice for renewable energy development," Renewable Energy, Elsevier, vol. 195(C), pages 554-565.

  17. Ferreira, Paulo & Kristoufek, Ladislav, 2020. "Uncovered interest rate parity through the lens of fractal methods: Evidence from the European Union," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 553(C).

    Cited by:

    1. Tilfani, Oussama & Kristoufek, Ladislav & Ferreira, Paulo & El Boukfaoui, My Youssef, 2022. "Heterogeneity in economic relationships: Scale dependence through the multivariate fractal regression," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 588(C).
    2. Dąbrowski, Marek A. & Janus, Jakub, 2021. "Does the interest parity puzzle hold for Central and Eastern European economies?," MPRA Paper 107558, University Library of Munich, Germany.
    3. Nazlioglu, Saban & Kucukkaplan, Ilhan & Kilic, Emre & Altuntas, Mehmet, 2022. "Financial market integration of emerging markets: Heavy tails, structural shifts, nonlinearity, and asymmetric persistence," Research in International Business and Finance, Elsevier, vol. 62(C).

  18. Kukacka, Jiri & Kristoufek, Ladislav, 2020. "Do ‘complex’ financial models really lead to complex dynamics? Agent-based models and multifractality," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).

    Cited by:

    1. Onur Özdemir & Anoop S. Kumar, 2024. "Dynamic Efficiency and Herd Behavior During Pre- and Post-COVID-19 in the NFT Market: Evidence from Multifractal Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 63(3), pages 1255-1279, March.
    2. Matthieu Garcin, 2023. "Complexity measure, kernel density estimation, bandwidth selection, and the efficient market hypothesis," Papers 2305.13123, arXiv.org.
    3. Krenar Avdulaj & Ladislav Kristoufek, 2020. "On Tail Dependence and Multifractality," Mathematics, MDPI, vol. 8(10), pages 1-13, October.
    4. Bornholdt, Stefan, 2022. "A q-spin Potts model of markets: Gain–loss asymmetry in stock indices as an emergent phenomenon," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 588(C).
    5. Vandin, Andrea & Giachini, Daniele & Lamperti, Francesco & Chiaromonte, Francesca, 2022. "Automated and distributed statistical analysis of economic agent-based models," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    6. Huang, Chuangxia & Deng, Yunke & Yang, Xiaoguang & Cao, Jinde & Yang, Xin, 2021. "A network perspective of comovement and structural change: Evidence from the Chinese stock market," International Review of Financial Analysis, Elsevier, vol. 76(C).
    7. Noemi Schmitt & Ivonne Schwartz & Frank Westerhoff, 2022. "Heterogeneous speculators and stock market dynamics: a simple agent-based computational model," The European Journal of Finance, Taylor & Francis Journals, vol. 28(13-15), pages 1263-1282, October.
    8. Jiri Kukacka & Ladislav Kristoufek, 2023. "Fundamental and speculative components of the cryptocurrency pricing dynamics," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-23, December.
    9. Cerruti, Gianluca & Lombardini, Simone, 2022. "Financial bubbles as a recursive process lead by short-term strategies," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 555-568.
    10. Stefan Bornholdt, 2021. "A q-spin Potts model of markets: Gain-loss asymmetry in stock indices as an emergent phenomenon," Papers 2112.06290, arXiv.org.
    11. Aurelio F. Bariviera, 2020. "One model is not enough: heterogeneity in cryptocurrencies' multifractal profiles," Papers 2003.09720, arXiv.org, revised Jun 2020.
    12. Andrea Vandin & Daniele Giachini & Francesco Lamperti & Francesca Chiaromonte, 2021. "Automated and Distributed Statistical Analysis of Economic Agent-Based Models," Papers 2102.05405, arXiv.org, revised Nov 2023.
    13. Matthieu Garcin, 2023. "Complexity measure, kernel density estimation, bandwidth selection, and the efficient market hypothesis," Working Papers hal-04102815, HAL.
    14. Zila, Eric & Kukacka, Jiri, 2023. "Moment set selection for the SMM using simple machine learning," Journal of Economic Behavior & Organization, Elsevier, vol. 212(C), pages 366-391.
    15. Gradojevic, Nikola & Kukolj, Dragan & Adcock, Robert & Djakovic, Vladimir, 2023. "Forecasting Bitcoin with technical analysis: A not-so-random forest?," International Journal of Forecasting, Elsevier, vol. 39(1), pages 1-17.
    16. F. Cavalli & A. Naimzada & N. Pecora & M. Pireddu, 2021. "Market sentiment and heterogeneous agents in an evolutive financial model," Journal of Evolutionary Economics, Springer, vol. 31(4), pages 1189-1219, September.

  19. Kristoufek, Ladislav, 2019. "Is the Bitcoin price dynamics economically reasonable? Evidence from fundamental laws," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).

    Cited by:

    1. Garcia-Jorcano, Laura & Benito, Sonia, 2020. "Studying the properties of the Bitcoin as a diversifying and hedging asset through a copula analysis: Constant and time-varying," Research in International Business and Finance, Elsevier, vol. 54(C).
    2. Hu, Yang & Hou, Yang (Greg) & Oxley, Les & Corbet, Shaen, 2021. "Does blockchain patent-development influence Bitcoin risk?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 70(C).
    3. Kristoufek, Ladislav & Bouri, Elie, 2023. "Exploring sources of statistical arbitrage opportunities among Bitcoin exchanges," Finance Research Letters, Elsevier, vol. 51(C).
    4. Jiri Kukacka & Ladislav Kristoufek, 2023. "Fundamental and speculative components of the cryptocurrency pricing dynamics," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-23, December.
    5. Ladislav Kristoufek, 2022. "On the role of stablecoins in cryptoasset pricing dynamics," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-26, December.
    6. Dunbar, Kwamie & Owusu-Amoako, Johnson, 2022. "Cryptocurrency returns under empirical asset pricing," International Review of Financial Analysis, Elsevier, vol. 82(C).
    7. Kubal, Jan & Kristoufek, Ladislav, 2022. "Exploring the relationship between Bitcoin price and network’s hashrate within endogenous system," International Review of Financial Analysis, Elsevier, vol. 84(C).

  20. Kristoufek, Ladislav & Vosvrda, Miloslav, 2019. "Cryptocurrencies market efficiency ranking: Not so straightforward," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 531(C).

    Cited by:

    1. Stanisław Drożdż & Ludovico Minati & Paweł Oświȩcimka & Marek Stanuszek & Marcin Wa̧torek, 2019. "Signatures of the Crypto-Currency Market Decoupling from the Forex," Future Internet, MDPI, vol. 11(7), pages 1-18, July.
    2. Bouri, Elie & Vo, Xuan Vinh & Saeed, Tareq, 2021. "Return equicorrelation in the cryptocurrency market: Analysis and determinants," Finance Research Letters, Elsevier, vol. 38(C).
    3. Tran, Vu Le & Leirvik, Thomas, 2020. "Efficiency in the markets of crypto-currencies," Finance Research Letters, Elsevier, vol. 35(C).
    4. Kristjanpoller, Werner & Bouri, Elie & Takaishi, Tetsuya, 2020. "Cryptocurrencies and equity funds: Evidence from an asymmetric multifractal analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    5. Stanis{l}aw Dro.zd.z & Jaros{l}aw Kwapie'n & Pawe{l} O'swik{e}cimka & Tomasz Stanisz & Marcin Wk{a}torek, 2020. "Complexity in economic and social systems: cryptocurrency market at around COVID-19," Papers 2009.10030, arXiv.org.
    6. Fernandes, Leonardo H.S. & de Araujo, Fernando H.A. & Silva, José W.L. & Tabak, Benjamin Miranda, 2022. "Booms in commodities price: Assessing disorder and similarity over economic cycles," Resources Policy, Elsevier, vol. 79(C).
    7. Okorie, David Iheke & Bouri, Elie & Mazur, Mieszko, 2024. "NFTs versus conventional cryptocurrencies: A comparative analysis of market efficiency around COVID-19 and the Russia-Ukraine conflict," The Quarterly Review of Economics and Finance, Elsevier, vol. 95(C), pages 126-151.
    8. Helder Miguel Correia Virtuoso Sebastião & Paulo José Osório Rupino Da Cunha & Pedro Manuel Cortesão Godinho, 2021. "Cryptocurrencies and blockchain. Overview and future perspectives," International Journal of Economics and Business Research, Inderscience Enterprises Ltd, vol. 21(3), pages 305-342.
    9. Grobys, Klaus & Junttila, Juha, 2021. "Speculation and lottery-like demand in cryptocurrency markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 71(C).
    10. Shrestha, Keshab & Naysary, Babak & Philip, Sheena Sara Suresh, 2023. "Fintech market efficiency: A multifractal detrended fluctuation analysis," Finance Research Letters, Elsevier, vol. 54(C).
    11. Mustafa Tevfik Kartal & Mustafa Kevser & Fatih Ayhan, 2023. "Asymmetric effects of global factors on return of cryptocurrencies by novel nonlinear quantile approaches," Economic Change and Restructuring, Springer, vol. 56(3), pages 1515-1535, June.
    12. Aurelio F. Bariviera, 2020. "One model is not enough: heterogeneity in cryptocurrencies' multifractal profiles," Papers 2003.09720, arXiv.org, revised Jun 2020.
    13. Marcin Wk{a}torek & Stanis{l}aw Dro.zd.z & Jaros{l}aw Kwapie'n & Ludovico Minati & Pawe{l} O'swik{e}cimka & Marek Stanuszek, 2020. "Multiscale characteristics of the emerging global cryptocurrency market," Papers 2010.15403, arXiv.org, revised Mar 2021.
    14. Abdullah, Mohammad & Chowdhury, Mohammad Ashraful Ferdous & Sulong, Zunaidah, 2023. "Asymmetric efficiency and connectedness among green stocks, halal tourism stocks, cryptocurrencies, and commodities: Portfolio hedging implications," Resources Policy, Elsevier, vol. 81(C).
    15. Brouty, Xavier & Garcin, Matthieu, 2024. "Fractal properties, information theory, and market efficiency," Chaos, Solitons & Fractals, Elsevier, vol. 180(C).
    16. A. Gómez-Águila & J. E. Trinidad-Segovia & M. A. Sánchez-Granero, 2022. "Improvement in Hurst exponent estimation and its application to financial markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-21, December.
    17. Manahov, Viktor & Urquhart, Andrew, 2021. "The efficiency of Bitcoin: A strongly typed genetic programming approach to smart electronic Bitcoin markets," International Review of Financial Analysis, Elsevier, vol. 73(C).
    18. Łęt Blanka & Sobański Konrad & Świder Wojciech & Włosik Katarzyna, 2022. "Is the cryptocurrency market efficient? Evidence from an analysis of fundamental factors for Bitcoin and Ethereum," International Journal of Management and Economics, Warsaw School of Economics, Collegium of World Economy, vol. 58(4), pages 351-370, December.
    19. Aslam, Faheem & Memon, Bilal Ahmed & Hunjra, Ahmed Imran & Bouri, Elie, 2023. "The dynamics of market efficiency of major cryptocurrencies," Global Finance Journal, Elsevier, vol. 58(C).
    20. Leirvik, Thomas, 2022. "Cryptocurrency returns and the volatility of liquidity," Finance Research Letters, Elsevier, vol. 44(C).
    21. Assaf, Ata & Mokni, Khaled & Yousaf, Imran & Bhandari, Avishek, 2023. "Long memory in the high frequency cryptocurrency markets using fractal connectivity analysis: The impact of COVID-19," Research in International Business and Finance, Elsevier, vol. 64(C).

  21. Ji, Qiang & Bouri, Elie & Roubaud, David & Kristoufek, Ladislav, 2019. "Information interdependence among energy, cryptocurrency and major commodity markets," Energy Economics, Elsevier, vol. 81(C), pages 1042-1055.

    Cited by:

    1. Fei Su & Lili Zhai & Yunyan Zhou & Zixi Zhuang & Feifan Wang, 2024. "Risk contagion in financial markets: A systematic review using bibliometric methods," Australian Economic Papers, Wiley Blackwell, vol. 63(1), pages 163-199, March.
    2. Ahmed, Walid M.A., 2021. "How do Islamic equity markets respond to good and bad volatility of cryptocurrencies? The case of Bitcoin," Pacific-Basin Finance Journal, Elsevier, vol. 70(C).
    3. Ghabri, Yosra & Ben Rhouma, Oussama & Gana, Marjène & Guesmi, Khaled & Benkraiem, Ramzi, 2022. "Information transmission among energy markets, cryptocurrencies, and stablecoins under pandemic conditions," International Review of Financial Analysis, Elsevier, vol. 82(C).
    4. Liu, Chang & Sun, Xiaolei & Wang, Jun & Li, Jianping & Chen, Jianming, 2021. "Multiscale information transmission between commodity markets: An EMD-Based transfer entropy network," Research in International Business and Finance, Elsevier, vol. 55(C).
    5. Lv, Fei & Yang, Chen & Fang, Libing, 2020. "Do the crude oil futures of the Shanghai International Energy Exchange improve asset allocation of Chinese petrochemical-related stocks?," International Review of Financial Analysis, Elsevier, vol. 71(C).
    6. Jun Hao & Xiaolei Sun & Qianqian Feng, 2020. "A Novel Ensemble Approach for the Forecasting of Energy Demand Based on the Artificial Bee Colony Algorithm," Energies, MDPI, vol. 13(3), pages 1-25, January.
    7. Pham, Linh & Huynh, Toan Luu Duc & Hanif, Waqas, 2023. "Time-varying asymmetric spillovers among cryptocurrency, green and fossil-fuel investments," Global Finance Journal, Elsevier, vol. 58(C).
    8. Gunay, Samet & Goodell, John W. & Muhammed, Shahnawaz & Kirimhan, Destan, 2023. "Frequency connectedness between FinTech, NFT and DeFi: Considering linkages to investor sentiment," International Review of Financial Analysis, Elsevier, vol. 90(C).
    9. Mbarki, Imen & Khan, Muhammad Arif & Karim, Sitara & Paltrinieri, Andrea & Lucey, Brian M., 2023. "Unveiling commodities-financial markets intersections from a bibliometric perspective," Resources Policy, Elsevier, vol. 83(C).
    10. Sun, Xiaolei & Liu, Chang & Wang, Jun & Li, Jianping, 2020. "Assessing the extreme risk spillovers of international commodities on maritime markets: A GARCH-Copula-CoVaR approach," International Review of Financial Analysis, Elsevier, vol. 68(C).
    11. Zhu, Bangzhu & Huang, Liqing & Yuan, Lili & Ye, Shunxin & Wang, Ping, 2020. "Exploring the risk spillover effects between carbon market and electricity market: A bidimensional empirical mode decomposition based conditional value at risk approach," International Review of Economics & Finance, Elsevier, vol. 67(C), pages 163-175.
    12. Ji, Qiang & Bahloul, Walid & Geng, Jiang-Bo & Gupta, Rangan, 2020. "Trading behaviour connectedness across commodity markets: Evidence from the hedgers’ sentiment perspective," Research in International Business and Finance, Elsevier, vol. 52(C).
    13. Lin, Mei-Yin & An, Che-Lun, 2021. "The relationship between Bitcoin and resource commodity futures: Evidence from NARDL approach," Resources Policy, Elsevier, vol. 74(C).
    14. Shimeng Shi, 2022. "Bitcoin futures risk premia," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(12), pages 2190-2217, December.
    15. Erdinc Akyildirim & Ahmet Goncu & Ahmet Sensoy, 2021. "Prediction of cryptocurrency returns using machine learning," Annals of Operations Research, Springer, vol. 297(1), pages 3-36, February.
    16. Xia, Tongshui & Ji, Qiang & Geng, Jiang-Bo, 2020. "Nonlinear dependence and information spillover between electricity and fuel source markets: New evidence from a multi-scale analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    17. Ma, Yu & Luan, Zhiqian, 2022. "Ethereum synchronicity, upside volatility and Bitcoin crash risk," Finance Research Letters, Elsevier, vol. 46(PA).
    18. Chwiłkowska-Kubala, Anna & Cyfert, Szymon & Malewska, Kamila & Mierzejewska, Katarzyna & Szumowski, Witold, 2023. "The impact of resources on digital transformation in energy sector companies. The role of readiness for digital transformation," Technology in Society, Elsevier, vol. 74(C).
    19. Damilola ABOLUWODI & Bomi NOMLALA & Paul-Francois MUZINDUTSI, 2022. "The COVID-19 Crisis and Interaction between the JSE, Real Estate, Energy, Commodity and Cryptocurrency Markets," Journal of Economics and Financial Analysis, Tripal Publishing House, vol. 6(1), pages 55-76.
    20. Albulescu, Claudiu Tiberiu & Tiwari, Aviral Kumar & Ji, Qiang, 2020. "Copula-based local dependence among energy, agriculture and metal commodities markets," Energy, Elsevier, vol. 202(C).
    21. Huang, Xiaohong & Huang, Shupei, 2020. "Identifying the comovement of price between China's and international crude oil futures: A time-frequency perspective," International Review of Financial Analysis, Elsevier, vol. 72(C).
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  22. Shahzad, Syed Jawad Hussain & Bouri, Elie & Roubaud, David & Kristoufek, Ladislav & Lucey, Brian, 2019. "Is Bitcoin a better safe-haven investment than gold and commodities?," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 322-330.

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    1. Wu, Shan & Tong, Mu & Yang, Zhongyi & Derbali, Abdelkader, 2019. "Does gold or Bitcoin hedge economic policy uncertainty?," Finance Research Letters, Elsevier, vol. 31(C), pages 171-178.
    2. Huang, Yingying & Duan, Kun & Urquhart, Andrew, 2023. "Time-varying dependence between Bitcoin and green financial assets: A comparison between pre- and post-COVID-19 periods," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    3. Bouri, Elie & Lucey, Brian & Roubaud, David, 2020. "Cryptocurrencies and the downside risk in equity investments," Finance Research Letters, Elsevier, vol. 33(C).
    4. Konstantakis, Konstantinos N. & Xidonas, Panos & Michaelides, Panayotis G. & Goutte, Stéphane, 2023. "Gold and CoVid-19: Uncovering the safe haven hypothesis with dynamic MSR modeling," International Review of Financial Analysis, Elsevier, vol. 89(C).
    5. Ghabri, Yosra & Ben Rhouma, Oussama & Gana, Marjène & Guesmi, Khaled & Benkraiem, Ramzi, 2022. "Information transmission among energy markets, cryptocurrencies, and stablecoins under pandemic conditions," International Review of Financial Analysis, Elsevier, vol. 82(C).
    6. Ihsan Erdem Kayral & Ahmed Jeribi & Sahar Loukil, 2023. "Are Bitcoin and Gold a Safe Haven during COVID-19 and the 2022 Russia–Ukraine War?," JRFM, MDPI, vol. 16(4), pages 1-22, April.
    7. Luisanna Cocco & Roberto Tonelli & Michele Marchesi, 2022. "Bitcoin as a Safe Haven during COVID-19 Disease," Future Internet, MDPI, vol. 14(4), pages 1-24, March.
    8. Onur Gozbasi & Buket Altinoz & Eyup Ensar Sahin, 2021. "Is Bitcoin a Safe Haven? A Study on the Factors that Affect Bitcoin Prices," International Journal of Economics and Financial Issues, Econjournals, vol. 11(4), pages 35-40.
    9. Bennett, Donyetta & Mekelburg, Erik & Williams, T.H., 2023. "BeFi meets DeFi: A behavioral finance approach to decentralized finance asset pricing," Research in International Business and Finance, Elsevier, vol. 65(C).
    10. Singh, Amanjot, 2021. "Investigating the dynamic relationship between litigation funding, gold, bitcoin and the stock market: The case of Australia," Economic Modelling, Elsevier, vol. 97(C), pages 45-57.
    11. Awasthi, Kritika & Ahmad, Wasim & Rahman, Abdul & Phani, B.V., 2020. "When US sneezes, clichés spread: How do the commodity index funds react then?," Resources Policy, Elsevier, vol. 69(C).
    12. Choi, Sangyup & Shin, Junhyeok, 2022. "Bitcoin: An inflation hedge but not a safe haven," Finance Research Letters, Elsevier, vol. 46(PB).
    13. Elie Bouri & Rangan Gupta & Xuan Vinh Vo, 2022. "Jumps in Geopolitical Risk and the Cryptocurrency Market: The Singularity of Bitcoin," Defence and Peace Economics, Taylor & Francis Journals, vol. 33(2), pages 150-161, February.
    14. Sinda Hadhri, 2021. "Fear of the Coronavirus and Cryptocurrencies' returns," Economics Bulletin, AccessEcon, vol. 41(3), pages 2041-2054.
    15. Yousaf, Imran & Yarovaya, Larisa, 2022. "Static and dynamic connectedness between NFTs, Defi and other assets: Portfolio implication," Global Finance Journal, Elsevier, vol. 53(C).
    16. Mohammad Bitar & Amine Tarazi, 2022. "A note on regulatory responses to COVID-19 pandemic: Balancing banks' solvency and contribution to recovery," Post-Print hal-03684360, HAL.
    17. Dwita Mariana, Christy & Ekaputra, Irwan Adi & Husodo, Zaäfri Ananto, 2021. "Are Bitcoin and Ethereum safe-havens for stocks during the COVID-19 pandemic?," Finance Research Letters, Elsevier, vol. 38(C).
    18. Bouri, Elie & Roubaud, David & Shahzad, Syed Jawad Hussain, 2020. "Do Bitcoin and other cryptocurrencies jump together?," The Quarterly Review of Economics and Finance, Elsevier, vol. 76(C), pages 396-409.
    19. Tarchella, Salma & Khalfaoui, Rabeh & Hammoudeh, Shawkat, 2024. "The safe haven, hedging, and diversification properties of oil, gold, and cryptocurrency for the G7 equity markets: Evidence from the pre- and post-COVID-19 periods," Research in International Business and Finance, Elsevier, vol. 67(PB).
    20. Stanisław Drożdż & Ludovico Minati & Paweł Oświȩcimka & Marek Stanuszek & Marcin Wa̧torek, 2019. "Signatures of the Crypto-Currency Market Decoupling from the Forex," Future Internet, MDPI, vol. 11(7), pages 1-18, July.
    21. Urquhart, Andrew & Zhang, Hanxiong, 2019. "Is Bitcoin a hedge or safe haven for currencies? An intraday analysis," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 49-57.
    22. Syed Jawad Hussain Shahzad & Elie Bouri & Sang Hoon Kang & Tareq Saeed, 2021. "Regime specific spillover across cryptocurrencies and the role of COVID-19," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-24, December.
    23. Fernandes, Leonardo H.S. & Araújo, Fernando H.A., 2020. "Taxonomy of commodities assets via complexity-entropy causality plane," Chaos, Solitons & Fractals, Elsevier, vol. 137(C).
    24. Singh, Sanjeet & Bansal, Pooja & Bhardwaj, Nav, 2022. "Correlation between geopolitical risk, economic policy uncertainty, and Bitcoin using partial and multiple wavelet coherence in P5 + 1 nations," Research in International Business and Finance, Elsevier, vol. 63(C).
    25. Fasanya, Ismail O. & Oyewole, Oluwatomisin J. & Oliyide, Johnson A., 2022. "Investors' sentiments and the dynamic connectedness between cryptocurrency and precious metals markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 86(C), pages 347-364.
    26. Syuhada, Khreshna & Hakim, Arief & Suprijanto, Djoko & Muchtadi-Alamsyah, Intan & Arbi, Lukman, 2022. "Is Tether a safe haven of safe haven amid COVID-19? An assessment against Bitcoin and oil using improved measures of risk," Resources Policy, Elsevier, vol. 79(C).
    27. Roman Matkovskyy & Akanksha Jalan & Michael Dowling & Taoufik Bouraoui, 2021. "From bottom ten to top ten: The role of cryptocurrencies in enhancing portfolio return of poorly performing stocks," Post-Print hal-04273124, HAL.
    28. Rubbaniy, Ghulame & Khalid, Ali Awais & Syriopoulos, Konstantinos & Samitas, Aristeidis, 2022. "Safe-haven properties of soft commodities during times of Covid-19," Journal of Commodity Markets, Elsevier, vol. 27(C).
    29. Georgios Bampinas & Theodore Panagiotidis, 2024. "How would the war and the pandemic affect the stock and cryptocurrency cross-market linkages?," Working Paper series 24-01, Rimini Centre for Economic Analysis.
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  24. Karel Janda & Ladislav Krištoufek, 2019. "The Relationship Between Fuel and Food Prices: Methods and Outcomes," Annual Review of Resource Economics, Annual Reviews, vol. 11(1), pages 195-216, October.

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    2. Linjie Wang & Jean‐Paul Chavas & Jian Li, 2024. "Dynamic linkages in agricultural and energy markets: A quantile impulse response approach," Agricultural Economics, International Association of Agricultural Economists, vol. 55(4), pages 639-676, July.
    3. Ji, Qiang & Bouri, Elie & Roubaud, David & Kristoufek, Ladislav, 2019. "Information interdependence among energy, cryptocurrency and major commodity markets," Energy Economics, Elsevier, vol. 81(C), pages 1042-1055.
    4. Zhuo Chen & Bo Yan & Hanwen Kang, 2022. "Dynamic correlation between crude oil and agricultural futures markets," Review of Development Economics, Wiley Blackwell, vol. 26(3), pages 1798-1849, August.
    5. Sergio Adriani David & Claudio M. C. Inácio & José A. Tenreiro Machado, 2019. "Ethanol Prices and Agricultural Commodities: An Investigation of Their Relationship," Mathematics, MDPI, vol. 7(9), pages 1-25, August.
    6. Karel Janda & Ladislav Krištoufek & Barbora Schererová & David Zilberman, 2021. "Price transmission in biofuel-related global agricultural networks," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 67(10), pages 399-408.
    7. Bilgili, Faik & Koçak, Emrah & Kuşkaya, Sevda & Bulut, Ümit, 2020. "Estimation of the co-movements between biofuel production and food prices: A wavelet-based analysis," Energy, Elsevier, vol. 213(C).
    8. Janda, Karel & Kravec, Peter, 2022. "VECM Modelling of the Price Dynamics for Fuels, Agricultural Commodities and Biofuels," EconStor Preprints 259404, ZBW - Leibniz Information Centre for Economics.
    9. Krzysztof Drachal, 2019. "Analysis of Agricultural Commodities Prices with New Bayesian Model Combination Schemes," Sustainability, MDPI, vol. 11(19), pages 1-23, September.
    10. Derick David Quintino & Heloisa Lee Burnquist & Paulo Jorge Silveira Ferreira, 2021. "Carbon Emissions and Brazilian Ethanol Prices: Are They Correlated? An Econophysics Study," Sustainability, MDPI, vol. 13(22), pages 1-18, November.

  25. Kristoufek, Ladislav, 2019. "Are the crude oil markets really becoming more efficient over time? Some new evidence," Energy Economics, Elsevier, vol. 82(C), pages 253-263.
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  26. Ladislav Kristoufek & Paulo Ferreira, 2018. "Capital asset pricing model in Portugal: Evidence from fractal regressions," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 17(3), pages 173-183, November.

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    3. Leonardo Badea & Daniel Ştefan Armeanu & Iulian Panait & Ştefan Cristian Gherghina, 2019. "A Markov Regime Switching Approach towards Assessing Resilience of Romanian Collective Investment Undertakings," Sustainability, MDPI, vol. 11(5), pages 1-24, March.
    4. Tilfani, Oussama & Kristoufek, Ladislav & Ferreira, Paulo & El Boukfaoui, My Youssef, 2022. "Heterogeneity in economic relationships: Scale dependence through the multivariate fractal regression," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 588(C).

  27. Kristoufek, Ladislav, 2018. "On Bitcoin markets (in)efficiency and its evolution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 257-262.

    Cited by:

    1. Aysan, Ahmet Faruk & Demir, Ender & Gozgor, Giray & Lau, Chi Keung Marco, 2019. "Effects of the geopolitical risks on Bitcoin returns and volatility," Research in International Business and Finance, Elsevier, vol. 47(C), pages 511-518.
    2. Ahmed, Walid M.A. & Al Mafrachi, Mustafa, 2021. "Do higher-order realized moments matter for cryptocurrency returns?," International Review of Economics & Finance, Elsevier, vol. 72(C), pages 483-499.
    3. Smaniotto, Emanuelle Nava & Neto, Giacomo Balbinotto, 2022. "Speculative trading in Bitcoin: A Brazilian market evidence," The Quarterly Review of Economics and Finance, Elsevier, vol. 85(C), pages 47-54.
    4. Hussain Shahzad, Syed Jawad & Bouri, Elie & Roubaud, David & Kristoufek, Ladislav, 2020. "Safe haven, hedge and diversification for G7 stock markets: Gold versus bitcoin," Economic Modelling, Elsevier, vol. 87(C), pages 212-224.
    5. Tetsuya Takaishi & Takanori Adachi, 2020. "Market Efficiency, Liquidity, and Multifractality of Bitcoin: A Dynamic Study," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 27(1), pages 145-154, March.
    6. Telli, Şahin & Chen, Hongzhuan, 2020. "Multifractal behavior in return and volatility series of Bitcoin and gold in comparison," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    7. Naeem, Muhammad Abubakr & Bouri, Elie & Peng, Zhe & Shahzad, Syed Jawad Hussain & Vo, Xuan Vinh, 2021. "Asymmetric efficiency of cryptocurrencies during COVID19," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    8. Jinxin Cui & Aktham Maghyereh, 2022. "Time–frequency co-movement and risk connectedness among cryptocurrencies: new evidence from the higher-order moments before and during the COVID-19 pandemic," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-56, December.
    9. Wang, Qiyu & Chong, Terence Tai-Leung, 2021. "Factor pricing of cryptocurrencies," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    10. Cristiana Vaz & Rui Pascoal & Helder Sebastião, 2021. "Price Appreciation and Roughness Duality in Bitcoin: A Multifractal Analysis," Mathematics, MDPI, vol. 9(17), pages 1-18, August.
    11. Hu, Yang & Valera, Harold Glenn A. & Oxley, Les, 2019. "Market efficiency of the top market-cap cryptocurrencies: Further evidence from a panel framework," Finance Research Letters, Elsevier, vol. 31(C), pages 138-145.
    12. Ruan, Qingsong & Meng, Lu & Lv, Dayong, 2021. "Effect of introducing Bitcoin futures on the underlying Bitcoin market efficiency: A multifractal analysis," Chaos, Solitons & Fractals, Elsevier, vol. 153(P1).
    13. Takaishi, Tetsuya, 2020. "Rough volatility of Bitcoin," Finance Research Letters, Elsevier, vol. 32(C).
    14. Telli, Şahin & Chen, Hongzhuan, 2020. "Structural breaks and trend awareness-based interaction in crypto markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 558(C).
    15. Aloosh, Arash & Ouzan, Samuel, 2020. "The psychology of cryptocurrency prices," Finance Research Letters, Elsevier, vol. 33(C).
    16. Éder Pereira & Paulo Ferreira & Derick Quintino, 2022. "Non-Fungible Tokens (NFTs) and Cryptocurrencies: Efficiency and Comovements," FinTech, MDPI, vol. 1(4), pages 1-8, October.
    17. Blau, Benjamin M. & Griffith, Todd G. & Whitby, Ryan J., 2021. "Inflation and Bitcoin: A descriptive time-series analysis," Economics Letters, Elsevier, vol. 203(C).
    18. Tran, Vu Le & Leirvik, Thomas, 2020. "Efficiency in the markets of crypto-currencies," Finance Research Letters, Elsevier, vol. 35(C).
    19. José Antonio Núñez & Mario I Contreras-Valdez & Carlos A Franco-Ruiz, 2019. "Statistical analysis of bitcoin during explosive behavior periods," PLOS ONE, Public Library of Science, vol. 14(3), pages 1-22, March.
    20. Kristjanpoller, Werner & Bouri, Elie & Takaishi, Tetsuya, 2020. "Cryptocurrencies and equity funds: Evidence from an asymmetric multifractal analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    21. Ahmed, Shaker & Grobys, Klaus & Sapkota, Niranjan, 2020. "Profitability of technical trading rules among cryptocurrencies with privacy function," Finance Research Letters, Elsevier, vol. 35(C).
    22. Aggarwal, Divya & Chandrasekaran, Shabana & Annamalai, Balamurugan, 2020. "A complete empirical ensemble mode decomposition and support vector machine-based approach to predict Bitcoin prices," Journal of Behavioral and Experimental Finance, Elsevier, vol. 27(C).
    23. Nie, Chun-Xiao, 2020. "Correlation dynamics in the cryptocurrency market based on dimensionality reduction analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 554(C).
    24. Zargar, Faisal Nazir & Kumar, Dilip, 2019. "Long range dependence in the Bitcoin market: A study based on high-frequency data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 625-640.
    25. Tetsuya Takaishi & Takanori Adachi, 2019. "Market efficiency, liquidity, and multifractality of Bitcoin: A dynamic study," Papers 1902.09253, arXiv.org.
    26. Li, Mu-Yao & Cai, Qing & Gu, Gao-Feng & Zhou, Wei-Xing, 2019. "Exponentially decayed double power-law distribution of Bitcoin trade sizes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    27. Chu, Jeffrey & Chan, Stephen & Zhang, Yuanyuan, 2023. "An analysis of the return–volume relationship in decentralised finance (DeFi)," International Review of Economics & Finance, Elsevier, vol. 85(C), pages 236-254.
    28. Helder Miguel Correia Virtuoso Sebastião & Paulo José Osório Rupino Da Cunha & Pedro Manuel Cortesão Godinho, 2021. "Cryptocurrencies and blockchain. Overview and future perspectives," International Journal of Economics and Business Research, Inderscience Enterprises Ltd, vol. 21(3), pages 305-342.
    29. Majid Mirzaee Ghazani & Mohammad Ali Jafari, 2021. "Cryptocurrencies, gold, and WTI crude oil market efficiency: a dynamic analysis based on the adaptive market hypothesis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-26, December.
    30. Grobys, Klaus, 2023. "A Fractal and Comparative View of the Memory of Bitcoin and S&P 500 Returns," Research in International Business and Finance, Elsevier, vol. 66(C).
    31. Walther, Thomas & Klein, Tony & Bouri, Elie, 2019. "Exogenous drivers of Bitcoin and Cryptocurrency volatility – A mixed data sampling approach to forecasting," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 63(C).
    32. Köchling, Gerrit & Müller, Janis & Posch, Peter N., 2019. "Does the introduction of futures improve the efficiency of Bitcoin?," Finance Research Letters, Elsevier, vol. 30(C), pages 367-370.
    33. Antonakakis, Nikolaos & Chatziantoniou, Ioannis & Gabauer, David, 2019. "Cryptocurrency market contagion: Market uncertainty, market complexity, and dynamic portfolios," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 61(C), pages 37-51.
    34. Ammy-Driss, Ayoub & Garcin, Matthieu, 2023. "Efficiency of the financial markets during the COVID-19 crisis: Time-varying parameters of fractional stable dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    35. Ma, Chaoqun & Tian, Yonggang & Hsiao, Shisong & Deng, Liurui, 2022. "Monetary policy shocks and Bitcoin prices," Research in International Business and Finance, Elsevier, vol. 62(C).
    36. Kilic, Emre & Yavuz, Ersin & Pazarci, Sevket & Kar, Asim, 2023. "Analyzing the efficient market hypothesis with asymmetric persistence in cryptocurrencies: Insights from the Fourier non-linear quantile unit root approach," Finance Research Letters, Elsevier, vol. 58(PC).
    37. Ángeles Cebrián-Hernández & Enrique Jiménez-Rodríguez, 2021. "Modeling of the Bitcoin Volatility through Key Financial Environment Variables: An Application of Conditional Correlation MGARCH Models," Mathematics, MDPI, vol. 9(3), pages 1-16, January.
    38. Köchling, Gerrit & Müller, Janis & Posch, Peter N., 2019. "Price delay and market frictions in cryptocurrency markets," Economics Letters, Elsevier, vol. 174(C), pages 39-41.
    39. Kristoufek, Ladislav, 2019. "Is the Bitcoin price dynamics economically reasonable? Evidence from fundamental laws," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    40. Park, Sangjin & Jang, Kwahngsoo & Yang, Jae-Suk, 2021. "Information flow between bitcoin and other financial assets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    41. Bouazizi, Tarek & Galariotis, Emilios & Guesmi, Khaled & Makrychoriti, Panagiota, 2023. "Investigating the nature of interaction between crypto-currency and commodity markets," International Review of Financial Analysis, Elsevier, vol. 88(C).
    42. Duc Huynh, Toan Luu & Burggraf, Tobias & Wang, Mei, 2020. "Gold, platinum, and expected Bitcoin returns," Journal of Multinational Financial Management, Elsevier, vol. 56(C).
    43. Flori, Andrea, 2019. "News and subjective beliefs: A Bayesian approach to Bitcoin investments," Research in International Business and Finance, Elsevier, vol. 50(C), pages 336-356.
    44. Bajra, Ujkan Q. & Aliu, Florin, 2023. "Deciphering the cryptocurrency conundrum: Investigating speculative characteristics and volatility," Finance Research Letters, Elsevier, vol. 58(PC).
    45. Sinda Hadhri, 2023. "How does Bitcoin react to economic discomfort? Evidence from the economic misery index," Economics Bulletin, AccessEcon, vol. 43(3), pages 1235-1253.
    46. Lennart Ante, 2020. "A place next to Satoshi: foundations of blockchain and cryptocurrency research in business and economics," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(2), pages 1305-1333, August.
    47. Efe Caglar Cagli & Pinar Evrim Mandaci, 2021. "Information transmission between bitcoin derivatives and spot markets: high-frequency causality analysis with Fourier approximation," Economics and Business Letters, Oviedo University Press, vol. 10(4), pages 394-402.
    48. Li, Xiao & Wu, Ruoxi & Wang, Chen, 2024. "Impacts of bitcoin on monetary system: Is China's bitcoin ban necessary?," Research in International Business and Finance, Elsevier, vol. 69(C).
    49. Dimpfl, Thomas & Peter, Franziska J., 2019. "Group transfer entropy with an application to cryptocurrencies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 543-551.
    50. Nils Bundi & Marc Wildi, 2019. "Bitcoin and market-(in)efficiency: a systematic time series approach," Digital Finance, Springer, vol. 1(1), pages 47-65, November.
    51. T. Takaishi, 2021. "Power-Law Return-Volatility Cross Correlations of Bitcoin," Papers 2102.08187, arXiv.org.
    52. Cynthia Weiyi Cai & Rui Xue & Bi Zhou, 2023. "Cryptocurrency puzzles: a comprehensive review and re-introduction," Journal of Accounting Literature, Emerald Group Publishing Limited, vol. 46(1), pages 26-50, June.
    53. Al-Shboul, Mohammad & Assaf, Ata & Mokni, Khaled, 2023. "Does economic policy uncertainty drive the dynamic spillover among traditional currencies and cryptocurrencies? The role of the COVID-19 pandemic," Research in International Business and Finance, Elsevier, vol. 64(C).
    54. Ferreira, Paulo & Kristoufek, Ladislav & Pereira, Eder Johnson de Area Leão, 2020. "DCCA and DMCA correlations of cryptocurrency markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    55. Zhang, Wei & Wang, Pengfei & Li, Xiao & Shen, Dehua, 2018. "Quantifying the cross-correlations between online searches and Bitcoin market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 657-672.
    56. Grobys, Klaus & Ahmed, Shaker & Sapkota, Niranjan, 2020. "Technical trading rules in the cryptocurrency market," Finance Research Letters, Elsevier, vol. 32(C).
    57. Abakah, Emmanuel Joel Aikins & Wali Ullah, GM & Adekoya, Oluwasegun B. & Osei Bonsu, Christiana & Abdullah, Mohammad, 2023. "Blockchain market and eco-friendly financial assets: Dynamic price correlation, connectedness and spillovers with portfolio implications," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 218-243.
    58. Karen Balladares & José Pedro Ramos-Requena & Juan Evangelista Trinidad-Segovia & Miguel Angel Sánchez-Granero, 2021. "Statistical Arbitrage in Emerging Markets: A Global Test of Efficiency," Mathematics, MDPI, vol. 9(2), pages 1-20, January.
    59. Assaf, Ata & Kristoufek, Ladislav & Demir, Ender & Kumar Mitra, Subrata, 2021. "Market efficiency in the art markets using a combination of long memory, fractal dimension, and approximate entropy measures," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 71(C).
    60. Zhang, Wei & Wang, Pengfei & Li, Xiao & Shen, Dehua, 2018. "The inefficiency of cryptocurrency and its cross-correlation with Dow Jones Industrial Average," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 658-670.
    61. Pengfei Wang & Wei Zhang & Xiao Li & Dehua Shen, 2019. "Trading volume and return volatility of Bitcoin market: evidence for the sequential information arrival hypothesis," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(2), pages 377-418, June.
    62. Manahov, Viktor & Urquhart, Andrew, 2021. "The efficiency of Bitcoin: A strongly typed genetic programming approach to smart electronic Bitcoin markets," International Review of Financial Analysis, Elsevier, vol. 73(C).
    63. Donglian Ma & Hisashi Tanizaki, 2022. "Intraday patterns of price clustering in Bitcoin," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-25, December.
    64. Łęt Blanka & Sobański Konrad & Świder Wojciech & Włosik Katarzyna, 2022. "Is the cryptocurrency market efficient? Evidence from an analysis of fundamental factors for Bitcoin and Ethereum," International Journal of Management and Economics, Warsaw School of Economics, Collegium of World Economy, vol. 58(4), pages 351-370, December.
    65. Telli, Şahin & Chen, Hongzhuan, 2021. "Multifractal behavior relationship between crypto markets and Wikipedia-Reddit online platforms," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    66. Palazzi, Rafael Baptista & Júnior, Gerson de Souza Raimundo & Klotzle, Marcelo Cabus, 2021. "The dynamic relationship between bitcoin and the foreign exchange market: A nonlinear approach to test causality between bitcoin and currencies," Finance Research Letters, Elsevier, vol. 42(C).
    67. Abakah, Emmanuel Joel Aikins & Gil-Alana, Luis Alberiko & Madigu, Godfrey & Romero-Rojo, Fatima, 2020. "Volatility persistence in cryptocurrency markets under structural breaks," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 680-691.
    68. Alaoui, Marwane El & Bouri, Elie & Roubaud, David, 2019. "Bitcoin price–volume: A multifractal cross-correlation approach," Finance Research Letters, Elsevier, vol. 31(C).
    69. Tetsuya Takaishi, 2021. "Time-varying properties of asymmetric volatility and multifractality in Bitcoin," Papers 2102.07425, arXiv.org.
    70. Chaim, Pedro & Laurini, Márcio P., 2019. "Nonlinear dependence in cryptocurrency markets," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 32-47.
    71. Aslam, Faheem & Memon, Bilal Ahmed & Hunjra, Ahmed Imran & Bouri, Elie, 2023. "The dynamics of market efficiency of major cryptocurrencies," Global Finance Journal, Elsevier, vol. 58(C).
    72. Andrea Flori, 2019. "Cryptocurrencies In Finance: Review And Applications," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 22(05), pages 1-22, August.

  28. Ferreira, Paulo & Kristoufek, Ladislav, 2017. "What is new about covered interest parity condition in the European Union? Evidence from fractal cross-correlation regressions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 554-566.

    Cited by:

    1. Ferreira, Paulo & Kristoufek, Ladislav, 2020. "Uncovered interest rate parity through the lens of fractal methods: Evidence from the European Union," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 553(C).
    2. Barreto, Ikaro Daniel de Carvalho & Dore, Luiz Henrique & Stosic, Tatijana & Stosic, Borko D., 2021. "Extending DFA-based multiple linear regression inference: Application to acoustic impedance models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 582(C).
    3. Ladislav Kristoufek & Paulo Ferreira, 2018. "Capital asset pricing model in Portugal: Evidence from fractal regressions," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 17(3), pages 173-183, November.
    4. Paulo Ferreira & Éder Pereira, 2019. "The impact of the Brexit referendum on British and European Union bank shares: a cross-correlation analysis with national indices," Economics Bulletin, AccessEcon, vol. 39(1), pages 335-346.
    5. Tilfani, Oussama & Kristoufek, Ladislav & Ferreira, Paulo & El Boukfaoui, My Youssef, 2022. "Heterogeneity in economic relationships: Scale dependence through the multivariate fractal regression," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 588(C).
    6. Kristoufek, Ladislav, 2018. "Fractality in market risk structure: Dow Jones Industrial components case," Chaos, Solitons & Fractals, Elsevier, vol. 110(C), pages 69-75.
    7. Grillini, Stefano & Ozkan, Aydin & Sharma, Abhijit & Al Janabi, Mazin A.M., 2019. "Pricing of time-varying illiquidity within the Eurozone: Evidence using a Markov switching liquidity-adjusted capital asset pricing model," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 145-158.
    8. Thiago B. Murari & Aloisio S. Nascimento Filho & Eder J.A.L. Pereira & Paulo Ferreira & Sergio Pitombo & Hernane B.B. Pereira & Alex A.B. Santos & Marcelo A. Moret, 2019. "Comparative Analysis between Hydrous Ethanol and Gasoline C Pricing in Brazilian Retail Market," Sustainability, MDPI, vol. 11(17), pages 1-12, August.
    9. da Silva Filho, A.M. & Zebende, G.F. & de Castro, A.P.N. & Guedes, E.F., 2021. "Statistical test for Multiple Detrended Cross-Correlation Coefficient," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 562(C).
    10. Adewuyi, Adeolu O. & Ogebe, Joseph O., 2019. "The validity of uncovered interest parity: Evidence from african members and non-member of the organisation of petroleum exporting countries (OPEC)," Economic Modelling, Elsevier, vol. 82(C), pages 229-249.

  29. Kristoufek, Ladislav, 2017. "Has global warming modified the relationship between sunspot numbers and global temperatures?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 351-358.

    Cited by:

    1. Sumarmi Sumarmi & Purwanto Purwanto & Syamsul Bachri, 2021. "Spatial Analysis of Mangrove Forest Management to Reduce Air Temperature and CO 2 Emissions," Sustainability, MDPI, vol. 13(14), pages 1-14, July.
    2. Slavica Malinović-Milićević & Milan M. Radovanović & Sonja D. Radenković & Yaroslav Vyklyuk & Boško Milovanović & Ana Milanović Pešić & Milan Milenković & Vladimir Popović & Marko Petrović & Petro Syd, 2023. "Application of Solar Activity Time Series in Machine Learning Predictive Modeling of Precipitation-Induced Floods," Mathematics, MDPI, vol. 11(4), pages 1-20, February.

  30. Kristoufek, Ladislav & Vosvrda, Miloslav, 2016. "Gold, currencies and market efficiency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 449(C), pages 27-34.
    See citations under working paper version above.
  31. Ondrej Filip & Karel Janda & Ladislav Kristoufek & David Zilberman, 2016. "Dynamics and evolution of the role of biofuels in global commodity and financial markets," Nature Energy, Nature, vol. 1(12), pages 1-9, December.

    Cited by:

    1. Yosra Ghabri & Luu Duc Toan Huynh & Muhammad Ali Nasir, 2024. "Volatility spillovers, hedging and safe‐havens under pandemics: All that glitters is not gold!," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(2), pages 1318-1344, April.
    2. Tiwari, Aviral Kumar & Nasreen, Samia & Shahbaz, Muhammad & Hammoudeh, Shawkat, 2020. "Time-frequency causality and connectedness between international prices of energy, food, industry, agriculture and metals," Energy Economics, Elsevier, vol. 85(C).
    3. Heckelei, T. & Amrouk, E.M. & Grosche, S., 2018. "International interdependence between cash crop and staple food futures price indices: A wavelet-BEKK-GARCH assessment," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277376, International Association of Agricultural Economists.
    4. Karel Janda & Ladislav Krištoufek, 2019. "The Relationship Between Fuel and Food Prices: Methods and Outcomes," Annual Review of Resource Economics, Annual Reviews, vol. 11(1), pages 195-216, October.
    5. Radmila Krkošková, 2020. "Relationship Between the Brent Oil Price and the US Dollar Exchange Rate," Prague Economic Papers, Prague University of Economics and Business, vol. 2020(2), pages 187-206.
    6. Manuel Monge & Luis A. Gil-Alana, 2020. "The Lithium Industry and Analysis of the Beta Term Structure of Oil Companies," Risks, MDPI, vol. 8(4), pages 1-17, December.
    7. Paulo Ferreira & Éder J.A.L. Pereira & Hernane B.B. Pereira, 2020. "From Big Data to Econophysics and Its Use to Explain Complex Phenomena," JRFM, MDPI, vol. 13(7), pages 1-10, July.
    8. Flori, Andrea & Pammolli, Fabio & Spelta, Alessandro, 2021. "Commodity prices co-movements and financial stability: A multidimensional visibility nexus with climate conditions," Journal of Financial Stability, Elsevier, vol. 54(C).
    9. Ondrej Filip & Karel Janda & Ladislav Kristoufek & David Zilberman, 2017. "Food versus Fuel: An Updated and Expanded Evidence," Working Papers IES 2017/26, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Nov 2017.
    10. Ji, Qiang & Bouri, Elie & Roubaud, David & Kristoufek, Ladislav, 2019. "Information interdependence among energy, cryptocurrency and major commodity markets," Energy Economics, Elsevier, vol. 81(C), pages 1042-1055.
    11. Zhou, Wei & Chen, Yan & Chen, Jin, 2022. "Risk spread in multiple energy markets: Extreme volatility spillover network analysis before and during the COVID-19 pandemic," Energy, Elsevier, vol. 256(C).
    12. Abid, Fathi & Kaffel, Bilel, 2018. "Time–frequency wavelet analysis of the interrelationship between the global macro assets and the fear indexes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1028-1045.
    13. Caporin, Massimiliano & Naeem, Muhammad Abubakr & Arif, Muhammad & Hasan, Mudassar & Vo, Xuan Vinh & Hussain Shahzad, Syed Jawad, 2021. "Asymmetric and time-frequency spillovers among commodities using high-frequency data," Resources Policy, Elsevier, vol. 70(C).
    14. Fathi Abid & Bilel Kaffel, 2018. "The extent of virgin olive-oil prices’ distribution revealing the behavior of market speculators," Review of Quantitative Finance and Accounting, Springer, vol. 50(2), pages 561-590, February.
    15. Karel Janda & Ladislav Kristoufek, 2019. "The relationship between fuel and food prices: Methods, outcomes, and lessons for commodity price risk management," CAMA Working Papers 2019-20, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    16. Pereira, Hernane Borges de Barros & Rosário, Raphael Silva do & Pereira, Eder Johnson de Area Leão & Moreira, Davidson Martins & Ferreira, Paulo & Miranda, José Garcia Vivas, 2022. "Network dynamic and stability on European Union," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 587(C).
    17. Mensi, Walid & Tiwari, Aviral & Bouri, Elie & Roubaud, David & Al-Yahyaee, Khamis H., 2017. "The dependence structure across oil, wheat, and corn: A wavelet-based copula approach using implied volatility indexes," Energy Economics, Elsevier, vol. 66(C), pages 122-139.
    18. Benes, Ondrej & Janda, Karel, 2022. "Environmental Dimensions of Biofuels," EconStor Preprints 259403, ZBW - Leibniz Information Centre for Economics.
    19. Zhang, Yali & Shang, Pengjian, 2019. "Multivariate multiscale distribution entropy of financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 72-80.
    20. Ondřej Filip & Karel Janda & Ladislav Krištoufek, 2018. "Ceny biopaliv a souvisejících komodit: analýza s použitím metod minimální kostry grafu a hierarchických stromů [Prices of Biofuels and Related Commodities: an Analysis Using Methods of Minimum Span," Politická ekonomie, Prague University of Economics and Business, vol. 2018(2), pages 218-239.
    21. Janda, Karel & Kravec, Peter, 2022. "VECM Modelling of the Price Dynamics for Fuels, Agricultural Commodities and Biofuels," EconStor Preprints 259404, ZBW - Leibniz Information Centre for Economics.

  32. Kristoufek, Ladislav & Lunackova, Petra, 2015. "Rockets and feathers meet Joseph: Reinvestigating the oil–gasoline asymmetry on the international markets," Energy Economics, Elsevier, vol. 49(C), pages 1-8.
    See citations under working paper version above.
  33. Kristoufek, Ladislav, 2015. "Can the bivariate Hurst exponent be higher than an average of the separate Hurst exponents?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 431(C), pages 124-127.

    Cited by:

    1. Qin, Jing & Ge, Jintian & Lu, Xinsheng, 2018. "The effectiveness of the monetary policy in China: New evidence from long-range cross-correlation analysis and the components of multifractality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 1026-1037.
    2. Ladislav Kristoufek, 2016. "Power-law cross-correlations estimation under heavy tails," Papers 1602.05385, arXiv.org, revised Apr 2016.
    3. Ladislav Kristoufek, 2018. "Power-law cross-correlations: Issues, solutions and future challenges," Papers 1806.01616, arXiv.org.
    4. Hasan, Rashid & Mohammed Salim, M., 2017. "Power law cross-correlations between price change and volume change of Indian stocks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 620-631.

  34. Kristoufek, Ladislav, 2015. "On the interplay between short and long term memory in the power-law cross-correlations setting," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 421(C), pages 218-222.
    See citations under working paper version above.
  35. Ladislav Kristoufek, 2015. "What Are the Main Drivers of the Bitcoin Price? Evidence from Wavelet Coherence Analysis," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-15, April.
    See citations under working paper version above.
  36. Kristoufek, Ladislav, 2015. "Finite sample properties of power-law cross-correlations estimators," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 513-525.
    See citations under working paper version above.
  37. Jaroslav Pavlicek & Ladislav Kristoufek, 2015. "Nowcasting Unemployment Rates with Google Searches: Evidence from the Visegrad Group Countries," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-11, May.
    See citations under working paper version above.
  38. Paulus, Michal & Kristoufek, Ladislav, 2015. "Worldwide clustering of the corruption perception," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 351-358.
    See citations under working paper version above.
  39. Kristoufek, Ladislav, 2015. "Power-law correlations in finance-related Google searches, and their cross-correlations with volatility and traded volume: Evidence from the Dow Jones Industrial components," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 194-205.
    See citations under working paper version above.
  40. Kristoufek, Ladislav, 2014. "Leverage effect in energy futures," Energy Economics, Elsevier, vol. 45(C), pages 1-9.
    See citations under working paper version above.
  41. Kristoufek, Ladislav, 2014. "Detrending moving-average cross-correlation coefficient: Measuring cross-correlations between non-stationary series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 406(C), pages 169-175.
    See citations under working paper version above.
  42. Štěpán Chrz & Karel Janda & Ladislav Krištoufek, 2014. "Modelování provázanosti trhů potravin, biopaliv a fosilních paliv [Modeling Interconnections within Food, Biofuel, and Fossil Fuel Markets]," Politická ekonomie, Prague University of Economics and Business, vol. 2014(1), pages 117-140.

    Cited by:

    1. Piroli, Giuseppe & Rajcaniova, Miroslava & Ciaian, Pavel & Kancs, d׳Artis, 2015. "From a rise in B to a fall in C? SVAR analysis of environmental impact of biofuels," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 921-930.
    2. Janda, Karel & Krska, Stepan & Prusa, Jan, 2014. "Odhad nákladů na podporu české fotovoltaické energie [The Estimation of the Cost of Promotion of the Czech Photovoltaic Energy]," MPRA Paper 54108, University Library of Munich, Germany.

  43. Ladislav Kristoufek & Miloslav Vosvrda, 2014. "Measuring capital market efficiency: long-term memory, fractal dimension and approximate entropy," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 87(7), pages 1-9, July.
    See citations under working paper version above.
  44. Kristoufek, Ladislav & Vosvrda, Miloslav, 2014. "Commodity futures and market efficiency," Energy Economics, Elsevier, vol. 42(C), pages 50-57.
    See citations under working paper version above.
  45. Kristoufek, Ladislav, 2014. "Measuring correlations between non-stationary series with DCCA coefficient," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 402(C), pages 291-298.
    See citations under working paper version above.
  46. Vacha, Lukas & Janda, Karel & Kristoufek, Ladislav & Zilberman, David, 2013. "Time–frequency dynamics of biofuel–fuel–food system," Energy Economics, Elsevier, vol. 40(C), pages 233-241.
    See citations under working paper version above.
  47. Kristoufek, Ladislav, 2013. "Mixed-correlated ARFIMA processes for power-law cross-correlations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(24), pages 6484-6493.
    See citations under working paper version above.
  48. Ladislav KRISTOUFEK & Petra LUNACKOVA, 2013. "Long-term Memory in Electricity Prices: Czech Market Evidence," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(5), pages 407-424, November.
    See citations under working paper version above.
  49. Kristoufek, Ladislav & Vosvrda, Miloslav, 2013. "Measuring capital market efficiency: Global and local correlations structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(1), pages 184-193.
    See citations under working paper version above.
  50. Ladislav Kristoufek & Karel Janda & David Zilberman, 2013. "Regime-dependent topological properties of biofuels networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 86(2), pages 1-12, February.
    See citations under working paper version above.
  51. Kristoufek, Ladislav & Janda, Karel & Zilberman, David, 2012. "Correlations between biofuels and related commodities before and during the food crisis: A taxonomy perspective," Energy Economics, Elsevier, vol. 34(5), pages 1380-1391.

    Cited by:

    1. Yosra Ghabri & Luu Duc Toan Huynh & Muhammad Ali Nasir, 2024. "Volatility spillovers, hedging and safe‐havens under pandemics: All that glitters is not gold!," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(2), pages 1318-1344, April.
    2. Muhammad Abubakr Naeem & Saqib Farid & Safwan Mohd Nor & Syed Jawad Hussain Shahzad, 2021. "Spillover and Drivers of Uncertainty among Oil and Commodity Markets," Mathematics, MDPI, vol. 9(4), pages 1-26, February.
    3. Karikallio, Hanna, 2015. "Cross-commodity Price Transmission and Integration of the EU Livestock Market of Pork and Beef: Panel Time-series Approach," 2015 Conference, August 9-14, 2015, Milan, Italy 211832, International Association of Agricultural Economists.
    4. Lukas Vacha & Karel Janda & Ladislav Kristoufek & David Zilberman, 2012. "Time-Frequency Dynamics of Biofuels-Fuels-Food System," Papers 1209.0900, arXiv.org.
    5. Hao, Na & Colson, Gregory & Karali, Berna & Wetzstein, Michael E., 2013. "Food before Biodiesel Fuel?," 2013 Annual Meeting, February 2-5, 2013, Orlando, Florida 143078, Southern Agricultural Economics Association.
    6. Ahmed Ghorbel & Wajdi Hamma & Anis Jarboui, 2017. "Dependence between oil and commodities markets using time-varying Archimedean copulas and effectiveness of hedging strategies," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(9), pages 1509-1542, July.
    7. Ladislav Kristoufek & Karel Janda & David Zilberman, 2013. "Non-linear Price Transmission between Biofuels, Fuels and Food Commodities," CERGE-EI Working Papers wp481, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    8. Gautier Marti & Frank Nielsen & Miko{l}aj Bi'nkowski & Philippe Donnat, 2017. "A review of two decades of correlations, hierarchies, networks and clustering in financial markets," Papers 1703.00485, arXiv.org, revised Nov 2020.
    9. Kantar, Ersin & Keskin, Mustafa, 2013. "The relationships between electricity consumption and GDP in Asian countries, using hierarchical structure methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(22), pages 5678-5684.
    10. Drabik, Dusan & de Gorter, Harry & Timilsina, Govinda R., 2014. "The effect of biodiesel policies on world biodiesel and oilseed prices," Energy Economics, Elsevier, vol. 44(C), pages 80-88.
    11. M. Thenmozhi & Shipra Maurya, 2020. "Crude Oil Volatility Transmission Across Food Commodity Markets: A Multivariate BEKK-GARCH Approach," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 20(2), pages 131-164, August.
    12. Yoon, Seong-Min, 2022. "On the interdependence between biofuel, fossil fuel and agricultural food prices: Evidence from quantile tests," Renewable Energy, Elsevier, vol. 199(C), pages 536-545.
    13. Tiwari, Aviral Kumar & Nasreen, Samia & Shahbaz, Muhammad & Hammoudeh, Shawkat, 2020. "Time-frequency causality and connectedness between international prices of energy, food, industry, agriculture and metals," Energy Economics, Elsevier, vol. 85(C).
    14. Nazlioglu, Saban & Erdem, Cumhur & Soytas, Ugur, 2013. "Volatility spillover between oil and agricultural commodity markets," Energy Economics, Elsevier, vol. 36(C), pages 658-665.
    15. Feng, Huan & He, Zhixia & Zhang, Bo & Chen, Haitao & Wang, Qian & Kandasamy, Sabariswaran, 2019. "Synergistic bio-oil production from hydrothermal co-liquefaction of Spirulina platensis and α-Cellulose," Energy, Elsevier, vol. 174(C), pages 1283-1291.
    16. Pavla BLAHOVA & Karel JANDA & Ladislav KRISTOUFEK, 2014. "The perspectives for genetically modified cellulosic biofuels in the Central European conditions," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 60(6), pages 247-259.
    17. Shahzad, Syed Jawad Hussain & Hernandez, Jose Arreola & Al-Yahyaee, Khamis Hamed & Jammazi, Rania, 2018. "Asymmetric risk spillovers between oil and agricultural commodities," Energy Policy, Elsevier, vol. 118(C), pages 182-198.
    18. Niu, Hongli & Hu, Ziang, 2021. "Information transmission and entropy-based network between Chinese stock market and commodity futures market," Resources Policy, Elsevier, vol. 74(C).
    19. Karel Janda & Ladislav Krištoufek, 2019. "The Relationship Between Fuel and Food Prices: Methods and Outcomes," Annual Review of Resource Economics, Annual Reviews, vol. 11(1), pages 195-216, October.
    20. Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2013. "Biofuels and Food Prices: Searching for the Causal Link," Working Papers 239, University of Milano-Bicocca, Department of Economics, revised Mar 2013.
    21. Manuel Monge & Luis A. Gil-Alana, 2020. "The Lithium Industry and Analysis of the Beta Term Structure of Oil Companies," Risks, MDPI, vol. 8(4), pages 1-17, December.
    22. Ladislav Kristoufek & Karel Janda & David Zilberman, 2012. "Mutual Responsiveness of Biofuels, Fuels and Food Prices," CAMA Working Papers 2012-38, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    23. Paulus, Michal & Kristoufek, Ladislav, 2015. "Worldwide clustering of the corruption perception," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 351-358.
    24. Maryam Ahmadi & Niaz Bashiri Behmiri & Matteo Manera, 2015. "How is Volatility in Commodity Markets Linked to Oil Price Shocks?," Working Papers 2015.101, Fondazione Eni Enrico Mattei.
    25. Ladislav Kristoufek & Karel Janda & David Zilberman, 2013. "Regime-dependent topological properties of biofuels networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 86(2), pages 1-12, February.
    26. Ouyang, Ruolan & Zhuang, Chengkai & Wang, Tingting & Zhang, Xuan, 2022. "Network analysis of risk transmission among energy futures: An industrial chain perspective," Energy Economics, Elsevier, vol. 107(C).
    27. Leong, Soon Heng, 2021. "Global crude oil and the Chinese oil-intensive sectors: A comprehensive causality study," Energy Economics, Elsevier, vol. 103(C).
    28. Sima Siami-Namini, 2019. "Volatility Transmission Among Oil Price, Exchange Rate and Agricultural Commodities Prices," Applied Economics and Finance, Redfame publishing, vol. 6(4), pages 41-61, July.
    29. Ludwik Wicki & Kaspars Naglis-Liepa & Tadeusz Filipiak & Andrzej Parzonko & Aleksandra Wicka, 2022. "Is the Production of Agricultural Biogas Environmentally Friendly? Does the Structure of Consumption of First- and Second-Generation Raw Materials in Latvia and Poland Matter?," Energies, MDPI, vol. 15(15), pages 1-16, August.
    30. Han-Yu Zhu & Peng-Fei Dai & Wei-Xing Zhou, 2024. "Uncovering the Sino-US dynamic risk spillovers effects: Evidence from agricultural futures markets," Papers 2403.01745, arXiv.org.
    31. Štěpán Chrz & Karel Janda & Ladislav Krištoufek, 2014. "Modelování provázanosti trhů potravin, biopaliv a fosilních paliv [Modeling Interconnections within Food, Biofuel, and Fossil Fuel Markets]," Politická ekonomie, Prague University of Economics and Business, vol. 2014(1), pages 117-140.
    32. Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2013. "Food versus Fuel: Causality and Predictability in Distribution," IEFE Working Papers 56, IEFE, Center for Research on Energy and Environmental Economics and Policy, Universita' Bocconi, Milano, Italy.
    33. Serra, Teresa & Zilberman, David, 2013. "Biofuel-related price transmission literature: A review," Energy Economics, Elsevier, vol. 37(C), pages 141-151.
    34. Pavel Ciaian & d'Artis Kancs & Miroslava Rajcaniova, 2012. "Bioenergy and Global Land Use Change," EERI Research Paper Series EERI_RP_2012_12, Economics and Econometrics Research Institute (EERI), Brussels.
    35. Bernhard Brümmer & Olaf Korn & Kristina Schlüßler & Tinoush Jamali Jaghdani, 2016. "Volatility in Oilseeds and Vegetable Oils Markets: Drivers and Spillovers," Journal of Agricultural Economics, Wiley Blackwell, vol. 67(3), pages 685-705, September.
    36. Flori, Andrea & Pammolli, Fabio & Spelta, Alessandro, 2021. "Commodity prices co-movements and financial stability: A multidimensional visibility nexus with climate conditions," Journal of Financial Stability, Elsevier, vol. 54(C).
    37. de Araujo, Fernando Henrique Antunes & Bejan, Lucian & Stosic, Borko & Stosic, Tatijana, 2020. "An analysis of Brazilian agricultural commodities using permutation – information theory quantifiers: The influence of food crisis," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    38. Matesanz, David & Ortega, Guillermo J., 2015. "Sovereign public debt crisis in Europe. A network analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 756-766.
    39. Ondrej Filip & Karel Janda & Ladislav Kristoufek & David Zilberman, 2017. "Food versus Fuel: An Updated and Expanded Evidence," Working Papers IES 2017/26, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Nov 2017.
    40. Ji, Qiang & Bouri, Elie & Roubaud, David & Kristoufek, Ladislav, 2019. "Information interdependence among energy, cryptocurrency and major commodity markets," Energy Economics, Elsevier, vol. 81(C), pages 1042-1055.
    41. Albarracín E., Eva Susana & Gamboa, Juan C. Rodríguez & Marques, Elaine C.M. & Stosic, Tatijana, 2019. "Complexity analysis of Brazilian agriculture and energy market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 933-941.
    42. Dániel Fróna & János Szenderák & Mónika Harangi-Rákos, 2019. "The Challenge of Feeding the World," Sustainability, MDPI, vol. 11(20), pages 1-18, October.
    43. Lahmiri, Salim, 2016. "Clustering of Casablanca stock market based on hurst exponent estimates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 310-318.
    44. Rajcaniova, Miroslava & Drabik, Dusan & Ciaian, Pavel, 2013. "How policies affect international biofuel price linkages," Energy Policy, Elsevier, vol. 59(C), pages 857-865.
    45. Lucotte, Yannick, 2016. "Co-movements between crude oil and food prices: A post-commodity boom perspective," Economics Letters, Elsevier, vol. 147(C), pages 142-147.
    46. Mohcine Bakhat & Klaas WŸrzburg, 2013. "Price Relationships of Crude Oil and Food Commodities," Working Papers fa06-2013, Economics for Energy.
    47. David Roubaud & Bouri Elie & Qiang Ji, 2018. "Dynamic network of implied volatility transmission among US equities, strategic commodities, and BRICS equities," Post-Print hal-02081506, HAL.
    48. Karel Janda & Ladislav Kristoufek, 2019. "The relationship between fuel and food prices: Methods, outcomes, and lessons for commodity price risk management," CAMA Working Papers 2019-20, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    49. Guellil, Mohammed Seghir & Benbouziane, Mohamed, 2018. "Volatility Linkages between Agricultural Commodity Prices, Oil Prices and Real USD Exchange Rate || Vínculos de volatilidad entre precios de productos agrícolas, precios del petróleo y tipo de cambio ," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 26(1), pages 71-83, Diciembre.
    50. Wang, Gang-Jin & Xie, Chi, 2015. "Correlation structure and dynamics of international real estate securities markets: A network perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 176-193.
    51. Dorel Dusmanescu & Jean Andrei & Gheorghe H. Popescu & Elvira Nica & Mirela Panait, 2016. "Heuristic Methodology for Estimating the Liquid Biofuel Potential of a Region," Energies, MDPI, vol. 9(9), pages 1-19, August.
    52. Fernandez-Perez, Adrian & Frijns, Bart & Tourani-Rad, Alireza, 2016. "Contemporaneous interactions among fuel, biofuel and agricultural commodities," Energy Economics, Elsevier, vol. 58(C), pages 1-10.
    53. Ladislav Kristoufek & Karel Janda & David Zilberman, 2015. "Co-movements of Ethanol Related Prices: Evidence from Brazil and the USA," CAMA Working Papers 2015-11, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    54. Hassouneh, Islam & Serra, Teresa & Goodwin, Barry K. & Gil, José M., 2012. "Non-parametric and parametric modeling of biodiesel, sunflower oil, and crude oil price relationships," Energy Economics, Elsevier, vol. 34(5), pages 1507-1513.
    55. Siami-Namini, Sima & Hudson, Darren, 2017. "Volatility Spillover Between Oil Prices, Us Dollar Exchange Rates And International Agricultural Commodities Prices," 2017 Annual Meeting, February 4-7, 2017, Mobile, Alabama 252845, Southern Agricultural Economics Association.
    56. David Matesanz & Benno Torgler & Germán Dabat & Guillermo J. Ortega, 2014. "Co-movements in commodity prices: a note based on network analysis," Agricultural Economics, International Association of Agricultural Economists, vol. 45(S1), pages 13-21, November.
    57. López Cabrera, Brenda & Schulz, Franziska, 2013. "Volatility linkages between energy and agricultural commodity prices," SFB 649 Discussion Papers 2013-042, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    58. Kang, Sang Hoon & Tiwari, Aviral Kumar & Albulescu, Claudiu Tiberiu & Yoon, Seong-Min, 2019. "Exploring the time-frequency connectedness and network among crude oil and agriculture commodities V1," Energy Economics, Elsevier, vol. 84(C).
    59. Giray GOZGOR & Cahit MEMIS, 2015. "Price volatility spillovers among agricultural commodity and crude oil markets: Evidence from the range-based estimator," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 61(5), pages 214-221.
    60. Karel Janda & Ladislav Krištoufek & Barbora Schererová & David Zilberman, 2021. "Price transmission in biofuel-related global agricultural networks," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 67(10), pages 399-408.
    61. Marcio Genovevo da Costa & Nils Donner, 2016. "Cointegration between Equity- and Agricultural Markets: Implications for Portfolio Diversification," Journal of Management and Sustainability, Canadian Center of Science and Education, vol. 6(1), pages 24-44, March.
    62. Bilgili, Faik & Koçak, Emrah & Kuşkaya, Sevda & Bulut, Ümit, 2020. "Estimation of the co-movements between biofuel production and food prices: A wavelet-based analysis," Energy, Elsevier, vol. 213(C).
    63. Benes, Ondrej & Janda, Karel, 2022. "Environmental Dimensions of Biofuels," EconStor Preprints 259403, ZBW - Leibniz Information Centre for Economics.
    64. FRÓNA Dániel, 2020. "Factors Affecting Food Security," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(1), pages 39-49, July.
    65. Han, Liyan & Zhou, Yimin & Yin, Libo, 2015. "Exogenous impacts on the links between energy and agricultural commodity markets," Energy Economics, Elsevier, vol. 49(C), pages 350-358.
    66. Kunlapath Sukcharoen & David Leatham, 2018. "Analyzing Extreme Comovements in Agricultural and Energy Commodity Markets Using a Regular Vine Copula Method," International Journal of Energy Economics and Policy, Econjournals, vol. 8(5), pages 193-201.
    67. Lima, Cristiane Rocha Albuquerque & de Melo, Gabriel Rivas & Stosic, Borko & Stosic, Tatijana, 2019. "Cross-correlations between Brazilian biofuel and food market: Ethanol versus sugar," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 687-693.
    68. Anelise Rahmeier Seyffarth, 2016. "The Impact of Rising Ethanol Production on the Brazilian Market for Basic Food Commodities: An Econometric Assessment," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 64(3), pages 511-536, July.
    69. Spencer, Simon & Bredin, Don & Conlon, Thomas, 2018. "Energy and agricultural commodities revealed through hedging characteristics: Evidence from developing and mature markets," Journal of Commodity Markets, Elsevier, vol. 9(C), pages 1-20.
    70. Rehman, Mobeen Ur & Vo, Xuan Vinh, 2021. "Energy commodities, precious metals and industrial metal markets: A nexus across different investment horizons and market conditions," Resources Policy, Elsevier, vol. 70(C).
    71. Bouri, Elie & Lucey, Brian & Saeed, Tareq & Vo, Xuan Vinh, 2021. "The realized volatility of commodity futures: Interconnectedness and determinants#," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 139-151.
    72. Wu, JunJie & Sexton, Steven & Zilberman, David, 2019. "Energy price shocks, household location patterns and housing crises: Theory and implications," Energy Economics, Elsevier, vol. 80(C), pages 691-706.
    73. Korhan K. Gokmenoglu & Hasan Güngör & Festus Victor Bekun, 2021. "Revisiting the linkage between oil and agricultural commodity prices: Panel evidence from an Agrarian state," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5610-5620, October.
    74. Ondřej Filip & Karel Janda & Ladislav Krištoufek, 2018. "Ceny biopaliv a souvisejících komodit: analýza s použitím metod minimální kostry grafu a hierarchických stromů [Prices of Biofuels and Related Commodities: an Analysis Using Methods of Minimum Span," Politická ekonomie, Prague University of Economics and Business, vol. 2018(2), pages 218-239.
    75. Chrz, Stepan & Hruby, Zdenek & Janda, Karel & Kristoufek, Ladislav, 2013. "Provazanost trhu potravin, biopaliv a fosilnich paliv [Interconnections within food, biofuel, and fossil fuel markets]," MPRA Paper 43958, University Library of Munich, Germany.
    76. Rico, J.A.P. & Sauer, I.L., 2015. "A review of Brazilian biodiesel experiences," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 513-529.
    77. Wang, Yudong & Wu, Chongfeng & Yang, Li, 2014. "Oil price shocks and agricultural commodity prices," Energy Economics, Elsevier, vol. 44(C), pages 22-35.
    78. Dalheimer, Bernhard & Herwartz, Helmut & Lange, Alexander, 2021. "The threat of oil market turmoils to food price stability in Sub-Saharan Africa," Energy Economics, Elsevier, vol. 93(C).

  52. Ladislav Kristoufek, 2012. "Fractal Markets Hypothesis And The Global Financial Crisis: Scaling, Investment Horizons And Liquidity," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 15(06), pages 1-13.
    See citations under working paper version above.
  53. Kristoufek, Ladislav, 2012. "How are rescaled range analyses affected by different memory and distributional properties? A Monte Carlo study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(17), pages 4252-4260.
    See citations under working paper version above.
  54. Ladislav Krištoufek & Miloslav Vošvrda, 2012. "Efektivita kapitálových trhů: fraktální dimenze, Hurstův exponent a entropie [Capital Markets Efficiency: Fractal Dimension, Hurst Exponent and Entropy]," Politická ekonomie, Prague University of Economics and Business, vol. 2012(2), pages 208-221.

    Cited by:

    1. Kristoufek, Ladislav & Vosvrda, Miloslav, 2014. "Measuring capital market efficiency: Long-term memory, fractal dimension and approximate entropy," FinMaP-Working Papers 18, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    2. Jan Hanousek & Evžen Kočenda & Jan Novotný, 2016. "Shluková analýza skoků na kapitálových trzích [Cluster Analysis of Jumps on Capital Markets]," Politická ekonomie, Prague University of Economics and Business, vol. 2016(2), pages 127-144.

  55. Karel Janda & Ladislav Kristoufek & David Zilberman, 2012. "Biofuels: policies and impacts," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 58(8), pages 372-386.

    Cited by:

    1. Karel Janda & Ladislav Krištoufek, 2019. "The Relationship Between Fuel and Food Prices: Methods and Outcomes," Annual Review of Resource Economics, Annual Reviews, vol. 11(1), pages 195-216, October.

  56. Barunik, Jozef & Kristoufek, Ladislav, 2010. "On Hurst exponent estimation under heavy-tailed distributions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(18), pages 3844-3855.
    See citations under working paper version above.
  57. Ladislav Krištoufek, 2010. "Rescaled Range Analysis and Detrended Fluctuation Analysis: Finite Sample Properties and Confidence Intervals," Czech Economic Review, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, vol. 4(3), pages 315-329, November.

    Cited by:

    1. Kristoufek, Ladislav & Vosvrda, Miloslav, 2014. "Measuring capital market efficiency: Long-term memory, fractal dimension and approximate entropy," FinMaP-Working Papers 18, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    2. Ladislav Kristoufek, 2014. "Leverage effect in energy futures," Papers 1403.0064, arXiv.org.
    3. Cao, Guangxi & Xu, Longbing & Cao, Jie, 2012. "Multifractal detrended cross-correlations between the Chinese exchange market and stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(20), pages 4855-4866.
    4. Ludwig O. Dittrich & Pavel Srbek, 2020. "Is Violation of the Random Walk Assumption an Exception or a Rule in Capital Markets?," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 48(4), pages 491-501, December.
    5. Teng, Yue & Shang, Pengjian, 2018. "Detrended fluctuation analysis based on higher-order moments of financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 311-322.
    6. Ladislav KRISTOUFEK & Petra LUNACKOVA, 2013. "Long-term Memory in Electricity Prices: Czech Market Evidence," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(5), pages 407-424, November.
    7. Lin, Xiaoqiang & Fei, Fangyu, 2013. "Long memory revisit in Chinese stock markets: Based on GARCH-class models and multiscale analysis," Economic Modelling, Elsevier, vol. 31(C), pages 265-275.
    8. Kristoufek, Ladislav, 2012. "How are rescaled range analyses affected by different memory and distributional properties? A Monte Carlo study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(17), pages 4252-4260.
    9. Asif, Raheel & Frömmel, Michael, 2022. "Testing Long memory in exchange rates and its implications for the adaptive market hypothesis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 593(C).
    10. Li, Daye & Nishimura, Yusaku & Men, Ming, 2016. "The long memory and the transaction cost in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 442(C), pages 312-320.
    11. Kristoufek, Ladislav, 2015. "Finite sample properties of power-law cross-correlations estimators," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 513-525.
    12. Ladislav Kristoufek & Miloslav Vosvrda, 2012. "Measuring capital market efficiency: Global and local correlations structure," Papers 1208.1298, arXiv.org.
    13. Li, Daye & Nishimura, Yusaku & Men, Ming, 2016. "Why the long-term auto-correlation has not been eliminated by arbitragers: Evidences from NYMEX," Energy Economics, Elsevier, vol. 59(C), pages 167-178.
    14. Horta, Paulo & Lagoa, Sérgio & Martins, Luís, 2014. "The impact of the 2008 and 2010 financial crises on the Hurst exponents of international stock markets: Implications for efficiency and contagion," International Review of Financial Analysis, Elsevier, vol. 35(C), pages 140-153.
    15. Li, Daye & Kou, Zhun & Sun, Qiankun, 2015. "The scale-dependent market trend: Empirical evidences using the lagged DFA method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 433(C), pages 26-35.
    16. Ibarra-Valdez, C. & Alvarez, J. & Alvarez-Ramirez, J., 2016. "Randomness confidence bands of fractal scaling exponents for financial price returns," Chaos, Solitons & Fractals, Elsevier, vol. 83(C), pages 119-124.
    17. Ladislav Kristoufek, 2013. "Testing power-law cross-correlations: Rescaled covariance test," Papers 1307.4727, arXiv.org, revised Aug 2013.
    18. Gomes, Luís M. P. & Soares, Vasco J. S. & Gama, Sílvio M. A. & Matos, José A. O., 2018. "Long-term memory in Euronext stock indexes returns: an econophysics approach," Business and Economic Horizons (BEH), Prague Development Center, vol. 14(4), pages 862-881, August.
    19. Pavel Srbek, 2018. "Odhad Hurstova exponentu v časových řadách denních výnosů akciových indexů [Estimation of the Hurst Exponent in Time Series of Daily Returns of Stock Indices]," Politická ekonomie, Prague University of Economics and Business, vol. 2018(4), pages 508-524.
    20. Monica Alexiadou & Emmanouil Sofianos & Periklis Gogas & Theophilos Papadimitriou, 2023. "Cryptocurrencies and Long-Range Trends," IJFS, MDPI, vol. 11(1), pages 1-17, February.
    21. Karahan, Cenk C. & Odabaşı, Attila & Tiryaki, C. Sani, 2024. "Wired together: Integration and efficiency in European electricity markets," Energy Economics, Elsevier, vol. 133(C).
    22. R. P. Datta, 2023. "Analysis of Indian foreign exchange markets: A Multifractal Detrended Fluctuation Analysis (MFDFA) approach," Papers 2306.16162, arXiv.org.

  58. Kristoufek, Ladislav, 2010. "On spurious anti-persistence in the US stock indices," Chaos, Solitons & Fractals, Elsevier, vol. 43(1), pages 68-78.

    Cited by:

    1. Dilip Kumar & S. Maheswaran, 2015. "Long memory in Indian exchange rates: an application of power-law scaling analysis," Macroeconomics and Finance in Emerging Market Economies, Taylor & Francis Journals, vol. 8(1-2), pages 90-107, July.
    2. Kristoufek, Ladislav, 2012. "How are rescaled range analyses affected by different memory and distributional properties? A Monte Carlo study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(17), pages 4252-4260.

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