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Jozef Baruník
(Jozef Barunik)

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.

Working papers

  1. Jozef Barunik & Lukas Vacha, 2023. "The Dynamic Persistence of Economic Shocks," Papers 2306.01511, arXiv.org.

    Cited by:

    1. Jozef Barunik & Lukas Vacha, 2024. "Forecasting Volatility of Oil-based Commodities: The Model of Dynamic Persistence," Papers 2402.01354, arXiv.org.

  2. Jozef Barunik & Lubos Hanus, 2022. "Learning Probability Distributions in Macroeconomics and Finance," Papers 2204.06848, arXiv.org.

    Cited by:

    1. Philippe Goulet Coulombe & Mikael Frenette & Karin Klieber, 2023. "From Reactive to Proactive Volatility Modeling with Hemisphere Neural Networks," Working Papers 23-04, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Nov 2023.
    2. Philippe Goulet Coulombe & Mikael Frenette & Karin Klieber, 2023. "From Reactive to Proactive Volatility Modeling with Hemisphere Neural Networks," Papers 2311.16333, arXiv.org, revised Apr 2024.

  3. Jozef Barunik & Mattia Bevilacqua & Robert Faff, 2021. "Dynamic industry uncertainty networks and the business cycle," Papers 2101.06957, arXiv.org, revised Mar 2021.

    Cited by:

    1. Mohammad Al-Shboul & Aktham Maghyereh, 2023. "Did real economic uncertainty drive risk connectedness in the oil–stock nexus during the COVID-19 outbreak? A partial wavelet coherence analysis," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 12(1), pages 1-23, December.

  4. Jozef Barunik & Michael Ellington, 2020. "Persistence in Financial Connectedness and Systemic Risk," Papers 2007.07842, arXiv.org, revised Nov 2023.

    Cited by:

    1. Mykola Babiak & Jozef Barunik, 2021. "Currency Network Risk," Papers 2101.09738, arXiv.org, revised Jul 2021.
    2. Baruník, Jozef & Bevilacqua, Mattia & Faff, Robert, 2024. "Dynamic industry uncertainty networks and the business cycle," Journal of Economic Dynamics and Control, Elsevier, vol. 159(C).

  5. Jozef Barunik & Zdenek Drabek & Matej Nevrla, 2020. "Investment Disputes and Abnormal Volatility of Stocks," Papers 2006.10505, arXiv.org.

    Cited by:

    1. Brada, Josef C. & Chen, Chunda & Jia, Jingyi & Kutan, Ali M. & Perez, M. Fabricio, 2022. "Value creation and value destruction in investor-state dispute arbitration," Journal of Multinational Financial Management, Elsevier, vol. 63(C).

  6. Mykola Babiak & Jozef Barunik, 2020. "Deep Learning, Predictability, and Optimal Portfolio Returns," Papers 2009.03394, arXiv.org, revised Jul 2021.

    Cited by:

    1. Philippe Goulet Coulombe & Maximilian Goebel, 2023. "Maximally Machine-Learnable Portfolios," Papers 2306.05568, arXiv.org, revised Apr 2024.
    2. Weidong Lin & Abderrahim Taamouti, 2023. "Portfolio Selection Under Non-Gaussianity And Systemic Risk: A Machine Learning Based Forecasting Approach," Working Papers 202310, University of Liverpool, Department of Economics.
    3. Jozef Barunik & Lubos Hanus, 2022. "Learning Probability Distributions in Macroeconomics and Finance," Papers 2204.06848, arXiv.org.
    4. Philippe Goulet Coulombe & Maximilian Gobel, 2023. "Maximally Machine-Learnable Portfolios," Working Papers 23-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Apr 2023.
    5. Zhenning Hong & Ruyan Tian & Qing Yang & Weiliang Yao & Tingting Ye & Liangliang Zhang, 2021. "Asset Allocation via Machine Learning," Accounting and Finance Research, Sciedu Press, vol. 10(4), pages 1-34, November.

  7. Jozef Barunik & Michael Ellington, 2020. "Dynamic Network Risk," Papers 2006.04639, arXiv.org, revised Jul 2020.

    Cited by:

    1. Gong, Xiao-Li & Liu, Jian-Min & Xiong, Xiong & Zhang, Wei, 2022. "Research on stock volatility risk and investor sentiment contagion from the perspective of multi-layer dynamic network," International Review of Financial Analysis, Elsevier, vol. 84(C).

  8. Jozef Barunik & Pavel Fiser, 2019. "Co-jumping of Treasury Yield Curve Rates," Papers 1905.01541, arXiv.org.

    Cited by:

    1. Semeyutin, Artur & Gozgor, Giray & Lau, Chi Keung Marco & Xu, Bing, 2021. "Effects of idiosyncratic jumps and co-jumps on oil, gold, and copper markets," Energy Economics, Elsevier, vol. 104(C).
    2. Semeyutin, Artur & Downing, Gareth, 2022. "Co-jumps in the U.S. interest rates and precious metals markets and their implications for investors," International Review of Financial Analysis, Elsevier, vol. 81(C).

  9. Jozef Barunik & Mattia Bevilacqua & Radu Tunaru, 2018. "Asymmetric Network Connectedness of Fears," Papers 1810.12022, arXiv.org, revised Oct 2020.

    Cited by:

    1. Jozef Barunik & Mattia Bevilacqua & Michael Ellington, 2023. "Common Firm-level Investor Fears: Evidence from Equity Options," Papers 2309.03968, arXiv.org.
    2. Baruník, Jozef & Ellington, Michael, 2024. "Persistence in financial connectedness and systemic risk," European Journal of Operational Research, Elsevier, vol. 314(1), pages 393-407.
    3. Ellington, Michael, 2022. "Fat tails, serial dependence, and implied volatility index connections," European Journal of Operational Research, Elsevier, vol. 299(2), pages 768-779.
    4. Niţoi, Mihai & Pochea, Maria Miruna, 2022. "The nexus between bank connectedness and investors’ sentiment," Finance Research Letters, Elsevier, vol. 44(C).
    5. Naeem, Muhammad Abubakr & Lucey, Brian M. & Karim, Sitara & Ghafoor, Abdul, 2022. "Do financial volatilities mitigate the risk of cryptocurrency indexes?," Finance Research Letters, Elsevier, vol. 50(C).
    6. Timo Dimitriadis & Yannick Hoga, 2023. "Regressions under Adverse Conditions," Papers 2311.13327, arXiv.org.
    7. 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.
    8. Baruník, Jozef & Bevilacqua, Mattia & Faff, Robert, 2024. "Dynamic industry uncertainty networks and the business cycle," Journal of Economic Dynamics and Control, Elsevier, vol. 159(C).
    9. Li, Qiang & Nong, Huifu, 2022. "A closer look at Chinese housing market: Measuring intra-city submarket connectedness in Shanghai and Guangzhou," China Economic Review, Elsevier, vol. 74(C).
    10. Pagnottoni, Paolo & Spelta, Alessandro, 2023. "The motifs of risk transmission in multivariate time series: Application to commodity prices," Socio-Economic Planning Sciences, Elsevier, vol. 87(PB).
    11. Yarovaya, Larisa & Brzeszczyński, Janusz & Goodell, John W. & Lucey, Brian & Lau, Chi Keung Marco, 2022. "Rethinking financial contagion: Information transmission mechanism during the COVID-19 pandemic," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    12. Bevilacqua, Mattia & Tunaru, Radu & Vioto, Davide, 2020. "Options-based systemic risk, financial distress, and macroeconomic downturns," LSE Research Online Documents on Economics 118850, London School of Economics and Political Science, LSE Library.
    13. Ye, Liping & Geng, Jiang-Bo, 2021. "Measuring the connectedness of global health sector stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    14. Bevilacqua, Mattia & Tunaru, Radu & Vioto, Davide, 2023. "Options-based systemic risk, financial distress, and macroeconomic downturns," Journal of Financial Markets, Elsevier, vol. 65(C).
    15. Bevilacqua, Mattia & Tunaru, Radu & Vioto, Davide, 2023. "Options-based systemic risk, financial distress, and macroeconomic downturns," LSE Research Online Documents on Economics 119289, London School of Economics and Political Science, LSE Library.
    16. Pagnottoni, Paolo, 2023. "Superhighways and roads of multivariate time series shock transmission: Application to cryptocurrency, carbon emission and energy prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 615(C).

  10. Jozef Barun'ik & Evv{z}en Kov{c}enda, 2018. "Total, asymmetric and frequency connectedness between oil and forex markets," Papers 1805.03980, arXiv.org, revised Feb 2019.

    Cited by:

    1. Vaclav Broz & Evzen Kocenda, 2019. "Mortgage-Related Bank Penalties and Systemic Risk Among U.S. Banks," Working Papers IES 2019/25, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Sep 2019.
    2. Balcilar, Mehmet & Ozdemir, Zeynel Abidin & Ozdemir, Huseyin & Wohar, Mark E., 2020. "Spillover effects in oil-related CDS markets during and after the sub-prime crisis," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    3. Mr. Adrian Alter & Mr. Selim A Elekdag, 2016. "Emerging Market Corporate Leverage and Global Financial Conditions," IMF Working Papers 2016/243, International Monetary Fund.
    4. Zhu, Huiming & Li, Shuang & Huang, Zishan, 2023. "Frequency domain quantile dependence and connectedness between crude oil and exchange rates: Evidence from oil-importing and exporting countries," The Quarterly Review of Economics and Finance, Elsevier, vol. 90(C), pages 1-30.
    5. Nekhili, Ramzi & Mensi, Walid & Vo, Xuan Vinh, 2021. "Multiscale spillovers and connectedness between gold, copper, oil, wheat and currency markets," Resources Policy, Elsevier, vol. 74(C).
    6. Fousekis, Panos & Tzaferi, Dimitra, 2021. "Returns and volume: Frequency connectedness in cryptocurrency markets," Economic Modelling, Elsevier, vol. 95(C), pages 13-20.
    7. Anwer, Zaheer & Naeem, Muhammad Abubakr & Hassan, M. Kabir & Karim, Sitara, 2022. "Asymmetric connectedness across Asia-Pacific currencies: Evidence from time-frequency domain analysis," Finance Research Letters, Elsevier, vol. 47(PB).
    8. Aktham Maghyereh & Hussein Abdoh, 2022. "COVID-19 and the volatility interlinkage between bitcoin and financial assets," Empirical Economics, Springer, vol. 63(6), pages 2875-2901, December.
    9. Mehmet Balcilar & Zeynel Abidin Ozdemir & Huseyin Ozdemir & Gurcan Aygun & Mark E. Wohar, 2022. "Effectiveness of monetary policy under the high and low economic uncertainty states: evidence from the major Asian economies," Empirical Economics, Springer, vol. 63(4), pages 1741-1769, October.
    10. Huynh, Toan Luu Duc & Nasir, Muhammad Ali & Nguyen, Duc Khuong, 2023. "Spillovers and connectedness in foreign exchange markets: The role of trade policy uncertainty," The Quarterly Review of Economics and Finance, Elsevier, vol. 87(C), pages 191-199.
    11. 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).
    12. Togonidze, Sophio & Kočenda, Evžen, 2022. "Macroeconomic responses of emerging market economies to oil price shocks: An analysis by region and resource profile," Economic Systems, Elsevier, vol. 46(3).
    13. Duc Huynh, Toan Luu & Burggraf, Tobias & Nasir, Muhammad Ali, 2020. "Financialisation of natural resources & instability caused by risk transfer in commodity markets," Resources Policy, Elsevier, vol. 66(C).
    14. Mensi, Walid & Shafiullah, Muhammad & Vo, Xuan Vinh & Kang, Sang Hoon, 2022. "Asymmetric spillovers and connectedness between crude oil and currency markets using high-frequency data," Resources Policy, Elsevier, vol. 77(C).
    15. Huynh, Toan Luu Duc & Hille, Erik & Nasir, Muhammad Ali, 2020. "Diversification in the age of the 4th industrial revolution: The role of artificial intelligence, green bonds and cryptocurrencies," Technological Forecasting and Social Change, Elsevier, vol. 159(C).
    16. Shah, Adil Ahmad & Dar, Arif Billah, 2022. "Asymmetric, time and frequency-based spillover transmission in financial and commodity markets," The Journal of Economic Asymmetries, Elsevier, vol. 25(C).
    17. Peter Albrecht & Evžen Kočenda & Evžen Kocenda, 2023. "Volatility Connectedness on the Central European Forex Markets," CESifo Working Paper Series 10728, CESifo.
    18. Evžen Kočenda & Michala Moravcová & Evžen Kocenda, 2024. "Frequency Volatility Connectedness and Portfolio Hedging of U.S. Energy Commodities," CESifo Working Paper Series 10889, CESifo.
    19. 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.
    20. Geng, Jiang-Bo & Xu, Xiao-Yue & Ji, Qiang, 2020. "The time-frequency impacts of natural gas prices on US economic activity," Energy, Elsevier, vol. 205(C).
    21. Lovcha, Yuliya & Perez-Laborda, Alejandro, 2022. "Long-memory and volatility spillovers across petroleum futures," Energy, Elsevier, vol. 243(C).
    22. Li, Guangchen & Shen, Z.Y. & Song, Malin & Wei, Weixian, 2024. "Exploring the interconnectedness of China's new energy and stock markets: A study on volatility spillovers and dynamic correlations," International Review of Economics & Finance, Elsevier, vol. 89(PB), pages 471-484.
    23. Naeem, Muhammad Abubakr & Pham, Linh & Senthilkumar, Arunachalam & Karim, Sitara, 2022. "Oil shocks and BRIC markets: Evidence from extreme quantile approach," Energy Economics, Elsevier, vol. 108(C).
    24. Shang, Jin & Hamori, Shigeyuki, 2021. "Do crude oil prices and the sentiment index influence foreign exchange rates differently in oil-importing and oil-exporting countries? A dynamic connectedness analysis," Resources Policy, Elsevier, vol. 74(C).
    25. Huynh, Toan Luu Duc, 2021. "Does Bitcoin React to Trump’s Tweets?," Journal of Behavioral and Experimental Finance, Elsevier, vol. 31(C).
    26. Huifu Nong, 2024. "Connectedness and risk transmission of China’s stock and currency markets with global commodities," Economic Change and Restructuring, Springer, vol. 57(1), pages 1-24, February.
    27. shah, Adil Ahmad & Bhanja, Niyati & Dar, Arif Billah, 2023. "Do gold and the US dollar diversify global sectoral risk? Evidence from connectedness and dynamic conditional correlation measures," The Journal of Economic Asymmetries, Elsevier, vol. 28(C).
    28. Luu Duc Huynh, Toan, 2020. "The effect of uncertainty on the precious metals market: New insights from Transfer Entropy and Neural Network VAR," Resources Policy, Elsevier, vol. 66(C).
    29. Fousekis, Panos & Tzaferi, Dimitra, 2018. "Market connectedness in the US beef supply chain," Agricultural Economics Review, Greek Association of Agricultural Economists, vol. 0(Issue 1).
    30. Dejan Živkov & Marina Gajic-Glamoclija & Jasmina Duraskovic & Mirela Momcilovic, 2022. "Assessing Permanent and Transitory Volatility Spillover Effect from Oil to Stocks in Baltic and Visegrad Countries," Journal of Economics / Ekonomicky casopis, Institute of Economic Research, Slovak Academy of Sciences, vol. 70(6), pages 523-542, June.
    31. Anh Ngoc Quang Huynh & Duy Duong & Tobias Burggraf & Hien Thi Thu Luong & Nam Huu Bui, 2022. "Energy Consumption and Bitcoin Market," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 29(1), pages 79-93, March.
    32. Alam, Md. Samsul & Shahzad, Syed Jawad Hussain & Ferrer, Román, 2019. "Causal flows between oil and forex markets using high-frequency data: Asymmetries from good and bad volatility," Energy Economics, Elsevier, vol. 84(C).
    33. Jian Yang & Zheng Li & Hong Miao, 2021. "Volatility spillovers in commodity futures markets: A network approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(12), pages 1959-1987, December.
    34. Apostolakis, George N. & Floros, Christos & Gkillas, Konstantinos & Wohar, Mark, 2021. "Political uncertainty, COVID-19 pandemic and stock market volatility transmission," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    35. Toan Luu Duc Huynh & Muhammad Shahbaz & Muhammad Ali Nasir & Subhan Ullah, 2022. "Financial modelling, risk management of energy instruments and the role of cryptocurrencies," Annals of Operations Research, Springer, vol. 313(1), pages 47-75, June.

  11. Frantiv{s}ek v{C}ech & Jozef Barun'ik, 2018. "Panel quantile regressions for estimating and predicting the Value--at--Risk of commodities," Papers 1807.11823, arXiv.org.

    Cited by:

    1. Zhang, Ning & Gong, Yujing & Xue, Xiaohan, 2023. "Less disagreement, better forecasts: adjusted risk measures in the energy futures market," LSE Research Online Documents on Economics 118451, London School of Economics and Political Science, LSE Library.
    2. Ning Zhang & Yujing Gong & Xiaohan Xue, 2023. "Less disagreement, better forecasts: Adjusted risk measures in the energy futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(10), pages 1332-1372, October.
    3. Gong, Xu & Xu, Jun & Liu, Tangyong & Zhou, Zicheng, 2022. "Dynamic volatility connectedness between industrial metal markets," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).

  12. Stanislav Anatolyev & Jozef Barunik, 2017. "Forecasting dynamic return distributions based on ordered binary choice," Papers 1711.05681, arXiv.org, revised Jan 2019.

    Cited by:

    1. Stanislav Anatolyev, 2021. "Directional news impact curve," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 94-107, January.
    2. Jozef Barunik & Lubos Hanus, 2023. "Learning Probability Distributions of Day-Ahead Electricity Prices," Papers 2310.02867, arXiv.org, revised Oct 2023.
    3. Jozef Barunik & Lubos Hanus, 2022. "Learning Probability Distributions in Macroeconomics and Finance," Papers 2204.06848, arXiv.org.
    4. Lei, Heng & Xue, Minggao & Liu, Huiling, 2022. "Probability distribution forecasting of carbon allowance prices: A hybrid model considering multiple influencing factors," Energy Economics, Elsevier, vol. 113(C).

  13. Frantisek Cech & Jozef Barunik, 2017. "Measurement of Common Risk Factors: A Panel Quantile Regression Model for Returns," Papers 1708.08622, arXiv.org.

    Cited by:

    1. Mr. Tobias Adrian & Federico Grinberg & Nellie Liang & Sheheryar Malik, 2018. "The Term Structure of Growth-at-Risk," IMF Working Papers 2018/180, International Monetary Fund.

  14. Jiri Kukacka & Jozef Barunik, 2016. "Simulated ML Estimation of Financial Agent-Based Models," Working Papers IES 2016/07, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Mar 2016.

    Cited by:

    1. Giorgio Fagiolo & Mattia Guerini & Francesco Lamperti & Alessio Moneta & Andrea Roventini, 2019. "Validation of Agent-Based Models in Economics and Finance," SciencePo Working papers Main halshs-02375423, HAL.
    2. Donovan Platt & Tim Gebbie, 2016. "The Problem of Calibrating an Agent-Based Model of High-Frequency Trading," Papers 1606.01495, arXiv.org, revised Mar 2017.
    3. Lamperti, Francesco, 2018. "An information theoretic criterion for empirical validation of simulation models," Econometrics and Statistics, Elsevier, vol. 5(C), pages 83-106.
    4. Lux, Thomas, 2017. "Estimation of agent-based models using sequential Monte Carlo methods," Economics Working Papers 2017-07, Christian-Albrechts-University of Kiel, Department of Economics.

  15. Jozef Barunik & Lukas Vacha, 2016. "Do co-jumps impact correlations in currency markets?," Papers 1602.05489, arXiv.org, revised Oct 2017.

    Cited by:

    1. Serdengeçti, Süleyman & Sensoy, Ahmet & Nguyen, Duc Khuong, 2021. "Dynamics of return and liquidity (co) jumps in emerging foreign exchange markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 73(C).
    2. Sensoy, Ahmet & Serdengeçti, Süleyman, 2020. "Impact of portfolio flows and heterogeneous expectations on FX jumps: Evidence from an emerging market," International Review of Financial Analysis, Elsevier, vol. 68(C).
    3. Dungey, Mardi & Matei, Marius & Treepongkaruna, Sirimon, 2020. "Examining stress in Asian currencies: A perspective offered by high frequency financial market data," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 67(C).
    4. Semeyutin, Artur & Gozgor, Giray & Lau, Chi Keung Marco & Xu, Bing, 2021. "Effects of idiosyncratic jumps and co-jumps on oil, gold, and copper markets," Energy Economics, Elsevier, vol. 104(C).
    5. Syed Jawad Hussain Shahzad & Jose Arreola‐Hernandez & Md Lutfur Rahman & Gazi Salah Uddin & Muhammad Yahya, 2021. "Asymmetric interdependence between currency markets' volatilities across frequencies and time scales," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2436-2457, April.
    6. Jozef Barunik & Pavel Fiser, 2019. "Co-jumping of Treasury Yield Curve Rates," Papers 1905.01541, arXiv.org.
    7. Semeyutin, Artur & Downing, Gareth, 2022. "Co-jumps in the U.S. interest rates and precious metals markets and their implications for investors," International Review of Financial Analysis, Elsevier, vol. 81(C).

  16. Tomas Krehlik & Jozef Barunik, 2016. "Cyclical properties of supply-side and demand-side shocks in oil-based commodity markets," Papers 1603.07020, arXiv.org, revised Jan 2017.

    Cited by:

    1. Lovcha, Yuliya & Perez-Laborda, Alejandro, 2020. "Dynamic frequency connectedness between oil and natural gas volatilities," Economic Modelling, Elsevier, vol. 84(C), pages 181-189.
    2. Umar, Zaghum & Nasreen, Samia & Solarin, Sakiru Adebola & Tiwari, Aviral Kumar, 2019. "Exploring the time and frequency domain connectedness of oil prices and metal prices," Resources Policy, Elsevier, vol. 64(C).
    3. Wu, You & Ren, Wenting & Wan, Jieru & Liu, Xiaoxue, 2023. "Time-frequency volatility connectedness between fossil energy and agricultural commodities: Comparing the COVID-19 pandemic with the Russia-Ukraine conflict," Finance Research Letters, Elsevier, vol. 55(PA).
    4. Emmanuel Joel Aikins Abakah & Aviral Kumar Tiwari & Imhotep Paul Alagidede & Shawkat Hammoudeh, 2023. "Nonlinearity in the causality and systemic risk spillover between the OPEC oil and GCC equity markets: a pre- and post-financial crisis analysis," Empirical Economics, Springer, vol. 65(3), pages 1027-1103, September.
    5. Gehrke, Britta & Yao, Fang, 2017. "Are supply shocks important for real exchange rates? A fresh view from the frequency-domain," Journal of International Money and Finance, Elsevier, vol. 79(C), pages 99-114.
    6. Ferrer, Román & Shahzad, Syed Jawad Hussain & López, Raquel & Jareño, Francisco, 2018. "Time and frequency dynamics of connectedness between renewable energy stocks and crude oil prices," Energy Economics, Elsevier, vol. 76(C), pages 1-20.
    7. Escribano, Ana & Koczar, Monika W. & Jareño, Francisco & Esparcia, Carlos, 2023. "Shock transmission between crude oil prices and stock markets," Resources Policy, Elsevier, vol. 83(C).
    8. Lovcha, Yuliya & Perez-Laborda, Alejandro, 2022. "Long-memory and volatility spillovers across petroleum futures," Energy, Elsevier, vol. 243(C).
    9. Dan Nie & Yanbin Li & Xiyu Li & Xuejiao Zhou & Feng Zhang, 2022. "The Dynamic Spillover between Renewable Energy, Crude Oil and Carbon Market: New Evidence from Time and Frequency Domains," Energies, MDPI, vol. 15(11), pages 1-28, May.
    10. 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).
    11. James Ming Chen & Mobeen Ur Rehman, 2021. "A Pattern New in Every Moment: The Temporal Clustering of Markets for Crude Oil, Refined Fuels, and Other Commodities," Energies, MDPI, vol. 14(19), pages 1-58, September.
    12. Chen, Jinyu & Liang, Zhipeng & Ding, Qian & Ren, Xiaohang & Wu, Anbing, 2023. "Dynamic connectedness across energy and metal futures markets during the COVID-19 pandemic: New evidence from a time-varying spillover index," Resources Policy, Elsevier, vol. 86(PA).
    13. Niu, Hongli, 2021. "Correlations between crude oil and stocks prices of renewable energy and technology companies: A multiscale time-dependent analysis," Energy, Elsevier, vol. 221(C).
    14. Zhang, Xu & Yang, Xian & He, Qizhi, 2022. "Multi-scale systemic risk and spillover networks of commodity markets in the bullish and bearish regimes," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    15. Chien-Fu Chen & Shu-hen Chiang, 2020. "Time-varying spillovers among first-tier housing markets in China," Urban Studies, Urban Studies Journal Limited, vol. 57(4), pages 844-864, March.
    16. Geng, Jiang-Bo & Chen, Fu-Rui & Ji, Qiang & Liu, Bing-Yue, 2021. "Network connectedness between natural gas markets, uncertainty and stock markets," Energy Economics, Elsevier, vol. 95(C).
    17. Jiang, Yonghong & Ao, Zhiming & Mo, Bin, 2023. "The risk spillover between China’s economic policy uncertainty and commodity markets: Evidence from frequency spillover and quantile connectedness approaches," The North American Journal of Economics and Finance, Elsevier, vol. 66(C).
    18. Alam, Md. Samsul & Shahzad, Syed Jawad Hussain & Ferrer, Román, 2019. "Causal flows between oil and forex markets using high-frequency data: Asymmetries from good and bad volatility," Energy Economics, Elsevier, vol. 84(C).
    19. Gong, Xu & Xu, Jun, 2022. "Geopolitical risk and dynamic connectedness between commodity markets," Energy Economics, Elsevier, vol. 110(C).
    20. Tokgoz, Simla & Traoré, Fousseini, 2023. "Understanding E10 markets in the U.S.: Evidence from spatial data," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 1267-1281.

  17. Kukacka, Jiri & Barunik, Jozef, 2016. "Estimation of financial agent-based models with simulated maximum likelihood," FinMaP-Working Papers 63, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.

    Cited by:

    1. Francesco Lamperti & Andrea Roventini & Amir Sani, 2017. "Agent-Based Model Calibration using Machine Learning Surrogates," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01499344, HAL.
    2. Siyan Chen & Saul Desiderio, 2022. "Calibration of Agent-Based Models by Means of Meta-Modeling and Nonparametric Regression," Computational Economics, Springer;Society for Computational Economics, vol. 60(4), pages 1457-1478, December.
    3. Filippo Gusella, 2022. "Detecting and Measuring Financial Cycles in Heterogeneous Agents Models: An Empirical Analysis," Working Papers - Economics wp2022_02.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    4. Kukacka, Jiri & Sacht, Stephen, 2021. "Estimation of Heuristic Switching in Behavioral Macroeconomic Models," Economics Working Papers 2021-01, Christian-Albrechts-University of Kiel, Department of Economics.
    5. Mohammad Ghaderi, 2020. "Public Health Interventions in the Face of Pandemics: Network Structure, Social Distancing, and Heterogeneity," Working Papers 1193, Barcelona School of Economics.
    6. Nils Bertschinger & Iurii Mozzhorin, 2021. "Bayesian estimation and likelihood-based comparison of agent-based volatility models," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 16(1), pages 173-210, January.
    7. Filippo Gusella & Giorgio Ricchiuti, 2021. "State Space Model to Detect Cycles in Heterogeneous Agents Models," Working Papers - Economics wp2021_10.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
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    3. Wang, Gang-Jin & Chen, Yang-Yang & Si, Hui-Bin & Xie, Chi & Chevallier, Julien, 2021. "Multilayer information spillover networks analysis of China’s financial institutions based on variance decompositions," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 325-347.
    4. Ando, Mitsuyo & Hayakawa, Kazunobu, 2021. "Impact of covid-19 on trade in services," IDE Discussion Papers 824, Institute of Developing Economies, Japan External Trade Organization(JETRO).
    5. Choi, Sun-Yong, 2022. "Volatility spillovers among Northeast Asia and the US: Evidence from the global financial crisis and the COVID-19 pandemic," Economic Analysis and Policy, Elsevier, vol. 73(C), pages 179-193.
    6. Okorie, David Iheke & Lin, Boqiang, 2022. "Givers never lack: Nigerian oil & gas asymmetric network analyses," Energy Economics, Elsevier, vol. 108(C).
    7. Chang, Ya-Ting & Gau, Yin-Feng & Hsu, Chih-Chiang, 2022. "Liquidity spillover in foreign exchange markets," Finance Research Letters, Elsevier, vol. 44(C).
    8. Balcilar, Mehmet & Ozdemir, Zeynel Abidin & Ozdemir, Huseyin & Wohar, Mark E., 2020. "Spillover effects in oil-related CDS markets during and after the sub-prime crisis," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    9. Xiurong Chen & Aimin Hao & Yali Li, 2020. "The impact of financial contagion on real economy-An empirical research based on combination of complex network technology and spatial econometrics model," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-20, March.
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    Cited by:

    1. Aviral Kumar Tiwari & Muhammad Shahbaz & Haslifah M. Hasim & Mohamed M. Elheddad, 2019. "Analysing the spillover of inflation in selected Euro-area countries," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 17(3), pages 551-577, September.
    2. 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.
    3. Jena, Sangram Keshari & Tiwari, Aviral Kumar & Aikins Abakah, Emmanuel Joel & Hammoudeh, Shawkat, 2022. "The connectedness in the world petroleum futures markets using a Quantile VAR approach," Journal of Commodity Markets, Elsevier, vol. 27(C).
    4. Batten, Jonathan A. & Brzeszczynski, Janusz & Ciner, Cetin & Lau, Marco C.K. & Lucey, Brian & Yarovaya, Larisa, 2019. "Price and volatility spillovers across the international steam coal market," Energy Economics, Elsevier, vol. 77(C), pages 119-138.
    5. Gehrke, Britta & Yao, Fang, 2017. "Are supply shocks important for real exchange rates? A fresh view from the frequency-domain," Journal of International Money and Finance, Elsevier, vol. 79(C), pages 99-114.
    6. Chang, Shu-Lien & Lee, Yun-Huan, 2019. "Returns spillovers between tourism ETFs," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    7. Muhammad Owais Qarni & Saqib Gulzar, 2020. "Intra-EMU and non-EMU, EU stock markets’ return spillover: evidence from ESDC," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 47(3), pages 543-577, August.
    8. Magkonis, Georgios & Tsouknidis, Dimitris A., 2017. "Dynamic spillover effects across petroleum spot and futures volatilities, trading volume and open interest," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 104-118.
    9. Lubos Hanus & Lukas Vacha, 2018. "Time-Frequency Response Analysis of Monetary Policy Transmission," Working Papers IES 2018/30, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Oct 2018.
    10. Aurelio F. Bariviera & Ignasi Merediz-Sol`a, 2020. "Where do we stand in cryptocurrencies economic research? A survey based on hybrid analysis," Papers 2003.09723, arXiv.org.
    11. Zhang, Wenting & He, Xie & Hamori, Shigeyuki, 2023. "The impact of the COVID-19 pandemic and Russia-Ukraine war on multiscale spillovers in green finance markets: Evidence from lower and higher order moments," International Review of Financial Analysis, Elsevier, vol. 89(C).
    12. 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).
    13. Ogbuabor, Jonathan E. & Anthony-Orji, Onyinye I. & Manasseh, Charles O. & Orji, Anthony, 2020. "Measuring the dynamics of COMESA output connectedness with the global economy," The Journal of Economic Asymmetries, Elsevier, vol. 21(C).
    14. Urom, Christian & Abid, Ilyes & Guesmi, Khaled & Chevallier, Julien, 2020. "Quantile spillovers and dependence between Bitcoin, equities and strategic commodities," Economic Modelling, Elsevier, vol. 93(C), pages 230-258.

  20. Jozef Barunik & Tomas Krehlik, 2015. "Measuring the frequency dynamics of financial connectedness and systemic risk," Papers 1507.01729, arXiv.org, revised Dec 2017.

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    1. Chang, Hao-Wen & Chang, Tsangyao & Lee, Chien-Chiang, 2023. "Return and volatility connectedness among the BRICS stock and oil markets," Resources Policy, Elsevier, vol. 86(PA).
    2. Hu, Yang & Lang, Chunlin & Corbet, Shaen & Wang, Junchuan, 2024. "The impact of COVID-19 on the volatility connectedness of the Chinese tourism sector," Research in International Business and Finance, Elsevier, vol. 68(C).
    3. Miklesh Yadav & Nandita Mishra & Shruti Ashok, 2023. "Dynamic connectedness of green bond with financial markets of European countries under OECD economies," Economic Change and Restructuring, Springer, vol. 56(1), pages 609-631, February.
    4. Liu, Rongyan & He, Lingyun & Xia, Yufei & Fu, Yating & Chen, Ling, 2023. "Research on the time-varying effects among green finance markets in China: A fresh evidence from multi-frequency scale perspective," The North American Journal of Economics and Finance, Elsevier, vol. 66(C).
    5. 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.
    6. Hoque, Mohammad Enamul & Soo-Wah, Low & Tiwari, Aviral Kumar & Akhter, Tahmina, 2023. "Time and frequency domain connectedness and spillover among categorical and regional financial stress, gold and bitcoin market," Resources Policy, Elsevier, vol. 85(PA).
    7. Yousaf, Imran & Yarovaya, Larisa, 2022. "The relationship between trading volume, volatility and returns of Non-Fungible Tokens: evidence from a quantile approach," Finance Research Letters, Elsevier, vol. 50(C).
    8. Farid, Saqib & Karim, Sitara & Naeem, Muhammad A. & Nepal, Rabindra & Jamasb, Tooraj, 2023. "Co-movement between dirty and clean energy: A time-frequency perspective," Energy Economics, Elsevier, vol. 119(C).
    9. Dhoha Mellouli & Imen Zoglami, 2024. "The Dynamics of Connectivity between Traditional Cryptocurrencies and NFTs: Validation of the Connectivity Model by Quantiles and Frequencies," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(1), pages 131-154.
    10. Lovcha, Yuliya & Perez-Laborda, Alejandro, 2020. "Dynamic frequency connectedness between oil and natural gas volatilities," Economic Modelling, Elsevier, vol. 84(C), pages 181-189.
    11. Feng, Huiqun & Zhang, Jun & Guo, Na, 2023. "Time-varying linkages between energy and stock markets: Dynamic spillovers and driving factors," International Review of Financial Analysis, Elsevier, vol. 89(C).
    12. Salem, Leila Ben & Zayati, Montassar & Nouira, Ridha & Rault, Christophe, 2024. "Volatility Spillover between Oil Prices and Main Exchange Rates: Evidence from a DCC-GARCH-Connectedness Approach," IZA Discussion Papers 16832, Institute of Labor Economics (IZA).
    13. Elsayed, Ahmed H. & Ahmed, Habib & Husam Helmi, Mohamad, 2023. "Determinants of financial stability and risk transmission in dual financial system: Evidence from the COVID pandemic," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 85(C).
    14. Qi, Haozhi & Wu, Tiantian & Chen, Hao & Lu, Xiuling, 2023. "Time-frequency connectedness and cross-quantile dependence between carbon emission trading and commodity markets: Evidence from China," Resources Policy, Elsevier, vol. 82(C).
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    28. Zhu, Huiming & Li, Shuang & Huang, Zishan, 2023. "Frequency domain quantile dependence and connectedness between crude oil and exchange rates: Evidence from oil-importing and exporting countries," The Quarterly Review of Economics and Finance, Elsevier, vol. 90(C), pages 1-30.
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    32. Gazi Salah Uddin & Muhammad Yahya & Ali Ahmed & Donghyun Park & Shu Tian, 2024. "In search of light in the darkness: What can we learn from ethical, sustainable and green investments?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(2), pages 1451-1495, April.
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    39. Mensi, Walid & Vo, Xuan Vinh & Kang, Sang Hoon, 2021. "Precious metals, oil, and ASEAN stock markets: From global financial crisis to global health crisis," Resources Policy, Elsevier, vol. 73(C).
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    1. Wang, Jue & Zhou, Hao & Hong, Tao & Li, Xiang & Wang, Shouyang, 2020. "A multi-granularity heterogeneous combination approach to crude oil price forecasting," Energy Economics, Elsevier, vol. 91(C).
    2. Lajos Horváth & Zhenya Liu & Curtis Miller & Weiqing Tang, 2024. "Breaks in term structures: Evidence from the oil futures markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(2), pages 2317-2341, April.
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  22. Jozef Barun'ik & Tobias Kley, 2015. "Quantile Coherency: A General Measure for Dependence between Cyclical Economic Variables," Papers 1510.06946, arXiv.org, revised Dec 2018.

    Cited by:

    1. Ángel López-Oriona & José A. Vilar, 2021. "F4: An All-Purpose Tool for Multivariate Time Series Classification," Mathematics, MDPI, vol. 9(23), pages 1-26, November.
    2. 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).
    3. Jozef Barun'ik & Matv{e}j Nevrla, 2018. "Quantile Spectral Beta: A Tale of Tail Risks, Investment Horizons, and Asset Prices," Papers 1806.06148, arXiv.org, revised Dec 2021.
    4. Maghyereh, Aktham & Abdoh, Hussein, 2022. "Extreme dependence between structural oil shocks and stock markets in GCC countries," Resources Policy, Elsevier, vol. 76(C).
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    6. Naeem, Muhammad Abubakr & Agyemang, Abraham & Hasan Chowdhury, Md Iftekhar & Hasan, Mudassar & Shahzad, Syed Jawad Hussain, 2022. "Precious metals as hedge and safe haven for African stock markets," Resources Policy, Elsevier, vol. 78(C).
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    9. Rehman, Mobeen Ur & Nautiyal, Neeraj & Vo, Xuan Vinh & Ghardallou, Wafa & Kang, Sang Hoon, 2023. "Is the impact of oil shocks more pronounced during extreme market conditions?," Resources Policy, Elsevier, vol. 85(PA).
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    1. Eduard Baumohl & Evzen Kocenda & Stefan Lyocsa & Tomas Vyrost, 2016. "Networks of volatility spillovers among stock markets," KIER Working Papers 941, Kyoto University, Institute of Economic Research.
    2. Lovcha, Yuliya & Perez-Laborda, Alejandro, 2020. "Dynamic frequency connectedness between oil and natural gas volatilities," Economic Modelling, Elsevier, vol. 84(C), pages 181-189.
    3. Restrepo, Natalia & Uribe, Jorge M. & Manotas, Diego, 2018. "Financial risk network architecture of energy firms," Applied Energy, Elsevier, vol. 215(C), pages 630-642.
    4. Balcilar, Mehmet & Ozdemir, Zeynel Abidin & Ozdemir, Huseyin & Wohar, Mark E., 2020. "Spillover effects in oil-related CDS markets during and after the sub-prime crisis," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    5. Evrim Mandacı, Pınar & Cagli, Efe Çaglar & Taşkın, Dilvin, 2020. "Dynamic connectedness and portfolio strategies: Energy and metal markets," Resources Policy, Elsevier, vol. 68(C).
    6. Chen, Yufeng & Li, Wenqi & Qu, Fang, 2019. "Dynamic asymmetric spillovers and volatility interdependence on China’s stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 825-838.
    7. Tule, Moses K. & Ndako, Umar B. & Onipede, Samuel F., 2017. "Oil price shocks and volatility spillovers in the Nigerian sovereign bond market," Review of Financial Economics, Elsevier, vol. 35(C), pages 57-65.
    8. Čech, František & Zítek, Michal, 2022. "Marine fuel hedging under the sulfur cap regulations," Energy Economics, Elsevier, vol. 113(C).
    9. Guan, Bo & Mazouz, Khelifa & Xu, Yongdeng, 2023. "Asymmetric volatility spillover between crude oil and other asset markets," Cardiff Economics Working Papers E2023/27, Cardiff University, Cardiff Business School, Economics Section.
    10. Andrea Bastianin & Chiara Casoli & Marzio Galeotti, 2023. "The connectedness of Energy Transition Metals," Working Papers 2023.11, Fondazione Eni Enrico Mattei.
    11. Liu, Tangyong & Gong, Xu, 2020. "Analyzing time-varying volatility spillovers between the crude oil markets using a new method," Energy Economics, Elsevier, vol. 87(C).
    12. An, Henry & Qiu, Feng & Rude, James, 2021. "Volatility spillovers between food and fuel markets: Do administrative regulations affect the transmission?," Economic Modelling, Elsevier, vol. 102(C).
    13. Wang, Gang-Jin & Xie, Chi & Zhao, Longfeng & Jiang, Zhi-Qiang, 2018. "Volatility connectedness in the Chinese banking system: Do state-owned commercial banks contribute more?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 57(C), pages 205-230.
    14. Hung Do & Rabindra Nepal & Tooraj Jamasb, 2020. "Electricity market integration, decarbonisation and security of supply: Dynamic volatility connectedness in the Irish and Great Britain markets," CAMA Working Papers 2020-42, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    15. Alomari, Mohammad & Mensi, Walid & Vo, Xuan Vinh & Kang, Sang Hoon, 2022. "Extreme return spillovers and connectedness between crude oil and precious metals futures markets: Implications for portfolio management," Resources Policy, Elsevier, vol. 79(C).
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    17. Christian Bucio-Pacheco & Miriam Sosa-Castro & Francisco Reyes-Zarate, 2023. "Volatilidad dinamica en el sector bancario en Mexico: evidencia DCC-GARCH vs Copula-GARCH," EconoQuantum, Revista de Economia y Finanzas, Universidad de Guadalajara, Centro Universitario de Ciencias Economico Administrativas, Departamento de Metodos Cuantitativos y Maestria en Economia., vol. 20(2), pages 69-93, Julio-Dic.
    18. Baruník, Jozef & Kočenda, Evžen & Vácha, Lukáš, 2016. "Asymmetric connectedness on the U.S. stock market: Bad and good volatility spillovers," Journal of Financial Markets, Elsevier, vol. 27(C), pages 55-78.
    19. Hung Do & Rabindra Nepal & Russell Smyth, 2020. "Interconnectedness in the Australian National Electricity Market: A Higher‐Moment Analysis," The Economic Record, The Economic Society of Australia, vol. 96(315), pages 450-469, December.
    20. Gong, Xu & Liu, Yun & Wang, Xiong, 2021. "Dynamic volatility spillovers across oil and natural gas futures markets based on a time-varying spillover method," International Review of Financial Analysis, Elsevier, vol. 76(C).
    21. Hoque, Mohammad Enamul & Soo-Wah, Low & Billah, Mabruk, 2023. "Time-frequency connectedness and spillover among carbon, climate, and energy futures: Determinants and portfolio risk management implications," Energy Economics, Elsevier, vol. 127(PB).
    22. Chatziantoniou, Ioannis & Gabauer, David & Perez de Gracia, Fernando, 2022. "Tail risk connectedness in the refined petroleum market: A first look at the impact of the COVID-19 pandemic," Energy Economics, Elsevier, vol. 111(C).
    23. Grobys, Klaus & Junttila, Juha & Kolari, James W. & Sapkota, Niranjan, 2021. "On the stability of stablecoins," Journal of Empirical Finance, Elsevier, vol. 64(C), pages 207-223.
    24. Le, Trung H. & Pham, Linh & Do, Hung X., 2023. "Price risk transmissions in the water-energy-food nexus: Impacts of climate risks and portfolio implications," Energy Economics, Elsevier, vol. 124(C).
    25. 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.
    26. Jena, Sangram Keshari & Tiwari, Aviral Kumar & Aikins Abakah, Emmanuel Joel & Hammoudeh, Shawkat, 2022. "The connectedness in the world petroleum futures markets using a Quantile VAR approach," Journal of Commodity Markets, Elsevier, vol. 27(C).
    27. 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).
    28. Umar, Zaghum & Jareño, Francisco & Escribano, Ana, 2021. "Oil price shocks and the return and volatility spillover between industrial and precious metals," Energy Economics, Elsevier, vol. 99(C).
    29. Togonidze, Sophio & Kočenda, Evžen, 2022. "Macroeconomic responses of emerging market economies to oil price shocks: An analysis by region and resource profile," Economic Systems, Elsevier, vol. 46(3).
    30. Guan, Bo & Mazouz, Khelifa & Xu, Yongdeng, 2024. "Asymmetric volatility spillover between crude oil and other asset markets," Energy Economics, Elsevier, vol. 130(C).
    31. Josef Kurka, 2017. "Do Cryptocurrencies and Traditional Asset Classes Influence Each Other?," Working Papers IES 2017/29, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Dec 2017.
    32. Baruník, Jozef & Kočenda, Evžen & Vácha, Lukáš, 2017. "Asymmetric volatility connectedness on the forex market," Journal of International Money and Finance, Elsevier, vol. 77(C), pages 39-56.
    33. Moses K. Tule & Umar B. Ndako & Samuel F. Onipede, 2017. "Oil price shocks and volatility spillovers in the Nigerian sovereign bond market," Review of Financial Economics, John Wiley & Sons, vol. 35(1), pages 57-65, November.
    34. Kostas Andriosopoulos & Emilios Galariotis & Spyros Spyrou, 2017. "Contagion, volatility persistence and volatility spill-overs: The case of energy markets during the European financial crisis," Post-Print hal-01578056, HAL.
    35. Kim, Jong-Min & Tabacu, Lucia & Jung, Hojin, 2020. "A quantile-copula approach to dependence between financial assets," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
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    38. Muhammad Owais Qarni & Saqib Gulzar, 2020. "Intra-EMU and non-EMU, EU stock markets’ return spillover: evidence from ESDC," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 47(3), pages 543-577, August.
    39. Magkonis, Georgios & Tsouknidis, Dimitris A., 2017. "Dynamic spillover effects across petroleum spot and futures volatilities, trading volume and open interest," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 104-118.
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    41. Wang, Xunxiao, 2020. "Frequency dynamics of volatility spillovers among crude oil and international stock markets: The role of the interest rate," Energy Economics, Elsevier, vol. 91(C).
    42. Křehlík, Tomáš & Baruník, Jozef, 2017. "Cyclical properties of supply-side and demand-side shocks in oil-based commodity markets," Energy Economics, Elsevier, vol. 65(C), pages 208-218.
    43. Okhrin, Yarema & Uddin, Gazi Salah & Yahya, Muhammad, 2023. "Nonlinear and asymmetric interconnectedness of crude oil with financial and commodity markets," Energy Economics, Elsevier, vol. 125(C).
    44. Peter Albrecht & Evžen Kočenda & Evžen Kocenda, 2023. "Volatility Connectedness on the Central European Forex Markets," CESifo Working Paper Series 10728, CESifo.
    45. Evžen Kočenda & Michala Moravcová & Evžen Kocenda, 2024. "Frequency Volatility Connectedness and Portfolio Hedging of U.S. Energy Commodities," CESifo Working Paper Series 10889, CESifo.
    46. Lovcha, Yuliya & Perez-Laborda, Alejandro, 2022. "Long-memory and volatility spillovers across petroleum futures," Energy, Elsevier, vol. 243(C).
    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. Achraf Ghorbel & Wajdi Frikha & Yasmine Snene Manzli, 2022. "Testing for asymmetric non-linear short- and long-run relationships between crypto-currencies and stock markets," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 12(3), pages 387-425, September.
    49. 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).
    50. Mensi, Walid & Rehman, Mobeen Ur & Vo, Xuan Vinh, 2021. "Dynamic frequency relationships and volatility spillovers in natural gas, crude oil, gas oil, gasoline, and heating oil markets: Implications for portfolio management," Resources Policy, Elsevier, vol. 73(C).
    51. Han, Lin & Kordzakhia, Nino & Trück, Stefan, 2020. "Volatility spillovers in Australian electricity markets," Energy Economics, Elsevier, vol. 90(C).
    52. Tangyong Liu & Xu Gong & Lizhi Tang, 2022. "The uncertainty spillovers of China's economic policy: Evidence from time and frequency domains," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4541-4555, October.
    53. Výrost, Tomas & Lyócsa, Štefan & Baumöhl, Eduard, 2019. "Network-based asset allocation strategies," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 516-536.
    54. Xu Gong & Boqiang Lin, 2021. "Effects of structural changes on the prediction of downside volatility in futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(7), pages 1124-1153, July.
    55. Muhammad Owais Qarni & Saiqb Gulzar, 2021. "Portfolio diversification benefits of alternative currency investment in Bitcoin and foreign exchange markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-37, December.
    56. shah, Adil Ahmad & Bhanja, Niyati & Dar, Arif Billah, 2023. "Do gold and the US dollar diversify global sectoral risk? Evidence from connectedness and dynamic conditional correlation measures," The Journal of Economic Asymmetries, Elsevier, vol. 28(C).
    57. Cui, Jinxin & Maghyereh, Aktham & Goh, Mark & Zou, Huiwen, 2022. "Risk spillovers and time-varying links between international oil and China’s commodity futures markets: Fresh evidence from the higher-order moments," Energy, Elsevier, vol. 238(PB).
    58. Chan, Ying Tung & Qiao, Hui, 2023. "Volatility spillover between oil and stock prices: Structural connectedness based on a multi-sector DSGE model approach with Bayesian estimation," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 265-286.
    59. Zelazny Jan, 2016. "Financialization and Commodity Market Stability," Financial Internet Quarterly (formerly e-Finanse), Sciendo, vol. 12(4), pages 33-42, December.
    60. Maghyereh, Aktham & Awartani, Basel & Abdoh, Hussein, 2022. "Asymmetric risk transfer in global equity markets: An extended sample that includes the COVID pandemic period," The Journal of Economic Asymmetries, Elsevier, vol. 25(C).
    61. Li, Wenqi, 2021. "COVID-19 and asymmetric volatility spillovers across global stock markets," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    62. Maitra, Debasish & Guhathakurta, Kousik & Kang, Sang Hoon, 2021. "The good, the bad and the ugly relation between oil and commodities: An analysis of asymmetric volatility connectedness and portfolio implications," Energy Economics, Elsevier, vol. 94(C).
    63. Chen, Rongda & Wei, Bo & Jin, Chenglu & Liu, Jia, 2021. "Returns and volatilities of energy futures markets: Roles of speculative and hedging sentiments," International Review of Financial Analysis, Elsevier, vol. 76(C).
    64. Do, Hung Xuan & Brooks, Robert & Treepongkaruna, Sirimon & Wu, Eliza, 2016. "Stock and currency market linkages: New evidence from realized spillovers in higher moments," International Review of Economics & Finance, Elsevier, vol. 42(C), pages 167-185.
    65. Lovcha, Yuliya & Pérez Laborda, Àlex, 2018. "Volatility Spillovers in a Long-Memory VAR: an Application to Energy Futures Returns," Working Papers 2072/307362, Universitat Rovira i Virgili, Department of Economics.
    66. Mohamad, Azhar & Fromentin, Vincent, 2023. "Herd and causality dynamics between energy commodities and ethical investment: Evidence from the different phases of the COVID-19 pandemic," Energy Economics, Elsevier, vol. 126(C).
    67. Dahl, Roy Endré & Jonsson, Erlendur, 2018. "Volatility spillover in seafood markets," Journal of Commodity Markets, Elsevier, vol. 12(C), pages 44-59.
    68. Apergis, Nicholas & Gozgor, Giray & Lau, Chi Keung Marco & Wang, Shixuan, 2019. "Decoding the Australian electricity market: New evidence from three-regime hidden semi-Markov model," Energy Economics, Elsevier, vol. 78(C), pages 129-142.
    69. Ederington, Louis H. & Fernando, Chitru S. & Hoelscher, Seth A. & Lee, Thomas K. & Linn, Scott C., 2019. "Characteristics of petroleum product prices: A survey," Journal of Commodity Markets, Elsevier, vol. 14(C), pages 1-15.
    70. Apergis, Nicholas & Baruník, Jozef & Lau, Marco Chi Keung, 2017. "Good volatility, bad volatility: What drives the asymmetric connectedness of Australian electricity markets?," Energy Economics, Elsevier, vol. 66(C), pages 108-115.
    71. Sema Bayraktar & Thomas C. Chiang, 2017. "Comovements of Stock Markets between Turkey and Global Countries," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 67(3), pages 250-275, June.

  25. Jozef Baruník & Lucie Kraicová, 2014. "Estimation of Long Memory in Volatility Using Wavelets," Working Papers IES 2014/33, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Sep 2014.

    Cited by:

    1. Lahmiri, Salim & Bekiros, Stelios, 2020. "Nonlinear analysis of Casablanca Stock Exchange, Dow Jones and S&P500 industrial sectors with a comparison," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).

  26. Jozef Baruník & Frantisek Cech, 2014. "On the modelling and forecasting multivariate realized volatility: Generalized Heterogeneous Autoregressive (GHAR) model," Working Papers IES 2014/23, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Aug 2014.

    Cited by:

    1. Jiawen Luo & Langnan Chen, 2019. "Multivariate realized volatility forecasts of agricultural commodity futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(12), pages 1565-1586, December.
    2. Hwang, Eunju & Hong, Won-Tak, 2021. "A multivariate HAR-RV model with heteroscedastic errors and its WLS estimation," Economics Letters, Elsevier, vol. 203(C).
    3. Luo, Jiawen & Chen, Langnan, 2020. "Realized volatility forecast with the Bayesian random compressed multivariate HAR model," International Journal of Forecasting, Elsevier, vol. 36(3), pages 781-799.
    4. Qu, Hui & Zhang, Yi, 2022. "Asymmetric multivariate HAR models for realized covariance matrix: A study based on volatility timing strategies," Economic Modelling, Elsevier, vol. 106(C).
    5. Hardik A. Marfatia & Qiang Ji & Jiawen Luo, 2022. "Forecasting the volatility of agricultural commodity futures: The role of co‐volatility and oil volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 383-404, March.
    6. Lyócsa, Štefan & Molnár, Peter, 2018. "Exploiting dependence: Day-ahead volatility forecasting for crude oil and natural gas exchange-traded funds," Energy, Elsevier, vol. 155(C), pages 462-473.
    7. Dark, Jonathan, 2024. "An adaptive long memory conditional correlation model," Journal of Empirical Finance, Elsevier, vol. 75(C).
    8. Won-Tak Hong & Jiwon Lee & Eunju Hwang, 2020. "A Note on the Asymptotic Normality Theory of the Least Squares Estimates in Multivariate HAR-RV Models," Mathematics, MDPI, vol. 8(11), pages 1-18, November.
    9. Jin, Xin & Maheu, John M & Yang, Qiao, 2017. "Bayesian Parametric and Semiparametric Factor Models for Large Realized Covariance Matrices," MPRA Paper 81920, University Library of Munich, Germany.
    10. Wei Kuang, 2021. "Conditional covariance matrix forecast using the hybrid exponentially weighted moving average approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1398-1419, December.
    11. Zhang, Yongjie & Chu, Gang & Shen, Dehua, 2021. "The role of investor attention in predicting stock prices: The long short-term memory networks perspective," Finance Research Letters, Elsevier, vol. 38(C).
    12. Andrea BUCCI, 2017. "Forecasting Realized Volatility A Review," Journal of Advanced Studies in Finance, ASERS Publishing, vol. 8(2), pages 94-138.
    13. Izzeldin, Marwan & Muradoğlu, Yaz Gülnur & Pappas, Vasileios & Sivaprasad, Sheeja, 2021. "The impact of Covid-19 on G7 stock markets volatility: Evidence from a ST-HAR model," International Review of Financial Analysis, Elsevier, vol. 74(C).
    14. Symitsi, Efthymia & Symeonidis, Lazaros & Kourtis, Apostolos & Markellos, Raphael, 2018. "Covariance forecasting in equity markets," Journal of Banking & Finance, Elsevier, vol. 96(C), pages 153-168.
    15. Pham, Son Duy & Nguyen, Thao Thac Thanh & Do, Hung Xuan, 2022. "Dynamic volatility connectedness between thermal coal futures and major cryptocurrencies: Evidence from China," Energy Economics, Elsevier, vol. 112(C).

  27. Krenar Avdulaj & Jozef Barunik, 2013. "Are benefits from oil - stocks diversification gone? New evidence from a dynamic copula and high frequency data," Papers 1307.5981, arXiv.org, revised Feb 2015.

    Cited by:

    1. Gaete, Michael & Herrera, Rodrigo, 2023. "Diversification benefits of commodities in portfolio allocation: A dynamic factor copula approach," Journal of Commodity Markets, Elsevier, vol. 32(C).
    2. Triki, Mohamed Bilel & Ben Maatoug, Abderrazek, 2021. "The GOLD market as a safe haven against the stock market uncertainty: Evidence from geopolitical risk," Resources Policy, Elsevier, vol. 70(C).
    3. Wen, Xiaoqian & Bouri, Elie & Roubaud, David, 2017. "Can energy commodity futures add to the value of carbon assets?," Economic Modelling, Elsevier, vol. 62(C), pages 194-206.
    4. Xiaojing Cai & Shigeyuki Hamori & Lu Yang & Shuairu Tian, 2020. "Multi-Horizon Dependence between Crude Oil and East Asian Stock Markets and Implications in Risk Management," Energies, MDPI, vol. 13(2), pages 1-24, January.
    5. Wen, Xiaoqian & Cheng, Hua, 2018. "Which is the safe haven for emerging stock markets, gold or the US dollar?," Emerging Markets Review, Elsevier, vol. 35(C), pages 69-90.
    6. Li, Songsong & Zhang, Weiqian & Zhang, Wei, 2023. "Dynamic time-frequency connectedness and risk spillover between geopolitical risks and natural resources," Resources Policy, Elsevier, vol. 82(C).
    7. Naeem, Muhammad & Umar, Zaghum & Ahmed, Sheraz & Ferrouhi, El Mehdi, 2020. "Dynamic dependence between ETFs and crude oil prices by using EGARCH-Copula approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 557(C).
    8. Heinlein, Reinhold & Legrenzi, Gabriella D. & Mahadeo, Scott M.R., 2021. "Crude oil and stock markets in the COVID-19 crisis: Evidence from oil exporters and importers," The Quarterly Review of Economics and Finance, Elsevier, vol. 82(C), pages 223-229.
    9. Parthajit Kayal & Janani Sri SG, 2020. "Going Beyond Gold: Can Equities be Safe-Haven?," Working Papers 2020-203, Madras School of Economics,Chennai,India.
    10. Massimiliano Caporin & Chia-Lin Chang & Michael McAleer, 2016. "Are the S&P 500 Index and Crude Oil, Natural Gas and Ethanol Futures Related for Intra-Day Data?," Documentos de Trabajo del ICAE 2016-01, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    11. Astrid Ayala & Szabolcs Blazsek, 2018. "Equity market neutral hedge funds and the stock market: an application of score-driven copula models," Applied Economics, Taylor & Francis Journals, vol. 50(37), pages 4005-4023, August.
    12. Song, Shijia & Li, Handong, 2022. "Predicting VaR for China's stock market: A score-driven model based on normal inverse Gaussian distribution," International Review of Financial Analysis, Elsevier, vol. 82(C).
    13. Murad A. BEIN & Mehmet AGA, 2016. "On the Linkage between the International Crude Oil Price and Stock Markets: Evidence from the Nordic and Other European Oil Importing and Oil Exporting Countries," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 115-134, December.
    14. Emmanuel Joel Aikins Abakah & Aviral Kumar Tiwari & Imhotep Paul Alagidede & Shawkat Hammoudeh, 2023. "Nonlinearity in the causality and systemic risk spillover between the OPEC oil and GCC equity markets: a pre- and post-financial crisis analysis," Empirical Economics, Springer, vol. 65(3), pages 1027-1103, September.
    15. Wen, Danyan & Wang, Yudong & Zhang, Yaojie, 2021. "Intraday return predictability in China’s crude oil futures market: New evidence from a unique trading mechanism," Economic Modelling, Elsevier, vol. 96(C), pages 209-219.
    16. Kayalar, Derya Ezgi & Küçüközmen, C. Coşkun & Selcuk-Kestel, A. Sevtap, 2017. "The impact of crude oil prices on financial market indicators: copula approach," Energy Economics, Elsevier, vol. 61(C), pages 162-173.
    17. Chen, Rongda & Xu, Jianjun, 2019. "Forecasting volatility and correlation between oil and gold prices using a novel multivariate GAS model," Energy Economics, Elsevier, vol. 78(C), pages 379-391.
    18. Ito, R., 2016. "Spline-DCS for Forecasting Trade Volume in High-Frequency Finance," Cambridge Working Papers in Economics 1606, Faculty of Economics, University of Cambridge.
    19. Batten, Jonathan A. & Kinateder, Harald & Szilagyi, Peter G. & Wagner, Niklas F., 2017. "Can stock market investors hedge energy risk? Evidence from Asia," Energy Economics, Elsevier, vol. 66(C), pages 559-570.
    20. Lu Yang & Jason Z. Ma & Shigeyuki Hamori, 2018. "Dependence Structures and Systemic Risk of Government Securities Markets in Central and Eastern Europe: A CoVaR-Copula Approach," Sustainability, MDPI, vol. 10(2), pages 1-23, January.
    21. Okhrin, Yarema & Uddin, Gazi Salah & Yahya, Muhammad, 2023. "Nonlinear and asymmetric interconnectedness of crude oil with financial and commodity markets," Energy Economics, Elsevier, vol. 125(C).
    22. Yu, Lean & Zha, Rui & Stafylas, Dimitrios & He, Kaijian & Liu, Jia, 2020. "Dependences and volatility spillovers between the oil and stock markets: New evidence from the copula and VAR-BEKK-GARCH models," International Review of Financial Analysis, Elsevier, vol. 68(C).
    23. Christensen, Troels Sønderby & Pircalabu, Anca & Høg, Esben, 2019. "A seasonal copula mixture for hedging the clean spark spread with wind power futures," Energy Economics, Elsevier, vol. 78(C), pages 64-80.
    24. Krenar AVDULAJ & Jozef BARUNIK, 2013. "Can We Still Benefit from International Diversification? The Case of the Czech and German Stock Markets," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(5), pages 425-442, November.
    25. Ji, Hao & Wang, Hao & Zhong, Rui & Li, Min, 2020. "China's liberalizing stock market, crude oil, and safe-haven assets: A linkage study based on a novel multivariate wavelet-vine copula approach," Economic Modelling, Elsevier, vol. 93(C), pages 187-204.
    26. Semeyutin, Artur & Gozgor, Giray & Lau, Chi Keung Marco & Xu, Bing, 2021. "Effects of idiosyncratic jumps and co-jumps on oil, gold, and copper markets," Energy Economics, Elsevier, vol. 104(C).
    27. Nguyen, Hoang & Virbickaite, Audrone, 2022. "Modeling stock-oil co-dependence with Dynamic Stochastic MIDAS Copula models," Working Papers 2022:5, Örebro University, School of Business.
    28. Pircalabu, A. & Benth, F.E., 2017. "A regime-switching copula approach to modeling day-ahead prices in coupled electricity markets," Energy Economics, Elsevier, vol. 68(C), pages 283-302.
    29. 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.
    30. Xu, Yingying & Lien, Donald, 2020. "Dynamic exchange rate dependences: The effect of the U.S.-China trade war," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 68(C).
    31. Ryoko Ito, 2016. "Asymptotic Theory for Beta-t-GARCH," Cambridge Working Papers in Economics 1607, Faculty of Economics, University of Cambridge.
    32. Batten, Jonathan A. & Kinateder, Harald & Szilagyi, Peter G. & Wagner, Niklas F., 2019. "Time-varying energy and stock market integration in Asia," Energy Economics, Elsevier, vol. 80(C), pages 777-792.
    33. Tobias Eckernkemper, 2018. "Modeling Systemic Risk: Time-Varying Tail Dependence When Forecasting Marginal Expected Shortfall," Journal of Financial Econometrics, Oxford University Press, vol. 16(1), pages 63-117.
    34. Migliavacca, Milena & Goodell, John W. & Paltrinieri, Andrea, 2023. "A bibliometric review of portfolio diversification literature," International Review of Financial Analysis, Elsevier, vol. 90(C).
    35. Pircalabu, A. & Hvolby, T. & Jung, J. & Høg, E., 2017. "Joint price and volumetric risk in wind power trading: A copula approach," Energy Economics, Elsevier, vol. 62(C), pages 139-154.
    36. Yang, Kun & Wei, Yu & Li, Shouwei & He, Jianmin, 2020. "Asymmetric risk spillovers between Shanghai and Hong Kong stock markets under China’s capital account liberalization," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    37. Francesco Serinaldi & Chris G. Kilsby, 2017. "A Blueprint for Full Collective Flood Risk Estimation: Demonstration for European River Flooding," Risk Analysis, John Wiley & Sons, vol. 37(10), pages 1958-1976, October.
    38. Chang, Kuang-Liang, 2023. "The low-magnitude and high-magnitude asymmetries in tail dependence structures in international equity markets and the role of bilateral exchange rate," Journal of International Money and Finance, Elsevier, vol. 133(C).
    39. Song, Shijia & Tian, Fei & Li, Handong, 2021. "An intraday-return-based Value-at-Risk model driven by dynamic conditional score with censored generalized Pareto distribution," Journal of Asian Economics, Elsevier, vol. 74(C).
    40. Georgios Bampinas & Theodore Panagiotidis, 2017. "Oil and stock markets before and after financial crises : a local Gaussian correlation approach," Bank of Estonia Working Papers wp2016-11, Bank of Estonia, revised 06 Feb 2017.
    41. Li, Xiafei & Wei, Yu, 2018. "The dependence and risk spillover between crude oil market and China stock market: New evidence from a variational mode decomposition-based copula method," Energy Economics, Elsevier, vol. 74(C), pages 565-581.
    42. Yingying Xu & Donald Lien, 2020. "Optimal futures hedging for energy commodities: An application of the GAS model," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(7), pages 1090-1108, July.
    43. Janani Sri S. & Parthajit Kayal & G. Balasubramanian, 2022. "Can Equity be Safe-haven for Investment?," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 21(1), pages 32-63, March.
    44. Ivanovski, Kris & Hailemariam, Abebe, 2021. "Forecasting the dynamic relationship between crude oil and stock prices since the 19th century," Journal of Commodity Markets, Elsevier, vol. 24(C).
    45. Semeyutin, Artur & Downing, Gareth, 2022. "Co-jumps in the U.S. interest rates and precious metals markets and their implications for investors," International Review of Financial Analysis, Elsevier, vol. 81(C).

  28. Jozef Barunik & Lukas Vacha, 2013. "Contagion among Central and Eastern European stock markets during the financial crisis," Papers 1309.0491, arXiv.org, revised Sep 2013.

    Cited by:

    1. Kregždė Arvydas & Kišonaitė Karolina, 2018. "Co-movements of Lithuanian and Central European Stock Markets Across Different Time Horizons: A Wavelet Approach," Ekonomika (Economics), Sciendo, vol. 97(2), pages 55-69, December.
    2. Dejan Živkov & Suzana Balaban & Marko Pećanac, 2021. "Assessing the multiscale “meteor shower” effect from oil to the central and eastern European stock indices," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 1855-1870, April.
    3. Jovan Njegic & Milica Stankovic & Dejan Živkov, 2019. "What Wavelet-Based Quantiles Can Suggest about the Stocks-Bond Interaction in the Emerging East Asian Economies?," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 69(1), pages 95-119, February.
    4. Cengiz KARATAS & Gazanfer UNAL & Adil YILMAZ, 2017. "Co-movement and Forecasting Analysis of Major Real Estate Markets by Wavelet Coherence and Multiple Wavelet Coherence," Chinese Journal of Urban and Environmental Studies (CJUES), World Scientific Publishing Co. Pte. Ltd., vol. 5(02), pages 1-18, June.
    5. Rehman, Mobeen Ur & Ahmad, Nasir & Shahzad, Syed Jawad Hussain & Vo, Xuan Vinh, 2022. "Dependence dynamics of stock markets during COVID-19," Emerging Markets Review, Elsevier, vol. 51(PB).
    6. Dejan Živkov & Jovan Njegić & Marko Pećanac, 2019. "Multiscale interdependence between the major agricultural commodities," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 65(2), pages 82-92.
    7. Yilmaz, Adil & Unal, Gazanfer & Karatasoglu, Cengiz, 2016. "Wavelet Based Analysis Of Major Real Estate Markets," MPRA Paper 74083, University Library of Munich, Germany.
    8. Jasmina Ðuraškovic & Slavica Manic & Dejan Živkov, 2019. "Multiscale Volatility Transmission and Portfolio Construction Between the Baltic Stock Markets," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 69(2), pages 211-235, April.
    9. RNuket Kirci Cevik & Sel Dibooglu & Ali M. Kutan, 2016. "Real and Financial Sector Studies in Central and Eastern Europe: A Review," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 66(1), pages 2-31, February.
    10. Emre Kahraman & Gazanfer Unal, 2016. "Multiple Wavelet Coherency Analysis and Forecasting of Metal Prices," Papers 1602.01960, arXiv.org.
    11. Caner Özdurak & Cengiz Karataş, 2021. "Covid-19 and the Technology Bubble 2.0: Evidence from DCC-MGARCH and Wavelet Approaches," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 11(2), pages 1-4.
    12. Dejan Zivkov & Marina Gajic-Glamoclija & Jelena Kovacevic & Sanja Loncar, 2020. "Inflation Uncertainty and Output Growth - Evidence from the Asia-Pacific Countries Based on the Multiscale Bayesian Quantile Inference," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 70(5), pages 461-486, November.
    13. Dejan Zivkov & Suzana Balaban & Jasmina Djuraskovic, 2018. "What Multiscale Approach Can Tell About the Nexus Between Exchange Rate and Stocks in the Major Emerging Markets?," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 68(5), pages 491-512, October.
    14. Adil Yilmaz & Gazanfer Unal, 2016. "Co-movement analysis of Asian stock markets against FTSE100 and S&P 500: Wavelet-based approach," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 3(04), pages 1-19, December.
    15. Reboredo, Juan C. & Tiwari, Aviral Kumar & Albulescu, Claudiu Tiberiu, 2015. "An analysis of dependence between Central and Eastern European stock markets," Economic Systems, Elsevier, vol. 39(3), pages 474-490.
    16. Dejan Živkov & Jovan Njegiæ & Mirela Momèiloviæ, 2018. "Bidirectional spillover effect between Russian stock index and the selected commodities," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 36(1), pages 29-53.

  29. Jozef Barunik & Evzen Kocenda & Lukas Vacha, 2013. "Asymmetric connectedness of stocks: How does bad and good volatility spill over the U.S. stock market?," Papers 1308.1221, arXiv.org, revised Jul 2014.

    Cited by:

    1. Aharon, David Y. & Umar, Zaghum & Aziz, Mukhriz Izraf Azman & Vo, Xuan vinh, 2022. "COVID-19 related media sentiment and the yield curve of G-7 economies," The North American Journal of Economics and Finance, Elsevier, vol. 61(C).
    2. Chen, Jing & Han, Qian & Ryu, Doojin & Tang, Jing, 2022. "Does the world smile together? A network analysis of global index option implied volatilities," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 77(C).
    3. 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).
    4. Klaus Grobys & Sami Vähämaa, 2020. "Another look at value and momentum: volatility spillovers," Review of Quantitative Finance and Accounting, Springer, vol. 55(4), pages 1459-1479, November.
    5. He, Feng & Wang, Ziwei & Yin, Libo, 2020. "Asymmetric volatility spillovers between international economic policy uncertainty and the U.S. stock market," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    6. Zheng, Biao & Zhang, Yuquan W. & Yin, Haitao & Geng, Yong, 2021. "The limited role of stock market in financing new energy development in China: An investigation using firms’ high-frequency data," Economic Analysis and Policy, Elsevier, vol. 72(C), pages 651-667.
    7. Okorie, David Iheke & Lin, Boqiang, 2022. "Givers never lack: Nigerian oil & gas asymmetric network analyses," Energy Economics, Elsevier, vol. 108(C).
    8. Zheng, Biao & Zhang, Yuquan & Chen, Yufeng, 2021. "Asymmetric connectedness and dynamic spillovers between renewable energy and rare earth markets in China: Evidence from firms’ high-frequency data," Resources Policy, Elsevier, vol. 71(C).
    9. Ahn, Yongkil & Tsai, Shih-Chuan, 2021. "What factors are associated with stock price jumps in high frequency?," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    10. Lien, Donald & Lee, Geul & Yang, Li & Zhang, Yuyin, 2018. "Volatility spillovers among the U.S. and Asian stock markets: A comparison between the periods of Asian currency crisis and subprime credit crisis," The North American Journal of Economics and Finance, Elsevier, vol. 46(C), pages 187-201.
    11. Balcilar, Mehmet & Ozdemir, Zeynel Abidin & Ozdemir, Huseyin & Wohar, Mark E., 2020. "Spillover effects in oil-related CDS markets during and after the sub-prime crisis," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    12. Chen, Yufeng & Li, Wenqi & Qu, Fang, 2019. "Dynamic asymmetric spillovers and volatility interdependence on China’s stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 825-838.
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    1. Śmiech, Sławomir & Papież, Monika, 2017. "In search of hedges and safe havens: Revisiting the relations between gold and oil in the rolling regression framework," Finance Research Letters, Elsevier, vol. 20(C), pages 238-244.
    2. Eduard Baumohl & Evzen Kocenda & Stefan Lyocsa & Tomas Vyrost, 2016. "Networks of volatility spillovers among stock markets," KIER Working Papers 941, Kyoto University, Institute of Economic Research.
    3. Lei Ming & Yao Shen & Shenggang Yang & Sangzhi Zhu & Hong Zhu, 2020. "Does Gold Serve as a Hedge for the Stock Market in China? Evidence from a Time-Frequency Analysis," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 56(3), pages 659-672, February.
    4. Nekhili, Ramzi & Mensi, Walid & Vo, Xuan Vinh, 2021. "Multiscale spillovers and connectedness between gold, copper, oil, wheat and currency markets," Resources Policy, Elsevier, vol. 74(C).
    5. Emrah Oral & Gazanfer Unal, 2017. "Co-movement of precious metals and forecasting using scale by scale wavelet transform," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 4(01), pages 1-21, March.
    6. Smimou, K., 2017. "Does gold Liquidity learn from the greenback or the equity?," Research in International Business and Finance, Elsevier, vol. 41(C), pages 461-479.
    7. Huang, Shupei & An, Haizhong & Gao, Xiangyun & Sun, Xiaoqi, 2017. "Do oil price asymmetric effects on the stock market persist in multiple time horizons?," Applied Energy, Elsevier, vol. 185(P2), pages 1799-1808.
    8. Lin, Fu-Lai & Yang, Sheng-Yung & Marsh, Terry & Chen, Yu-Fen, 2018. "Stock and bond return relations and stock market uncertainty: Evidence from wavelet analysis," International Review of Economics & Finance, Elsevier, vol. 55(C), pages 285-294.
    9. Marcin Wk{a}torek & Stanis{l}aw Dro.zd.z & Pawe{l} O'swic{e}cimka & Marek Stanuszek, 2018. "Multifractal cross-correlations between the World Oil and other Financial Markets in 2012-2017," Papers 1812.08548, arXiv.org, revised Jun 2019.
    10. Huang, Shupei & An, Haizhong & Huang, Xuan & Jia, Xiaoliang, 2018. "Co-movement of coherence between oil prices and the stock market from the joint time-frequency perspective," Applied Energy, Elsevier, vol. 221(C), pages 122-130.
    11. Muhammad Abubakr Naeem & Saqib Farid & Fiza Qureshi & Farhad Taghizadeh‐Hesary, 2023. "Global factors and the transmission between United States and emerging stock markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 3488-3510, October.
    12. Qian, Yao & Ralescu, Dan A. & Zhang, Bo, 2019. "The analysis of factors affecting global gold price," Resources Policy, Elsevier, vol. 64(C).
    13. Zhang, Weiping & Zhuang, Xintian, 2019. "The stability of Chinese stock network and its mechanism," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 748-761.
    14. Aviral Kumar Tiwari & Samia Nasreen & Subhan Ullah & Muhammad Shahbaz, 2021. "Analysing spillover between returns and volatility series of oil across major stock markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2458-2490, April.
    15. Shahzad, Umer & Mohammed, Kamel Si & Tiwari, Sunil & Nakonieczny, Joanna & Nesterowicz, Renata, 2023. "Connectedness between geopolitical risk, financial instability indices and precious metals markets: Novel findings from Russia Ukraine conflict perspective," Resources Policy, Elsevier, vol. 80(C).
    16. Huang, Shupei & An, Haizhong & Gao, Xiangyun & Huang, Xuan, 2016. "Time–frequency featured co-movement between the stock and prices of crude oil and gold," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 985-995.
    17. Fasanya, Ismail & Adekoya, Oluwasegun & Oyewole, Oluwatomisin & Adegboyega, Soliu, 2022. "Investor sentiment and energy futures predictability: Evidence from Feasible Quasi Generalized Least Squares," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    18. 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.
    19. Adewuyi, Adeolu O. & Awodumi, Olabanji B. & Abodunde, Temitope T., 2019. "Analysing the gold-stock nexus using VARMA-BEKK-AGARCH and Quantile regression models: New evidence from South Africa and Nigeria," Resources Policy, Elsevier, vol. 61(C), pages 348-362.
    20. Ahmad Alrazni Alshammari, Basheer Altarturi, Buerhan Saiti, Latifah Munassar, 2020. "The impact of exchange rate, oil price and gold price on the Kuwaiti stock market: a wavelet analysis," European Journal of Comparative Economics, Cattaneo University (LIUC), vol. 17(1), pages 31-54, June.
    21. Rehman, Mobeen Ur & Kang, Sang Hoon, 2021. "A time–frequency comovement and causality relationship between Bitcoin hashrate and energy commodity markets," Global Finance Journal, Elsevier, vol. 49(C).
    22. Ali, Heba & Hegazy, Aya Yasser, 2022. "Dividend policy, risk and the cross-section of stock returns: Evidence from India," International Review of Economics & Finance, Elsevier, vol. 79(C), pages 169-192.
    23. AlKhazali, Osamah M. & Lean, Hooi Hooi & Mirzaei, Ali & Zoubi, Taisier, 2021. "A comparison of the gold-oil portfolio and oil portfolio: A stochastic dominance approach," Finance Research Letters, Elsevier, vol. 40(C).
    24. 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.
    25. Sakurai, Yuji & Kurosaki, Tetsuo, 2020. "How has the relationship between oil and the US stock market changed after the Covid-19 crisis?," Finance Research Letters, Elsevier, vol. 37(C).
    26. Thi-Hong-Van Hoang & Zhenzhen Zhu & Abdelbari El Khamlichi & Wing-Keung Wong, 2019. "Does the Shari’ah screening impact the gold-stock nexus? A sectorial analysis," Post-Print hal-02179795, HAL.
    27. Awatef Ourir & Elie Bouri & Essahbi Essaadi, 2021. "Hedging the Risks of MENA Stock Markets with Gold: Evidence from the Spectral Approach," Working Papers 1511, Economic Research Forum, revised 20 Nov 2021.
    28. Wang, Xiangning & Huang, Qian & Zhang, Shuguang, 2023. "Effects of macroeconomic factors on stock prices for BRICS using the variational mode decomposition and quantile method," The North American Journal of Economics and Finance, Elsevier, vol. 67(C).
    29. Pavel Gertler & Roman Horváth & Júlia Jonášová, 2020. "Central Bank Communication and Financial Market Comovements in the Euro Area," Open Economies Review, Springer, vol. 31(2), pages 257-272, April.
    30. Beatriz de la Flor & Javier Ojea-Ferreiro & Eva Ferreira, 2022. "The Hedging Cost of Forgetting the Exchange Rate," Documentos de Trabajo del ICAE 2022-01, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    31. Wen, Fenghua & Tong, Xi & Ren, Xiaohang, 2022. "Gold or Bitcoin, which is the safe haven during the COVID-19 pandemic?," International Review of Financial Analysis, Elsevier, vol. 81(C).
    32. Amine Ben Amar & Jean‐Étienne Carlotti, 2021. "Who drives the dance? Further insights from a time‐frequency wavelet analysis of the interrelationship between stock markets and uncertainty," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 1623-1636, January.
    33. Dai, Xingyu & Wang, Qunwei & Zha, Donglan & Zhou, Dequn, 2020. "Multi-scale dependence structure and risk contagion between oil, gold, and US exchange rate: A wavelet-based vine-copula approach," Energy Economics, Elsevier, vol. 88(C).
    34. Mejri, Sami & Aloui, Chaker & Khan, Nasir, 2024. "The gold stock nexus: Assessing the causality dynamics based on advanced multiscale approaches," Resources Policy, Elsevier, vol. 88(C).
    35. Huang, Shupei & An, Haizhong & Huang, Xuan & Wang, Yue, 2018. "Do all sectors respond to oil price shocks simultaneously?," Applied Energy, Elsevier, vol. 227(C), pages 393-402.
    36. Semeyutin, Artur & Gozgor, Giray & Lau, Chi Keung Marco & Xu, Bing, 2021. "Effects of idiosyncratic jumps and co-jumps on oil, gold, and copper markets," Energy Economics, Elsevier, vol. 104(C).
    37. Liu, Ruipeng & Lux, Thomas, 2017. "Generalized Method of Moment estimation of multivariate multifractal models," Economic Modelling, Elsevier, vol. 67(C), pages 136-148.
    38. Shah, Adil Ahmad & Dar, Arif Billah, 2021. "Exploring diversification opportunities across commodities and financial markets: Evidence from time-frequency based spillovers," Resources Policy, Elsevier, vol. 74(C).
    39. Bhatia, Vaneet & Das, Debojyoti & Kumar, Surya Bhushan, 2020. "Hedging effectiveness of precious metals across frequencies: Evidence from Wavelet based Dynamic Conditional Correlation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 541(C).
    40. 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.
    41. Huang, Jianbai & Dong, Xuesong & Chen, Jinyu & Zhong, Meirui, 2022. "Do oil prices and economic policy uncertainty matter for precious metal returns? New insights from a TVP-VAR framework," International Review of Economics & Finance, Elsevier, vol. 78(C), pages 433-445.
    42. Tweneboah, George & Owusu Junior, Peterson & Kumah, Seyram Pearl, 2020. "Modelling the asymmetric linkages between spot gold prices and African stocks," Research in International Business and Finance, Elsevier, vol. 54(C).
    43. Sun, Qingru & Gao, Xiangyun & An, Haizhong & Guo, Sui & Liu, Xueyong & Wang, Ze, 2021. "Which time-frequency domain dominates spillover in the Chinese energy stock market?," International Review of Financial Analysis, Elsevier, vol. 73(C).
    44. Abdulrazak Nur Mohamed & Idiris Sid Ali Mohamed, 2023. "Precious Metals and Oil Price Dynamics," International Journal of Energy Economics and Policy, Econjournals, vol. 13(6), pages 119-128, November.
    45. Trabelsi, Nader & Gozgor, Giray & Tiwari, Aviral Kumar & Hammoudeh, Shawkat, 2021. "Effects of Price of Gold on Bombay Stock Exchange Sectoral Indices: New Evidence for Portfolio Risk Management," Research in International Business and Finance, Elsevier, vol. 55(C).
    46. Mensi, Walid & Ali, Syed Riaz Mahmood & Vo, Xuan Vinh & Kang, Sang Hoon, 2022. "Multiscale dependence, spillovers, and connectedness between precious metals and currency markets: A hedge and safe-haven analysis," Resources Policy, Elsevier, vol. 77(C).
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    48. Berna Kirkulak-Uludag & Zorikto Lkhamazhapov, 2017. "Volatility Dynamics of Precious Metals: Evidence from Russia," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 67(4), pages 300-317, August.
    49. Aviral Kumar Tiwari & Muhammad Tahir Suleman & Subhan Ullah & Muhammad Shahbaz, 2023. "Analyzing the connectedness between crude oil and petroleum products: Evidence from USA," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 2278-2347, July.
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    51. Hkiri, Besma & Hammoudeh, Shawkat & Aloui, Chaker & Shahbaz, Muhammad, 2018. "The interconnections between U.S. financial CDS spreads and control variables: New evidence using partial and multivariate wavelet coherences," International Review of Economics & Finance, Elsevier, vol. 57(C), pages 237-257.
    52. Oosterlinck, Kim & Reyns, Ariane & Szafarz, Ariane, 2023. "Gold, bitcoin, and portfolio diversification: Lessons from the Ukrainian war," Resources Policy, Elsevier, vol. 83(C).
    53. Mohamed Arbi Madani & Zied Ftiti, 2019. "The Generalisation of the DMCA Coefficient to Serve Distinguishing Between Hedge and Safe Haven Capabilities of the Gold," Papers 1912.12590, arXiv.org.
    54. Wadud, Sania & Gronwald, Marc & Durand, Robert B. & Lee, Seungho, 2023. "Co-movement between commodity and equity markets revisited—An application of the Thick Pen method," International Review of Financial Analysis, Elsevier, vol. 87(C).
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    56. Jammazi, Rania & Ferrer, Román & Jareño, Francisco & Shahzad, Syed Jawad Hussain, 2017. "Time-varying causality between crude oil and stock markets: What can we learn from a multiscale perspective?," International Review of Economics & Finance, Elsevier, vol. 49(C), pages 453-483.
    57. Hung, Ngo Thai, 2021. "Oil prices and agricultural commodity markets: Evidence from pre and during COVID-19 outbreak," Resources Policy, Elsevier, vol. 73(C).
    58. Maghyereh, Aktham I. & Abdoh, Hussein & Awartani, Basel, 2019. "Connectedness and hedging between gold and Islamic securities: A new evidence from time-frequency domain approaches," Pacific-Basin Finance Journal, Elsevier, vol. 54(C), pages 13-28.
    59. Feng, Sida & Huang, Shupei & Qi, Yabin & Liu, Xueyong & Sun, Qingru & Wen, Shaobo, 2018. "Network features of sector indexes spillover effects in China: A multi-scale view," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 461-473.
    60. 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.
    61. Dejan Zivkov & Marina Gajic-Glamoclija & Jelena Kovacevic & Sanja Loncar, 2020. "Inflation Uncertainty and Output Growth - Evidence from the Asia-Pacific Countries Based on the Multiscale Bayesian Quantile Inference," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 70(5), pages 461-486, November.
    62. Maghyereh, Aktham I. & Awartani, Basel & Abdoh, Hussein, 2019. "The co-movement between oil and clean energy stocks: A wavelet-based analysis of horizon associations," Energy, Elsevier, vol. 169(C), pages 895-913.
    63. Gil-Alana, Luis A. & Yaya, OlaOluwa S. & Awe, Olushina O., 2017. "Time series analysis of co-movements in the prices of gold and oil: Fractional cointegration approach," Resources Policy, Elsevier, vol. 53(C), pages 117-124.
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    65. Huang, Shupei & An, Haizhong & Gao, Xiangyun & Hao, Xiaoqing, 2016. "Unveiling heterogeneities of relations between the entire oil–stock interaction and its components across time scales," Energy Economics, Elsevier, vol. 59(C), pages 70-80.
    66. Li, Panpan & Dong, Zhiliang, 2020. "Time-varying network analysis of fluctuations between crude oil and Chinese and U.S. gold prices in different periods," Resources Policy, Elsevier, vol. 68(C).
    67. Esparcia, Carlos & Jareño, Francisco & Umar, Zaghum, 2022. "Revisiting the safe haven role of Gold across time and frequencies during the COVID-19 pandemic," The North American Journal of Economics and Finance, Elsevier, vol. 61(C).
    68. Shah, Adil Ahmad & Paul, Manas & Bhanja, Niyati & Dar, Arif Billah, 2021. "Dynamics of connectedness across crude oil, precious metals and exchange rate: Evidence from time and frequency domains," Resources Policy, Elsevier, vol. 73(C).
    69. Aktham Maghyereh & Basel Awartani & Abul Hassan, 2018. "Can gold be used as a hedge against the risks of Sharia-compliant securities? Application for Islamic portfolio management," Journal of Asset Management, Palgrave Macmillan, vol. 19(6), pages 394-412, October.
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    1. Astrid Ayala & Szabolcs Blazsek, 2018. "Equity market neutral hedge funds and the stock market: an application of score-driven copula models," Applied Economics, Taylor & Francis Journals, vol. 50(37), pages 4005-4023, August.
    2. Sekuła Paweł, 2019. "Causality Analysis Between Stock Market Indices," Financial Sciences. Nauki o Finansach, Sciendo, vol. 24(1), pages 74-93, March.
    3. Albulescu, Claudiu Tiberiu & Aubin, Christian & Goyeau, Daniel & Tiwari, Aviral Kumar, 2018. "Extreme co-movements and dependencies among major international exchange rates: A copula approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 56-69.
    4. Chaker Aloui & Hela BEN HAMIDA, 2015. "Estimation and Performance Assessment of Value-at-Risk and Expected Shortfall Based on Long-Memory GARCH-Class Models," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 65(1), pages 30-54, January.
    5. Reboredo, Juan C. & Tiwari, Aviral Kumar & Albulescu, Claudiu Tiberiu, 2015. "An analysis of dependence between Central and Eastern European stock markets," Economic Systems, Elsevier, vol. 39(3), pages 474-490.

  32. Jozef Barunik & Jiri Kukacka, 2013. "Realizing stock market crashes: stochastic cusp catastrophe model of returns under the time-varying volatility," Papers 1302.7036, arXiv.org, revised May 2013.

    Cited by:

    1. Michael S. Harr'e & Adam Harris & Scott McCallum, 2019. "Singularities and Catastrophes in Economics: Historical Perspectives and Future Directions," Papers 1907.05582, arXiv.org.
    2. Kukacka, Jiri & Barunik, Jozef, 2017. "Estimation of financial agent-based models with simulated maximum likelihood," Journal of Economic Dynamics and Control, Elsevier, vol. 85(C), pages 21-45.
    3. 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.
    4. Dennis Wesselbaum, 2017. "Catastrophe theory and the financial crisis," Scottish Journal of Political Economy, Scottish Economic Society, vol. 64(4), pages 376-391, September.
    5. Michael S. Harr'e, 2018. "Multi-agent Economics and the Emergence of Critical Markets," Papers 1809.01332, arXiv.org.
    6. Wang, J., 2015. "Can a stochastic cusp catastrophe model explain housing market crashes?," CeNDEF Working Papers 15-12, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    7. 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).
    8. Mohamed M. Mostafa, 2020. "Catastrophe Theory Predicts International Concern for Global Warming," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(3), pages 709-731, September.
    9. 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.
    10. Bolgorian, Meysam, 2019. "Can a cusp catastrophe model describe the effect of sanctions on exchange rates?," Economics Discussion Papers 2019-2, Kiel Institute for the World Economy (IfW Kiel).

  33. Filip Zikes & Jozef Barunik, 2013. "Semiparametric Conditional Quantile Models for Financial Returns and Realized Volatility," Papers 1308.4276, arXiv.org.

    Cited by:

    1. Gerlach, Richard & Wang, Chao, 2020. "Semi-parametric dynamic asymmetric Laplace models for tail risk forecasting, incorporating realized measures," International Journal of Forecasting, Elsevier, vol. 36(2), pages 489-506.
    2. Kawakami, Tabito, 2023. "Quantile prediction for Bitcoin returns using financial assets’ realized measures," Finance Research Letters, Elsevier, vol. 55(PA).
    3. Stefan Lyocsa & Peter Molnar & Igor Fedorko, 2016. "Forecasting Exchange Rate Volatility: The Case of the Czech Republic, Hungary and Poland," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 66(5), pages 453-475, October.
    4. Frantiv{s}ek v{C}ech & Jozef Barun'ik, 2018. "Panel quantile regressions for estimating and predicting the Value--at--Risk of commodities," Papers 1807.11823, arXiv.org.
    5. Giovanni Bonaccolto & Massimiliano Caporin, 2016. "The Determinants of Equity Risk and Their Forecasting Implications: A Quantile Regression Perspective," JRFM, MDPI, vol. 9(3), pages 1-25, July.
    6. Stanislav Anatolyev & Jozef Barunik, 2017. "Forecasting dynamic return distributions based on ordered binary choice," Papers 1711.05681, arXiv.org, revised Jan 2019.
    7. Jozef Barunik & Lubos Hanus, 2022. "Learning Probability Distributions in Macroeconomics and Finance," Papers 2204.06848, arXiv.org.
    8. Christophe Boucher & Gilles de Truchis & Elena Dumitrescu & Sessi Tokpavi, 2017. "Testing for Extreme Volatility Transmission with Realized Volatility Measures," EconomiX Working Papers 2017-20, University of Paris Nanterre, EconomiX.
    9. Lazar, Emese & Xue, Xiaohan, 2020. "Forecasting risk measures using intraday data in a generalized autoregressive score framework," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1057-1072.
    10. Christophe Boucher & Gilles de Truchis & Elena Ivona Dumitrescu & Sessi Tokpavi, 2017. "Testing for Extreme Volatility Transmission with Realized Volatility Measures," Working Papers hal-04141651, HAL.
    11. Baruník, Jozef & Čech, František, 2021. "Measurement of common risks in tails: A panel quantile regression model for financial returns," Journal of Financial Markets, Elsevier, vol. 52(C).
    12. Vincenzo Candila & Giampiero M. Gallo & Lea Petrella, 2020. "Mixed--frequency quantile regressions to forecast Value--at--Risk and Expected Shortfall," Papers 2011.00552, arXiv.org, revised Mar 2023.
    13. Zongwu Cai & Chaoqun Ma & Xianhua Mi, 2020. "Realized Volatility Forecasting Based on Dynamic Quantile Model Averaging," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202016, University of Kansas, Department of Economics, revised Sep 2020.
    14. Zhao, Yixiu & Upreti, Vineet & Cai, Yuzhi, 2021. "Stock returns, quantile autocorrelation, and volatility forecasting," International Review of Financial Analysis, Elsevier, vol. 73(C).
    15. Le, Trung Hai & Do, Hung Xuan & Nguyen, Duc Khuong & Sensoy, Ahmet, 2021. "Covid-19 pandemic and tail-dependency networks of financial assets," Finance Research Letters, Elsevier, vol. 38(C).
    16. Chao Wang & Richard Gerlach, 2019. "Semi-parametric Realized Nonlinear Conditional Autoregressive Expectile and Expected Shortfall," Papers 1906.09961, arXiv.org.
    17. Marco Bee & Luca Trapin, 2018. "Estimating and Forecasting Conditional Risk Measures with Extreme Value Theory: A Review," Risks, MDPI, vol. 6(2), pages 1-16, April.

  34. Jozef Barunik & Tomas Krehlik & Lukas Vacha, 2012. "Modeling and forecasting exchange rate volatility in time-frequency domain," Papers 1204.1452, arXiv.org, revised Feb 2015.

    Cited by:

    1. de Souza Vasconcelos, Camila & Hadad Júnior, Eli, 2023. "Forecasting exchange rate: A bibliometric and content analysis," International Review of Economics & Finance, Elsevier, vol. 83(C), pages 607-628.
    2. Wen, Danyan & Liu, Li & Wang, Yudong & Zhang, Yaojie, 2022. "Forecasting crude oil market returns: Enhanced moving average technical indicators," Resources Policy, Elsevier, vol. 76(C).
    3. Davood Pirayesh Neghab & Mucahit Cevik & M. I. M. Wahab, 2023. "Explaining Exchange Rate Forecasts with Macroeconomic Fundamentals Using Interpretive Machine Learning," Papers 2303.16149, arXiv.org.
    4. Baruník, Jozef & Ellington, Michael, 2024. "Persistence in financial connectedness and systemic risk," European Journal of Operational Research, Elsevier, vol. 314(1), pages 393-407.
    5. Kang, Sang Hoon & Maitra, Debasish & Dash, Saumya Ranjan & Brooks, Robert, 2019. "Dynamic spillovers and connectedness between stock, commodities, bonds, and VIX markets," Pacific-Basin Finance Journal, Elsevier, vol. 58(C).
    6. Aloui, Chaker & Shahzad, Syed Jawad Hussain & Hkiri, Besma & Hela, Ben Hamida & Khan, Muhammad Asif, 2021. "On the investors' sentiments and the Islamic stock-bond interplay across investments' horizons," Pacific-Basin Finance Journal, Elsevier, vol. 65(C).
    7. Deniz Erer, 2023. "The Impact of News Related Covid-19 on Exchange Rate Volatility:A New Evidence From Generalized Autoregressive Score Model," EKOIST Journal of Econometrics and Statistics, Istanbul University, Faculty of Economics, vol. 0(38), pages 105-126, June.
    8. Degiannakis, Stavros, 2017. "The one-trading-day-ahead forecast errors of intra-day realized volatility," Research in International Business and Finance, Elsevier, vol. 42(C), pages 1298-1314.
    9. Maitra, Debasish & Dash, Saumya Ranjan, 2017. "Sentiment and stock market volatility revisited: A time–frequency domain approach," Journal of Behavioral and Experimental Finance, Elsevier, vol. 15(C), pages 74-91.
    10. Chen-Yu Tai & Wun-Jhe Wang & Yueh-Min Huang, 2023. "Using Time-Series Generative Adversarial Networks to Synthesize Sensing Data for Pest Incidence Forecasting on Sustainable Agriculture," Sustainability, MDPI, vol. 15(10), pages 1-24, May.
    11. Boakye, Robert Owusu & Mensah, Lord Kwaku & Kang, Sang Hoon & Osei, Kofi Acheampong, 2023. "Foreign exchange market return spillovers and connectedness among African countries," International Review of Financial Analysis, Elsevier, vol. 86(C).
    12. Baruník, Jozef & Hlínková, Michaela, 2016. "Revisiting the long memory dynamics of the implied–realized volatility relationship: New evidence from the wavelet regression," Economic Modelling, Elsevier, vol. 54(C), pages 503-514.
    13. Shahzad, Umer & Ghaemi Asl, Mahdi & Khalfaoui, Rabeh & Tedeschi, Marco, 2024. "Extreme contributions of conventional investments vis-à-vis Islamic ones to renewables," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    14. Leong, Soon Heng & Urga, Giovanni, 2023. "A practical multivariate approach to testing volatility spillover," Journal of Economic Dynamics and Control, Elsevier, vol. 153(C).
    15. Xu Gong & Boqiang Lin, 2018. "Structural breaks and volatility forecasting in the copper futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(3), pages 290-339, March.
    16. Bonato, Matteo & Cepni, Oguzhan & Gupta, Rangan & Pierdzioch, Christian, 2023. "Climate risks and realized volatility of major commodity currency exchange rates," Journal of Financial Markets, Elsevier, vol. 62(C).
    17. Escobar-Anel, Marcos & Rastegari, Javad & Stentoft, Lars, 2021. "Option pricing with conditional GARCH models," European Journal of Operational Research, Elsevier, vol. 289(1), pages 350-363.
    18. Idoko Ahmed Itodo & Ojonugwa Usman & Michael Maju Abu, 2017. "The Asymmetric Effect in the Volatility of the South African Rand," Academic Journal of Economic Studies, Faculty of Finance, Banking and Accountancy Bucharest,"Dimitrie Cantemir" Christian University Bucharest, vol. 3(3), pages 47-53, September.
    19. Ma, Feng & Wang, Jiqian & Wahab, M.I.M. & Ma, Yuanhui, 2023. "Stock market volatility predictability in a data-rich world: A new insight," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1804-1819.
    20. Kraicova, Lucie & Barunik, Jozef, 2015. "Estimation of long memory in volatility using wavelets," FinMaP-Working Papers 33, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    21. Guglielmo Maria Caporale & Menelaos Karanasos & Stavroula Yfanti, 2024. "Macro‐financial linkages in the high‐frequency domain: Economic fundamentals and the Covid‐induced uncertainty channel in US and UK financial markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(2), pages 1581-1608, April.
    22. M. Karanasos & S. Yfanti & J. Hunter, 2022. "Emerging stock market volatility and economic fundamentals: the importance of US uncertainty spillovers, financial and health crises," Annals of Operations Research, Springer, vol. 313(2), pages 1077-1116, June.
    23. Salisu, Afees A. & Cuñado, Juncal & Gupta, Rangan, 2022. "Geopolitical risks and historical exchange rate volatility of the BRICS," International Review of Economics & Finance, Elsevier, vol. 77(C), pages 179-190.
    24. Semeyutin, Artur & Gozgor, Giray & Lau, Chi Keung Marco & Xu, Bing, 2021. "Effects of idiosyncratic jumps and co-jumps on oil, gold, and copper markets," Energy Economics, Elsevier, vol. 104(C).
    25. Degiannakis, Stavros & Filis, George & Hassani, Hossein, 2018. "Forecasting global stock market implied volatility indices," Journal of Empirical Finance, Elsevier, vol. 46(C), pages 111-129.
    26. Albulescu, Claudiu Tiberiu & Aubin, Christian & Goyeau, Daniel & Tiwari, Aviral Kumar, 2018. "Extreme co-movements and dependencies among major international exchange rates: A copula approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 56-69.
    27. Yong Shi & Wei Dai & Wen Long & Bo Li, 2021. "Deep Kernel Gaussian Process Based Financial Market Predictions," Papers 2105.12293, arXiv.org.
    28. Bartsch, Zachary, 2019. "Economic policy uncertainty and dollar-pound exchange rate return volatility," Journal of International Money and Finance, Elsevier, vol. 98(C), pages 1-1.
    29. Barunik, Jozef & Vacha, Lukas, 2018. "Do co-jumps impact correlations in currency markets?," Journal of Financial Markets, Elsevier, vol. 37(C), pages 97-119.
    30. Luo, Changqing & Liu, Lan & Wang, Da, 2021. "Multiscale financial risk contagion between international stock markets: Evidence from EMD-Copula-CoVaR analysis," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    31. Xu Gong & Boqiang Lin, 2021. "Effects of structural changes on the prediction of downside volatility in futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(7), pages 1124-1153, July.
    32. Jozef Barunik & Michaela Barunikova, 2012. "Revisiting the fractional cointegrating dynamics of implied-realized volatility relation with wavelet band spectrum regression," Papers 1208.4831, arXiv.org, revised Feb 2013.
    33. Bošnjak Mile & Kordić Gordana & Bilas Vlatka, 2018. "Determinants Of Financial Euroisation In A Small Open Economy: The Case Of Serbia," Economic Annals, Faculty of Economics and Business, University of Belgrade, vol. 63(218), pages 9-22, July – Se.
    34. Ma, Feng & Wahab, M.I.M. & Zhang, Yaojie, 2019. "Forecasting the U.S. stock volatility: An aligned jump index from G7 stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 54(C), pages 132-146.
    35. Stelios Bekiros & Jose Arreola Hernandez & Gazi Salah Uddin & Ahmed Taneem Muzaffar, 2020. "On the predictability of crude oil market: A hybrid multiscale wavelet approach," Post-Print hal-02956380, HAL.
    36. Ganbold, Batzorig & Akram, Iqra & Fahrozi Lubis, Raisal, 2017. "Exchange rate volatility: A forecasting approach of using the ARCH family along with ARIMA SARIMA and semi-structural-SVAR in Turkey," MPRA Paper 84447, University Library of Munich, Germany, revised 2017.
    37. Gabriel Rodríguez & Junior A. Ojeda Cunya & José Carlos Gonzáles Tanaka, 2019. "An empirical note about estimation and forecasting Latin American Forex returns volatility: the role of long memory and random level shifts components," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 18(2), pages 107-123, June.
    38. Horta, Eduardo & Ziegelmann, Flavio, 2018. "Dynamics of financial returns densities: A functional approach applied to the Bovespa intraday index," International Journal of Forecasting, Elsevier, vol. 34(1), pages 75-88.
    39. Peng, Lijuan & Pan, Zhigang & Liang, Chao & Umar, Muhammad, 2023. "Exchange rate volatility predictability: A new insight from climate policy uncertainty," Economic Analysis and Policy, Elsevier, vol. 80(C), pages 688-700.
    40. Buccheri, Giuseppe & Corsi, Fulvio & Flandoli, Franco & Livieri, Giulia, 2021. "The continuous-time limit of score-driven volatility models," Journal of Econometrics, Elsevier, vol. 221(2), pages 655-675.
    41. Fu, Sibao & Li, Yongwu & Sun, Shaolong & Li, Hongtao, 2019. "Evolutionary support vector machine for RMB exchange rate forecasting," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 692-704.
    42. Degiannakis, Stavros & Filis, George & Hassani, Hossein, 2015. "Forecasting implied volatility indices worldwide: A new approach," MPRA Paper 72084, University Library of Munich, Germany.
    43. Bian, Siyu & Serra, Teresa & Garcia, Philip & Irwin, Scott, 2022. "New evidence on market response to public announcements in the presence of microstructure noise," European Journal of Operational Research, Elsevier, vol. 298(2), pages 785-800.
    44. Jozef Barunik & Pavel Fiser, 2019. "Co-jumping of Treasury Yield Curve Rates," Papers 1905.01541, arXiv.org.
    45. Lin, Boqiang & Su, Tong, 2021. "Do China's macro-financial factors determine the Shanghai crude oil futures market?," International Review of Financial Analysis, Elsevier, vol. 78(C).
    46. Semeyutin, Artur & Downing, Gareth, 2022. "Co-jumps in the U.S. interest rates and precious metals markets and their implications for investors," International Review of Financial Analysis, Elsevier, vol. 81(C).

  35. Jiri Kukacka & Jozef Barunik, 2012. "Behavioural breaks in the heterogeneous agent model: the impact of herding, overconfidence, and market sentiment," Papers 1205.3763, arXiv.org, revised May 2013.

    Cited by:

    1. Kukacka, Jiri & Barunik, Jozef, 2017. "Estimation of financial agent-based models with simulated maximum likelihood," Journal of Economic Dynamics and Control, Elsevier, vol. 85(C), pages 21-45.
    2. 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.
    3. Jan Polach & Jiri Kukacka, 2019. "Prospect Theory in the Heterogeneous Agent Model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(1), pages 147-174, March.
    4. Jia, Linlu & Ke, Jinchuan & Wang, Jun, 2019. "Volatility aggregation intensity energy futures series on stochastic finite-range exclusion dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 370-383.
    5. Rodrigo Fernandes Malaquias & Gleison de Abreu Pontes, 2018. "Liquidity Restrictions on Investment Funds: Are they a Response to Behavioral Bias?," Brazilian Business Review, Fucape Business School, vol. 15(4), pages 382-390, July.
    6. Marvello Yang & Abdullah Al Mamun & Muhammad Mohiuddin & Sayed Samer Ali Al-Shami & Noor Raihani Zainol, 2021. "Predicting Stock Market Investment Intention and Behavior among Malaysian Working Adults Using Partial Least Squares Structural Equation Modeling," Mathematics, MDPI, vol. 9(8), pages 1-16, April.
    7. Heba M. Ezzat, 2019. "Disposition effect and multi-asset market dynamics," Review of Behavioral Finance, Emerald Group Publishing Limited, vol. 11(2), pages 144-164, June.
    8. 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).
    9. da Silva, Eduardo Borges & Silva, Thiago Christiano & Constantino, Michel & Amancio, Diego Raphael & Tabak, Benjamin Miranda, 2020. "Overconfidence and the 2D:4D ratio," Journal of Behavioral and Experimental Finance, Elsevier, vol. 25(C).
    10. Yuri Biondi & Simone Righi, 2013. "What does the financial market pricing do? A simulation analysis with a view to systemic volatility, exuberance and vagary," Papers 1312.7460, arXiv.org.
    11. Suman Gupta & Vinay Goyal & Vinay Kumar Kalakbandi & Sankarshan Basu, 2018. "Overconfidence, trading volume and liquidity effect in Asia’s Giants: evidence from pre-, during- and post-global recession," DECISION: Official Journal of the Indian Institute of Management Calcutta, Springer;Indian Institute of Management Calcutta, vol. 45(3), pages 235-257, September.
    12. 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.
    13. Zhong, Li-Xin & Xu, Wen-Juan & Chen, Rong-Da & Zhong, Chen-Yang & Qiu, Tian & Ren, Fei & He, Yun-Xing, 2018. "Self-reinforcing feedback loop in financial markets with coupling of market impact and momentum traders," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 493(C), pages 301-310.

  36. Jozef Barunik & Michaela Barunikova, 2012. "Revisiting the fractional cointegrating dynamics of implied-realized volatility relation with wavelet band spectrum regression," Papers 1208.4831, arXiv.org, revised Feb 2013.

    Cited by:

    1. Silvia Muzzioli, 2013. "The Optimal Corridor for Implied Volatility: from Calm to Turmoil Periods," Department of Economics (DEMB) 0029, University of Modena and Reggio Emilia, Department of Economics "Marco Biagi".
    2. Imlak Shaikh & Puja Padhi, 2014. "The forecasting performance of implied volatility index: evidence from India VIX," Economic Change and Restructuring, Springer, vol. 47(4), pages 251-274, November.

  37. Filip Zikes & Jozef Barunik & Nikhil Shenai, 2012. "Modeling and Forecasting Persistent Financial Durations," Papers 1208.3087, arXiv.org, revised Apr 2013.

    Cited by:

    1. Chiranjit Dutta & Kara Karpman & Sumanta Basu & Nalini Ravishanker, 2023. "Review of Statistical Approaches for Modeling High-Frequency Trading Data," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 1-48, May.
    2. Marcin Wk{a}torek & Jaros{l}aw Kwapie'n & Stanis{l}aw Dro.zd.z, 2022. "Multifractal cross-correlations of bitcoin and ether trading characteristics in the post-COVID-19 time," Papers 2208.01445, arXiv.org.
    3. Bjoern Schulte-Tillmann & Mawuli Segnon & Timo Wiedemann, 2023. "A comparison of high-frequency realized variance measures: Duration- vs. return-based approaches," CQE Working Papers 10523, Center for Quantitative Economics (CQE), University of Muenster.
    4. Marcin Wątorek & Jarosław Kwapień & Stanisław Drożdż, 2022. "Multifractal Cross-Correlations of Bitcoin and Ether Trading Characteristics in the Post-COVID-19 Time," Future Internet, MDPI, vol. 14(7), pages 1-15, July.
    5. Xin-Lan Fu & Xing-Lu Gao & Zheng Shan & Zhi-Qiang Jiang & Wei-Xing Zhou, 2018. "Multifractal characteristics and return predictability in the Chinese stock markets," Papers 1806.07604, arXiv.org.
    6. Mawuli Segnon & Stelios Bekiros & Bernd Wilfling, 2018. "Forecasting Inflation Uncertainty in the G7 Countries," CQE Working Papers 7118, Center for Quantitative Economics (CQE), University of Muenster.
    7. Zhicheng Li & Haipeng Xing, 2022. "High-Frequency Quote Volatility Measurement Using a Change-Point Intensity Model," Mathematics, MDPI, vol. 10(4), pages 1-24, February.

  38. Lukas Vacha & Jozef Barunik, 2012. "Co-movement of energy commodities revisited: Evidence from wavelet coherence analysis," Papers 1201.4776, arXiv.org.

    Cited by:

    1. 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).
    2. Marchese, Malvina & Kyriakou, Ioannis & Tamvakis, Michael & Di Iorio, Francesca, 2020. "Forecasting crude oil and refined products volatilities and correlations: New evidence from fractionally integrated multivariate GARCH models," Energy Economics, Elsevier, vol. 88(C).
    3. Cai, Xiao Jing & Tian, Shuairu & Yuan, Nannan & Hamori, Shigeyuki, 2017. "Interdependence between oil and East Asian stock markets: Evidence from wavelet coherence analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 48(C), pages 206-223.
    4. Monge, Manuel & Poza, Carlos & Borgia, Sofía, 2022. "A proposal of a suspicion of tax fraud indicator based on Google trends to foresee Spanish tax revenues," International Economics, Elsevier, vol. 169(C), pages 1-12.
    5. Avishek Bhandari & Kamaiah Bandi, 2018. "On the Dynamics of Inflation-Stock Returns in India," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 16(1), pages 89-99, March.
    6. 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).
    7. Chang, Chun-Ping & Lee, Chien-Chiang, 2015. "Do oil spot and futures prices move together?," Energy Economics, Elsevier, vol. 50(C), pages 379-390.
    8. Özmen, M. Utku & Yılmaz, Erdal, 2017. "Co-movement of exchange rates with interest rate differential, risk premium and FED policy in “fragile economies”," Emerging Markets Review, Elsevier, vol. 33(C), pages 173-188.
    9. Saeed Sazzad Jeris & Ridoy Deb Nath, 2021. "US banks in the time of COVID-19: fresh insights from the wavelet approach," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 11(2), pages 349-361, June.
    10. Kılıç, Yunus & Destek, Mehmet Akif & Cevik, Emrah Ismail & Bugan, Mehmet Fatih & Korkmaz, Oya & Dibooglu, Sel, 2022. "Return and Risk Spillovers between ESG Global Index and Stock Markets: Evidence from Time and Frequency Analysis," MPRA Paper 117557, University Library of Munich, Germany.
    11. Umar, Zaghum & Gubareva, Mariya, 2021. "Faith-based investments and the Covid-19 pandemic: Analyzing equity volatility and media coverage time-frequency relations," Pacific-Basin Finance Journal, Elsevier, vol. 67(C).
    12. Hanus, Lubos & Vacha, Lukas, 2015. "Business cycle synchronization of the Visegrad Four and the European Union," FinMaP-Working Papers 42, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    13. Jiang, Yonghong & Nie, He & Monginsidi, Joe Yohanes, 2017. "Co-movement of ASEAN stock markets: New evidence from wavelet and VMD-based copula tests," Economic Modelling, Elsevier, vol. 64(C), pages 384-398.
    14. Luís Aguiar-Conraria & Maria Joana Soares & Rita Sousa, 2017. "California´s Carbon Market and Energy Prices: A Wavelet Analysis," NIPE Working Papers 13/2017, NIPE - Universidade do Minho.
    15. Sipan Aslan & Ceylan Yozgatligil & Cem Iyigun, 2018. "Temporal clustering of time series via threshold autoregressive models: application to commodity prices," Annals of Operations Research, Springer, vol. 260(1), pages 51-77, January.
    16. Haniff, Norazza Mohd & Masih, Mansur, 2016. "Shariah stocks as an inflation hedge in Malaysia," MPRA Paper 71681, University Library of Munich, Germany.
    17. Cai, Guixin & Zhang, Hao & Chen, Ziyue, 2019. "Comovement between commodity sectors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 1247-1258.
    18. 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).
    19. 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.
    20. 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).
    21. Gazi Salah Uddin & Jose Areola Hernandez & Syed Jawad Hussain Shahzad & Seong-Min Yoon, 2018. "Time-varying evidence of efficiency, decoupling, and diversification of conventional and Islamic stocks," Post-Print hal-01997844, HAL.
    22. Ross C Phillips & Denise Gorse, 2018. "Cryptocurrency price drivers: Wavelet coherence analysis revisited," PLOS ONE, Public Library of Science, vol. 13(4), pages 1-21, April.
    23. Bilgili, Faik & Kuşkaya, Sevda & Toğuç, Nurhan & Muğaloğlu, Erhan & Koçak, Emrah & Bulut, Ümit & Bağlıtaş, H. Hilal, 2019. "A revisited renewable consumption-growth nexus: A continuous wavelet approach through disaggregated data," Renewable and Sustainable Energy Reviews, Elsevier, vol. 107(C), pages 1-19.
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    144. Jozef Barunik & Michaela Barunikova, 2012. "Revisiting the fractional cointegrating dynamics of implied-realized volatility relation with wavelet band spectrum regression," Papers 1208.4831, arXiv.org, revised Feb 2013.
    145. Azza Bejaoui & Wajdi Frikha & Ahmed Jeribi, 2023. "On the dynamic connectedness between the G7 stock market indices and different asset classes: Fresh insights from the COVID-19 pandemic and Russia–Ukraine war," SN Business & Economics, Springer, vol. 3(11), pages 1-21, November.
    146. 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).
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    194. Athanasios Tsagkanos & Aarzoo Sharma & Bikramaditya Ghosh, 2022. "Green Bonds and Commodities: A New Asymmetric Sustainable Relationship," Sustainability, MDPI, vol. 14(11), pages 1-16, June.
    195. Buerhan Saiti & Azlan Ali & Naziruddin Abdullah & Sulaiman Sajilan, 2014. "Palm Oil Price, Exchange Rate, and Stock Market: A Wavelet Analysis on the Malaysian Market," Eurasian Journal of Economics and Finance, Eurasian Publications, vol. 2(1), pages 13-27.
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    200. Hanif, Waqas & Mensi, Walid & Gubareva, Mariya & Teplova, Tamara, 2023. "Impacts of COVID-19 on dynamic return and volatility spillovers between rare earth metals and renewable energy stock markets," Resources Policy, Elsevier, vol. 80(C).
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    202. Dejan Zivkov & Suzana Balaban & Jasmina Djuraskovic, 2018. "What Multiscale Approach Can Tell About the Nexus Between Exchange Rate and Stocks in the Major Emerging Markets?," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 68(5), pages 491-512, October.
    203. Gandjon Fankem, Gislain Stéphane & Fouda Mbesa, Lucien Cédric, 2023. "Business cycle synchronization and African monetary union: A wavelet analysis," Journal of Macroeconomics, Elsevier, vol. 77(C).
    204. Rubaiyat Ahsan Bhuiyan & Afzol Husain & Changyong Zhang, 2023. "Diversification evidence of bitcoin and gold from wavelet analysis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-36, December.
    205. Syed Abul, Basher, 2019. "Oil and other energy commodities," MPRA Paper 97318, University Library of Munich, Germany.
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    207. Adil Yilmaz & Gazanfer Unal, 2016. "Co-movement analysis of Asian stock markets against FTSE100 and S&P 500: Wavelet-based approach," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 3(04), pages 1-19, December.
    208. Chen, Qitong & Zhu, Huiming & Yu, Dongwei & Hau, Liya, 2022. "How does investor attention matter for crude oil prices and returns? Evidence from time-frequency quantile causality analysis," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
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    216. Kang, Sang Hoon & Tiwari, Aviral Kumar & Albulescu, Claudiu Tiberiu & Yoon, Seong-Min, 2019. "Time-frequency co-movements between the largest nonferrous metal futures markets," Resources Policy, Elsevier, vol. 61(C), pages 393-398.
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    221. Naeem, Muhammad Abubakr & Husain, Afzol & Bossman, Ahmed & Karim, Sitara, 2024. "Assessing the linkage of energy cryptocurrency with clean and dirty energy markets," Energy Economics, Elsevier, vol. 130(C).
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  39. Jozef Barunik & Lukas Vacha, 2012. "Realized wavelet-based estimation of integrated variance and jumps in the presence of noise," Papers 1202.1854, arXiv.org, revised Feb 2013.

    Cited by:

    1. Faria, Gonçalo & Verona, Fabio, 2017. "Forecasting the equity risk premium with frequency-decomposed predictors," Bank of Finland Research Discussion Papers 1/2017, Bank of Finland.
    2. Aloui, Chaker & Shahzad, Syed Jawad Hussain & Hkiri, Besma & Hela, Ben Hamida & Khan, Muhammad Asif, 2021. "On the investors' sentiments and the Islamic stock-bond interplay across investments' horizons," Pacific-Basin Finance Journal, Elsevier, vol. 65(C).
    3. Hathroubi, Salem & Aloui, Chaker, 2022. "Oil price dynamics and fiscal policy cyclicality in Saudi Arabia: New evidence from partial and multiple wavelet coherences," The Quarterly Review of Economics and Finance, Elsevier, vol. 85(C), pages 149-160.
    4. Faria, Gonçalo & Verona, Fabio, 2020. "Time-frequency forecast of the equity premium," Bank of Finland Research Discussion Papers 6/2020, Bank of Finland.
    5. Baruník, Jozef & Hlínková, Michaela, 2016. "Revisiting the long memory dynamics of the implied–realized volatility relationship: New evidence from the wavelet regression," Economic Modelling, Elsevier, vol. 54(C), pages 503-514.
    6. Gonçalo Faria & Fabio Verona, 2016. "Forecasting stock market returns by summing the frequency-decomposed parts," Working Papers de Economia (Economics Working Papers) 05, Católica Porto Business School, Universidade Católica Portuguesa.
    7. Faria, Gonçalo & Verona, Fabio, 2020. "The yield curve and the stock market: Mind the long run," Journal of Financial Markets, Elsevier, vol. 50(C).
    8. Kraicova, Lucie & Barunik, Jozef, 2015. "Estimation of long memory in volatility using wavelets," FinMaP-Working Papers 33, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    9. Semeyutin, Artur & Gozgor, Giray & Lau, Chi Keung Marco & Xu, Bing, 2021. "Effects of idiosyncratic jumps and co-jumps on oil, gold, and copper markets," Energy Economics, Elsevier, vol. 104(C).
    10. Barunik, Jozef & Krehlik, Tomas & Vacha, Lukas, 2016. "Modeling and forecasting exchange rate volatility in time-frequency domain," European Journal of Operational Research, Elsevier, vol. 251(1), pages 329-340.
    11. Barunik, Jozef & Vacha, Lukas, 2018. "Do co-jumps impact correlations in currency markets?," Journal of Financial Markets, Elsevier, vol. 37(C), pages 97-119.
    12. Barunik, Jozef & Barunikova, Michaela, 2015. "Revisiting the long memory dynamics of implied-realized volatility relation: A new evidence from wavelet band spectrum regression," FinMaP-Working Papers 43, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    13. Jozef Barunik & Michaela Barunikova, 2012. "Revisiting the fractional cointegrating dynamics of implied-realized volatility relation with wavelet band spectrum regression," Papers 1208.4831, arXiv.org, revised Feb 2013.
    14. Faria, Gonçalo & Verona, Fabio, 2020. "Frequency-domain information for active portfolio management," Bank of Finland Research Discussion Papers 2/2020, Bank of Finland.
    15. Kim C. Raath & Katherine B. Ensor, 2023. "Wavelet-L2E Stochastic Volatility Models: an Application to the Water-Energy Nexus," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 150-176, May.
    16. Takaki Hayashi & Yuta Koike, 2017. "Multi-scale analysis of lead-lag relationships in high-frequency financial markets," Papers 1708.03992, arXiv.org, revised May 2020.
    17. Kshatriya, Saranya & Prasanna, Krishna, 2021. "Jump Interdependencies: Stochastic linkages among international stock markets," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    18. Naeem, Muhammad Abubakr & Husain, Afzol & Bossman, Ahmed & Karim, Sitara, 2024. "Assessing the linkage of energy cryptocurrency with clean and dirty energy markets," Energy Economics, Elsevier, vol. 130(C).
    19. Semeyutin, Artur & Downing, Gareth, 2022. "Co-jumps in the U.S. interest rates and precious metals markets and their implications for investors," International Review of Financial Analysis, Elsevier, vol. 81(C).

  40. Jozef Barunik & Tomaso Aste & Tiziana Di Matteo & Ruipeng Liu, 2012. "Understanding the source of multifractality in financial markets," Papers 1201.1535, arXiv.org, revised Jan 2012.

    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. Francesco Caravelli & James Requeima & Cozmin Ududec & Ali Ashtari & Tiziana Di Matteo & Tomaso Aste, 2015. "Multi-scaling of wholesale electricity prices," Papers 1507.06219, arXiv.org.
    3. Noemi Nava & T. Di Matteo & Tomaso Aste, 2015. "Anomalous volatility scaling in high frequency financial data," Papers 1503.08465, arXiv.org, revised Dec 2015.
    4. Ladislav Kristoufek, 2013. "Testing power-law cross-correlations: Rescaled covariance test," Papers 1307.4727, arXiv.org, revised Aug 2013.
    5. 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.
    6. 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.
    7. 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).
    8. Zhan, Cun & Liang, Chuan & Zhao, Lu & Zhang, Yaling & Cheng, Long & Jiang, Shouzheng & Xing, Liwen, 2021. "Multifractal characteristics analysis of daily reference evapotranspiration in different climate zones of China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 583(C).
    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. Salat, Hadrien & Murcio, Roberto & Arcaute, Elsa, 2017. "Multifractal methodology," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 467-487.
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    20. 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.
    21. 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.
    22. 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.
    23. Xiao, Di & Wang, Jun, 2021. "Attitude interaction for financial price behaviours by contact system with small-world network topology," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 572(C).
    24. Aurelio F. Bariviera, 2020. "One model is not enough: heterogeneity in cryptocurrencies' multifractal profiles," Papers 2003.09720, arXiv.org, revised Jun 2020.
    25. 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.
    26. 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.
    27. Stošić, Darko & Stošić, Dusan & Stošić, Tatijana & Stanley, H. Eugene, 2015. "Multifractal analysis of managed and independent float exchange rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 13-18.
    28. Lee, Hojin & Chang, Woojin, 2015. "Multifractal regime detecting method for financial time series," Chaos, Solitons & Fractals, Elsevier, vol. 70(C), pages 117-129.
    29. Liu, Zhicao & Ye, Yong & Ma, Feng & Liu, Jing, 2017. "Can economic policy uncertainty help to forecast the volatility: A multifractal perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 181-188.
    30. Ruan, Qingsong & Zhang, Manqian & Lv, Dayong & Yang, Haiquan, 2018. "SAD and stock returns revisited: Nonlinear analysis based on MF-DCCA and Granger test," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 1009-1022.
    31. Saâdaoui, Foued, 2023. "Skewed multifractal scaling of stock markets during the COVID-19 pandemic," Chaos, Solitons & Fractals, Elsevier, vol. 170(C).
    32. Saâdaoui, Foued, 2018. "Testing for multifractality of Islamic stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 263-273.
    33. Riccardo Junior Buonocore & Tomaso Aste & Tiziana Di Matteo, 2015. "Measuring multiscaling in financial time-series," Papers 1509.05471, arXiv.org, revised Sep 2015.
    34. 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.
    35. 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.
    36. Mensi, Walid & Sensoy, Ahmet & Vo, Xuan Vinh & Kang, Sang Hoon, 2020. "Impact of COVID-19 outbreak on asymmetric multifractality of gold and oil prices," Resources Policy, Elsevier, vol. 69(C).
    37. John Goddard & Enrico Onali, 2016. "Long memory and multifractality: A joint test," Papers 1601.00903, arXiv.org.
    38. Lee, Hojin & Song, Jae Wook & Chang, Woojin, 2016. "Multifractal Value at Risk model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 113-122.
    39. Fernandes, Leonardo H.S. & Araújo, Fernando H.A. & Silva, Igor E.M. & Leite, Urbanno P.S. & de Lima, Neílson F. & Stosic, Tatijana & Ferreira, Tiago A.E., 2020. "Multifractal behavior in the dynamics of Brazilian inflation indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 550(C).
    40. Sensoy, Ahmet & Hacihasanoglu, Erk, 2014. "Time-varying long range dependence in energy futures markets," Energy Economics, Elsevier, vol. 46(C), pages 318-327.
    41. 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).
    42. 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.
    43. Faheem Aslam & Paulo Ferreira & Haider Ali & Ana Ercília José, 2022. "Application of Multifractal Analysis in Estimating the Reaction of Energy Markets to Geopolitical Acts and Threats," Sustainability, MDPI, vol. 14(10), pages 1-23, May.
    44. 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).
    45. Shen, Na & Chen, Jiayi, 2023. "Asymmetric multifractal spectrum distribution based on detrending moving average cross-correlation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 615(C).
    46. Cao, Guangxi & Cao, Jie & Xu, Longbing, 2013. "Asymmetric multifractal scaling behavior in the Chinese stock market: Based on asymmetric MF-DFA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(4), pages 797-807.
    47. Pagnottoni, Paolo & Spelta, Alessandro & Flori, Andrea & Pammolli, Fabio, 2022. "Climate change and financial stability: Natural disaster impacts on global stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 599(C).
    48. Krenar Avdulaj & Ladislav Kristoufek, 2020. "On Tail Dependence and Multifractality," Mathematics, MDPI, vol. 8(10), pages 1-13, October.
    49. Schadner, Wolfgang, 2022. "U.S. Politics from a multifractal perspective," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
    50. Wei, Yu & Chen, Wang & Lin, Yu, 2013. "Measuring daily Value-at-Risk of SSEC index: A new approach based on multifractal analysis and extreme value theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(9), pages 2163-2174.
    51. da Fonseca, Eder Lucio & Ferreira, Fernando F. & Muruganandam, Paulsamy & Cerdeira, Hilda A., 2013. "Identifying financial crises in real time," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(6), pages 1386-1392.
    52. 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.
    53. 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.
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    2. Ladislav Kristoufek, 2013. "Testing power-law cross-correlations: Rescaled covariance test," Papers 1307.4727, arXiv.org, revised Aug 2013.
    3. 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.
    4. 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.
    5. 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.
    6. Guglielmo Maria Caporale & Luis A. Gil-Alana & Alex Plastun, 2017. "Long Memory and Data Frequency in Financial Markets," CESifo Working Paper Series 6396, CESifo.
    7. 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.
    8. Ladislav Kristoufek, 2018. "Power-law cross-correlations: Issues, solutions and future challenges," Papers 1806.01616, arXiv.org.
    9. 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.
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    12. Ladislav Kristoufek & Miloslav Vosvrda, 2013. "Commodity futures and market efficiency," Papers 1309.1492, arXiv.org.
    13. 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).
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    15. 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).
    16. 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.
    17. 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.
    18. Kristoufek, Ladislav & Vosvrda, Miloslav, 2016. "Gold, currencies and market efficiency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 449(C), pages 27-34.
    19. Ladislav Kristoufek, 2016. "Power-law cross-correlations estimation under heavy tails," Papers 1602.05385, arXiv.org, revised Apr 2016.
    20. Ladislav Kristoufek & Miloslav Vosvrda, 2012. "Measuring capital market efficiency: Global and local correlations structure," Papers 1208.1298, arXiv.org.
    21. Rypdal, Martin & Sirnes, Espen & Løvsletten, Ola & Rypdal, Kristoffer, 2013. "Assessing market uncertainty by means of a time-varying intermittency parameter for asset price fluctuations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(16), pages 3335-3343.
    22. 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.
    23. 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).
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    31. 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.
    32. 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.
    33. 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.
    34. 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.
    35. 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.
    36. 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.
    37. Ladislav Kristoufek, 2012. "Fractal Markets Hypothesis and the Global Financial Crisis: Scaling, Investment Horizons and Liquidity," Papers 1203.4979, arXiv.org.
    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. 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.
    40. 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.
    41. 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.
    42. 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.
    43. Lee, Hojin & Chang, Woojin, 2015. "Multifractal regime detecting method for financial time series," Chaos, Solitons & Fractals, Elsevier, vol. 70(C), pages 117-129.
    44. 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.
    45. 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.
    46. 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.
    47. 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.
    48. Riccardo Junior Buonocore & Tomaso Aste & Tiziana Di Matteo, 2015. "Measuring multiscaling in financial time-series," Papers 1509.05471, arXiv.org, revised Sep 2015.
    49. 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.
    50. Jebabli, Ikram & Roubaud, David, 2018. "Time-varying efficiency in food and energy markets: Evidence and implications," Economic Modelling, Elsevier, vol. 70(C), pages 97-114.
    51. 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.
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    54. 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.
    55. Ladislav Kristoufek, 2014. "Leverage effect in energy futures," Papers 1403.0064, arXiv.org.
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    57. 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).
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    63. 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.
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    65. 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).
    66. 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.
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    69. 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.
    70. 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).
    71. Aslan, Aylin & Sensoy, Ahmet, 2020. "Intraday efficiency-frequency nexus in the cryptocurrency markets," Finance Research Letters, Elsevier, vol. 35(C).
    72. 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.
    73. 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.
    74. 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.
    75. 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.
    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. 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.
    78. 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.
    79. 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.
    80. 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.
    81. 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.
    82. Kristoufek, Ladislav, 2010. "On spurious anti-persistence in the US stock indices," Chaos, Solitons & Fractals, Elsevier, vol. 43(1), pages 68-78.
    83. 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.
    84. 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.
    85. 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).
    86. 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.
    87. 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.
    88. 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.
    89. 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.
    90. 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.
    91. 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.
    92. 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.
    93. 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.
    94. 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.
    95. 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.
    96. 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.
    97. 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.
    98. 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.
    99. 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.
    100. Kristoufek, Ladislav, 2018. "Fractality in market risk structure: Dow Jones Industrial components case," Chaos, Solitons & Fractals, Elsevier, vol. 110(C), pages 69-75.
    101. 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.
    102. 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.
    103. 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).
    104. Goddard, John & Onali, Enrico, 2012. "Self-affinity in financial asset returns," International Review of Financial Analysis, Elsevier, vol. 24(C), pages 1-11.
    105. 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.

  42. Jozef Barunik & Lukas Vacha, 2012. "Monte Carlo-based tail exponent estimator," Papers 1201.4781, arXiv.org.

    Cited by:

    1. 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.

  43. 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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. Besma Hkiri & Juncal Cunado & Mehmet Balcilar & Rangan Gupta, 2021. "Time-varying relationship between conventional and unconventional monetary policies and risk aversion: international evidence from time- and frequency-domains," Empirical Economics, Springer, vol. 61(6), pages 2963-2983, December.
    7. Avishek BHANDARI, 2017. "Wavelets based multiscale analysis of select global equity returns," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(4(613), W), pages 75-88, Winter.
    8. 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.
    9. Çekin, Semih Emre & Hkiri, Besma & Tiwari, Aviral Kumar & Gupta, Rangan, 2020. "The relationship between monetary policy and uncertainty in advanced economies: Evidence from time- and frequency-domains," The Quarterly Review of Economics and Finance, Elsevier, vol. 78(C), pages 70-87.
    10. 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.
    11. Avishek Bhandari, 2020. "A wavelet analysis of inter-dependence, contagion and long memory among global equity markets," Papers 2003.14110, arXiv.org.
    12. 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.
    13. 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.

  44. Michal Franta & Jozef Barunik & Roman Horvath & Katerina Smidkova, 2011. "Are Bayesian Fan Charts Useful for Central Banks? Uncertainty, Forecasting, and Financial Stability Stress Tests," Working Papers 2011/10, Czech National Bank.

    Cited by:

    1. Adam Gersl & Petr Jakubik & Tomas Konecny & Jakub Seidler, 2013. "Dynamic Stress Testing: The Framework for Assessing the Resilience of the Banking Sector Used by the Czech National Bank," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(6), pages 505-536, December.
    2. Robert Ambrisko & Vitezslav Augusta & Jan Babecky & Michal Franta & Dana Hajkova & Petr Kral & Jan Libich & Pavla Netusilova & Milan Rikovsky & Jakub Rysanek & Pavel Soukup & Petr Stehlik & Vilem Vale, 2013. "Macroeconomic Effects of Fiscal Policy," Occasional Publications - Edited Volumes, Czech National Bank, edition 2, volume 11, number rb11/2 edited by Jan Babecky & Kamil Galuscak, January.
    3. Adam Gersl & Petr Jakubik & Tomas Konecny & Jakub Seidler, 2012. "Dynamic Stress Testing: The Framework for Testing Banking Sector Resilience Used by the Czech National Bank," Working Papers 2012/11, Czech National Bank.
    4. Gatt, William, 2014. "Communicating uncertainty - a fan chart for HICP projections," MPRA Paper 59603, University Library of Munich, Germany.
    5. Horváth, Roman & Vaško, Dan, 2016. "Central bank transparency and financial stability," Journal of Financial Stability, Elsevier, vol. 22(C), pages 45-56.

  45. Jozef Barunik & Lukas Vacha & Miloslav Vosvrda, 2010. "Tail Behavior of the Central European Stock Markets during the Financial Crisis," Working Papers IES 2010/04, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Mar 2010.

    Cited by:

    1. Abootaleb Shirvani, 2020. "Stock Returns and Roughness Extreme Variations: A New Model for Monitoring 2008 Market Crash and 2015 Flash Crash," Applied Economics and Finance, Redfame publishing, vol. 7(3), pages 78-95, May.

  46. Jozef Barunik & Lukas Vacha, 2009. "Wavelet Analysis of Central European Stock Market Behaviour During the Crisis," Working Papers IES 2009/23, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Oct 2009.

    Cited by:

    1. Murat Yalcintas & Oyk㜠Iyigãœn & Gokhan Karabulut, 2023. "Personal Characteristics And Intention For Entrepreneurship," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 68(02), pages 539-561.

Articles

  1. Baruník, Jozef & Bevilacqua, Mattia & Faff, Robert, 2024. "Dynamic industry uncertainty networks and the business cycle," Journal of Economic Dynamics and Control, Elsevier, vol. 159(C).
    See citations under working paper version above.
  2. Baruník, Jozef & Ellington, Michael, 2024. "Persistence in financial connectedness and systemic risk," European Journal of Operational Research, Elsevier, vol. 314(1), pages 393-407.
    See citations under working paper version above.
  3. Jozef Barunik & Mattia Bevilacqua & Radu Tunaru, 2022. "Asymmetric Network Connectedness of Fears," The Review of Economics and Statistics, MIT Press, vol. 104(6), pages 1304-1316, November.
    See citations under working paper version above.
  4. Baruník, Jozef & Čech, František, 2021. "Measurement of common risks in tails: A panel quantile regression model for financial returns," Journal of Financial Markets, Elsevier, vol. 52(C).

    Cited by:

    1. de Castro, Luciano & Galvao, Antonio F. & Muchon, Andre, 2023. "Numerical Solution of Dynamic Quantile Models," Journal of Economic Dynamics and Control, Elsevier, vol. 148(C).
    2. Yousaf, Imran & Pham, Linh & Goodell, John W., 2023. "Interconnectedness between healthcare tokens and healthcare stocks: Evidence from a quantile VAR approach," International Review of Economics & Finance, Elsevier, vol. 86(C), pages 271-283.
    3. Siddique, Md Abubakar & Nobanee, Haitham & Karim, Sitara & Naz, Farah, 2023. "Do green financial markets offset the risk of cryptocurrencies and carbon markets?," International Review of Economics & Finance, Elsevier, vol. 86(C), pages 822-833.
    4. Cosmin Octavian Cepoi & Victor Dragotă & Ruxandra Trifan & Andreea Iordache, 2023. "Probability of informed trading during the COVID-19 pandemic: the case of the Romanian stock market," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-27, December.

  5. Anatolyev, Stanislav & Baruník, Jozef, 2019. "Forecasting dynamic return distributions based on ordered binary choice," International Journal of Forecasting, Elsevier, vol. 35(3), pages 823-835.
    See citations under working paper version above.
  6. Jozef Baruník & Tobias Kley, 2019. "Quantile coherency: A general measure for dependence between cyclical economic variables," The Econometrics Journal, Royal Economic Society, vol. 22(2), pages 131-152.
    See citations under working paper version above.
  7. František Čech & Jozef Baruník, 2019. "Panel quantile regressions for estimating and predicting the value‐at‐risk of commodities," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(9), pages 1167-1189, September.
    See citations under working paper version above.
  8. Barunik, Jozef & Vacha, Lukas, 2018. "Do co-jumps impact correlations in currency markets?," Journal of Financial Markets, Elsevier, vol. 37(C), pages 97-119.
    See citations under working paper version above.
  9. Jozef Baruník & Tomáš Křehlík, 2018. "Measuring the Frequency Dynamics of Financial Connectedness and Systemic Risk," Journal of Financial Econometrics, Oxford University Press, vol. 16(2), pages 271-296.
    See citations under working paper version above.
  10. Avdulaj Krenar & Barunik Jozef, 2017. "A semiparametric nonlinear quantile regression model for financial returns," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(1), pages 81-97, February.

    Cited by:

    1. Gerlach, Richard & Wang, Chao, 2020. "Semi-parametric dynamic asymmetric Laplace models for tail risk forecasting, incorporating realized measures," International Journal of Forecasting, Elsevier, vol. 36(2), pages 489-506.
    2. Michał Woźniak & Marcin Chlebus, 2021. "HCR & HCR-GARCH – novel statistical learning models for Value at Risk estimation," Working Papers 2021-10, Faculty of Economic Sciences, University of Warsaw.
    3. Chao Wang & Richard Gerlach, 2019. "Semi-parametric Realized Nonlinear Conditional Autoregressive Expectile and Expected Shortfall," Papers 1906.09961, arXiv.org.

  11. Kraicová Lucie & Baruník Jozef, 2017. "Estimation of long memory in volatility using wavelets," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(3), pages 1-22, June.
    See citations under working paper version above.
  12. Kukacka, Jiri & Barunik, Jozef, 2017. "Estimation of financial agent-based models with simulated maximum likelihood," Journal of Economic Dynamics and Control, Elsevier, vol. 85(C), pages 21-45.
    See citations under working paper version above.
  13. František Čech & Jozef Baruník, 2017. "On the Modelling and Forecasting of Multivariate Realized Volatility: Generalized Heterogeneous Autoregressive (GHAR) Model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(2), pages 181-206, March.
    See citations under working paper version above.
  14. Apergis, Nicholas & Baruník, Jozef & Lau, Marco Chi Keung, 2017. "Good volatility, bad volatility: What drives the asymmetric connectedness of Australian electricity markets?," Energy Economics, Elsevier, vol. 66(C), pages 108-115.

    Cited by:

    1. Hasan, Mudassar & Arif, Muhammad & Naeem, Muhammad Abubakr & Ngo, Quang-Thanh & Taghizadeh–Hesary, Farhad, 2021. "Time-frequency connectedness between Asian electricity sectors," Economic Analysis and Policy, Elsevier, vol. 69(C), pages 208-224.
    2. Lovcha, Yuliya & Perez-Laborda, Alejandro, 2020. "Dynamic frequency connectedness between oil and natural gas volatilities," Economic Modelling, Elsevier, vol. 84(C), pages 181-189.
    3. Zheng, Biao & Zhang, Yuquan W. & Yin, Haitao & Geng, Yong, 2021. "The limited role of stock market in financing new energy development in China: An investigation using firms’ high-frequency data," Economic Analysis and Policy, Elsevier, vol. 72(C), pages 651-667.
    4. Okorie, David Iheke & Lin, Boqiang, 2022. "Givers never lack: Nigerian oil & gas asymmetric network analyses," Energy Economics, Elsevier, vol. 108(C).
    5. Brice Kamguia & Ronald Djeunankan & Sosson Tadadjeu & Henri Njangang, 2024. "Does macroeconomic instability hamper access to electricity? Evidence from developing countries," Economics of Transition and Institutional Change, John Wiley & Sons, vol. 32(2), pages 387-414, April.
    6. Ma, Rufei & Liu, Zhenhua & Zhai, Pengxiang, 2022. "Does economic policy uncertainty drive volatility spillovers in electricity markets: Time and frequency evidence," Energy Economics, Elsevier, vol. 107(C).
    7. Singh, Vipul Kumar & Kumar, Pawan & Nishant, Shreyank, 2019. "Global connectedness of MSCI energy equity indices: A system-wide network approach," Energy Economics, Elsevier, vol. 84(C).
    8. Anwer, Zaheer & Naeem, Muhammad Abubakr & Hassan, M. Kabir & Karim, Sitara, 2022. "Asymmetric connectedness across Asia-Pacific currencies: Evidence from time-frequency domain analysis," Finance Research Letters, Elsevier, vol. 47(PB).
    9. Wang, Gang-Jin & Xie, Chi & Zhao, Longfeng & Jiang, Zhi-Qiang, 2018. "Volatility connectedness in the Chinese banking system: Do state-owned commercial banks contribute more?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 57(C), pages 205-230.
    10. Hung Do & Rabindra Nepal & Tooraj Jamasb, 2020. "Electricity market integration, decarbonisation and security of supply: Dynamic volatility connectedness in the Irish and Great Britain markets," CAMA Working Papers 2020-42, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    11. Apergis, Nicholas & Gozgor, Giray & Lau, Chi Keung Marco & Wang, Shixuan, 2020. "Dependence structure in the Australian electricity markets: New evidence from regular vine copulae," Energy Economics, Elsevier, vol. 90(C).
    12. Hung Do & Rabindra Nepal & Russell Smyth, 2020. "Interconnectedness in the Australian National Electricity Market: A Higher‐Moment Analysis," The Economic Record, The Economic Society of Australia, vol. 96(315), pages 450-469, December.
    13. Chanatásig-Niza, Evelyn & Ciarreta, Aitor & Zarraga, Ainhoa, 2022. "A volatility spillover analysis with realized semi(co)variances in Australian electricity markets," Energy Economics, Elsevier, vol. 111(C).
    14. 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).
    15. Carlo Andrea Bollino & Davide Ciferri & Paolo Polinori, 2013. "Integration and convergence in European electricity markets," Quaderni del Dipartimento di Economia, Finanza e Statistica 114/2013, Università di Perugia, Dipartimento Economia.
    16. Qiang Chen & Anush Balian & Mykola Kyzym & Tetiana Salashenko & Inna Gryshova & Viktoriia Khaustova, 2021. "Electricity Markets Instability: Causes of Price Dispersion," Sustainability, MDPI, vol. 13(22), pages 1-19, November.
    17. Guan, Bo & Mazouz, Khelifa & Xu, Yongdeng, 2024. "Asymmetric volatility spillover between crude oil and other asset markets," Energy Economics, Elsevier, vol. 130(C).
    18. Mensi, Walid & Shafiullah, Muhammad & Vo, Xuan Vinh & Kang, Sang Hoon, 2022. "Asymmetric spillovers and connectedness between crude oil and currency markets using high-frequency data," Resources Policy, Elsevier, vol. 77(C).
    19. David Iheke Okorie & Boqiang Lin, 2022. "Crude oil market and Nigerian stocks: An asymmetric information spillover approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4002-4017, October.
    20. Valadkhani, Abbas & Nguyen, Jeremy & Smyth, Russell, 2018. "Consumer electricity and gas prices across Australian capital cities: Structural breaks, effects of policy reforms and interstate differences," Energy Economics, Elsevier, vol. 72(C), pages 365-375.
    21. Yanbin Li & Dan Nie & Bingkang Li & Xiyu Li, 2020. "The Spillover Effect between Carbon Emission Trading (CET) Price and Power Company Stock Price in China," Sustainability, MDPI, vol. 12(16), pages 1-17, August.
    22. Michael Stanley Smith & Thomas S. Shively, 2018. "Econometric Modeling of Regional Electricity Spot Prices in the Australian Market," Papers 1804.08218, arXiv.org.
    23. Chenyan Lyu & Hung Xuan Do & Rabindra Nepal & Tooraj Jamasb, 2023. "Volatility Spillovers and Carbon Price in the Nordic Wholesale Electricity Markets," CAMA Working Papers 2023-36, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    24. Afees A. Salisu & Raymond Swaray, 2020. "Forecasting the Return Volatility of Energy Prices: A GARCH-MIDAS Approach," World Scientific Book Chapters, in: Stéphane Goutte & Duc Khuong Nguyen (ed.), HANDBOOK OF ENERGY FINANCE Theories, Practices and Simulations, chapter 3, pages 47-71, World Scientific Publishing Co. Pte. Ltd..
    25. Shi Chen & Wolfgang Karl Hardle & Brenda L'opez Cabrera, 2020. "Regularization Approach for Network Modeling of German Power Derivative Market," Papers 2009.09739, arXiv.org.
    26. Luo, Jiawen & Ji, Qiang, 2018. "High-frequency volatility connectedness between the US crude oil market and China's agricultural commodity markets," Energy Economics, Elsevier, vol. 76(C), pages 424-438.
    27. Abdullah, Mohammad & Abakah, Emmanuel Joel Aikins & Wali Ullah, G M & Tiwari, Aviral Kumar & Khan, Isma, 2023. "Tail risk contagion across electricity markets in crisis periods," Energy Economics, Elsevier, vol. 127(PB).
    28. Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna, 2019. "A Moving Average Heterogeneous Autoregressive Model for Forecasting the Realized Volatility of the US Stock Market: Evidence from Over a Century of Data," Working Papers 201978, University of Pretoria, Department of Economics.
    29. Lovcha, Yuliya & Perez-Laborda, Alejandro, 2022. "Long-memory and volatility spillovers across petroleum futures," Energy, Elsevier, vol. 243(C).
    30. Dan Nie & Yanbin Li & Xiyu Li & Xuejiao Zhou & Feng Zhang, 2022. "The Dynamic Spillover between Renewable Energy, Crude Oil and Carbon Market: New Evidence from Time and Frequency Domains," Energies, MDPI, vol. 15(11), pages 1-28, May.
    31. Hung Xuan Do & Rabindra Nepal & Son Duy Pham & Tooraj Jamasb, 2023. "Electricity Market Crisis in Europe and Cross Border Price Effects: A Quantile Return Connectedness Analysis," CAMA Working Papers 2023-46, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    32. Naeem, Muhammad Abubakr & Karim, Sitara & Rabbani, Mustafa Raza & Nepal, Rabindra & Uddin, Gazi Salah, 2022. "Market integration in the Australian National Electricity Market: Fresh evidence from asymmetric time-frequency connectedness," Energy Economics, Elsevier, vol. 112(C).
    33. Han, Lin & Kordzakhia, Nino & Trück, Stefan, 2020. "Volatility spillovers in Australian electricity markets," Energy Economics, Elsevier, vol. 90(C).
    34. Sirin, Selahattin Murat & Camadan, Ercument & Erten, Ibrahim Etem & Zhang, Alex Hongliang, 2023. "Market failure or politics? Understanding the motives behind regulatory actions to address surging electricity prices," Energy Policy, Elsevier, vol. 180(C).
    35. Zhang, Hanyu & Dufour, Alfonso, 2019. "Modeling intraday volatility of European bond markets: A data filtering application," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 131-146.
    36. Awaworyi Churchill, Sefa & Smyth, Russell & Farrell, Lisa, 2020. "Fuel poverty and subjective wellbeing," Energy Economics, Elsevier, vol. 86(C).
    37. Xiao, Jihong & Wang, Yudong, 2021. "Investor attention and oil market volatility: Does economic policy uncertainty matter?," Energy Economics, Elsevier, vol. 97(C).
    38. Wang, Hu & Li, Shouwei, 2021. "Asymmetric volatility spillovers between crude oil and China's financial markets," Energy, Elsevier, vol. 233(C).
    39. Wang, Ziwei & Li, Youwei & He, Feng, 2020. "Asymmetric volatility spillovers between economic policy uncertainty and stock markets: Evidence from China," Research in International Business and Finance, Elsevier, vol. 53(C).
    40. Apergis, Nicholas & Pan, Wei-Fong & Reade, James & Wang, Shixuan, 2023. "Modelling Australian electricity prices using indicator saturation," Energy Economics, Elsevier, vol. 120(C).
    41. Ji, Qiang & Bouri, Elie & Lau, Chi Keung Marco & Roubaud, David, 2019. "Dynamic connectedness and integration in cryptocurrency markets," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 257-272.
    42. Tang, Yumei & Chen, Xihui Haviour & Sarker, Provash Kumer & Baroudi, Sarra, 2023. "Asymmetric effects of geopolitical risks and uncertainties on green bond markets," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    43. Apergis, Nicholas & Gozgor, Giray & Lau, Chi Keung Marco & Wang, Shixuan, 2019. "Decoding the Australian electricity market: New evidence from three-regime hidden semi-Markov model," Energy Economics, Elsevier, vol. 78(C), pages 129-142.
    44. Zhang, Dongna & Dai, Xingyu & Wang, Qunwei & Lau, Chi Keung Marco, 2023. "Impacts of weather conditions on the US commodity markets systemic interdependence across multi-timescales," Energy Economics, Elsevier, vol. 123(C).

  15. Filip Žikeš & Jozef Baruník & Nikhil Shenai, 2017. "Modeling and forecasting persistent financial durations," Econometric Reviews, Taylor & Francis Journals, vol. 36(10), pages 1081-1110, November.
    See citations under working paper version above.
  16. Baruník, Jozef & Kočenda, Evžen & Vácha, Lukáš, 2017. "Asymmetric volatility connectedness on the forex market," Journal of International Money and Finance, Elsevier, vol. 77(C), pages 39-56.
    See citations under working paper version above.
  17. Křehlík, Tomáš & Baruník, Jozef, 2017. "Cyclical properties of supply-side and demand-side shocks in oil-based commodity markets," Energy Economics, Elsevier, vol. 65(C), pages 208-218.
    See citations under working paper version above.
  18. Baruník, Jozef & Hlínková, Michaela, 2016. "Revisiting the long memory dynamics of the implied–realized volatility relationship: New evidence from the wavelet regression," Economic Modelling, Elsevier, vol. 54(C), pages 503-514.

    Cited by:

    1. Cipollini, Andrea & Lo Cascio, Iolanda & Muzzioli, Silvia, 2018. "Risk aversion connectedness in five European countries," Economic Modelling, Elsevier, vol. 71(C), pages 68-79.
    2. Xingxing He & Korhan K. Gokmenoglu & Dervis Kirikkaleli & Syed Kumail Abbas Rizvi, 2023. "Co‐movement of foreign exchange rate returns and stock market returns in an emerging market: Evidence from the wavelet coherence approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(2), pages 1994-2005, April.
    3. 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).
    4. 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.

  19. Barunik, Jozef & Krehlik, Tomas & Vacha, Lukas, 2016. "Modeling and forecasting exchange rate volatility in time-frequency domain," European Journal of Operational Research, Elsevier, vol. 251(1), pages 329-340.
    See citations under working paper version above.
  20. Baruník, Jozef & Malinská, Barbora, 2016. "Forecasting the term structure of crude oil futures prices with neural networks," Applied Energy, Elsevier, vol. 164(C), pages 366-379.
    See citations under working paper version above.
  21. Baruník, Jozef & Kočenda, Evžen & Vácha, Lukáš, 2016. "Gold, oil, and stocks: Dynamic correlations," International Review of Economics & Finance, Elsevier, vol. 42(C), pages 186-201.
    See citations under working paper version above.
  22. Filip Žikeš & Jozef Baruník, 2016. "Semi-parametric Conditional Quantile Models for Financial Returns and Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 14(1), pages 185-226.
    See citations under working paper version above.
  23. Baruník, Jozef & Kočenda, Evžen & Vácha, Lukáš, 2016. "Asymmetric connectedness on the U.S. stock market: Bad and good volatility spillovers," Journal of Financial Markets, Elsevier, vol. 27(C), pages 55-78.
    See citations under working paper version above.
  24. Baruník, Jozef & Dvořáková, Sylvie, 2015. "An empirical model of fractionally cointegrated daily high and low stock market prices," Economic Modelling, Elsevier, vol. 45(C), pages 193-206.

    Cited by:

    1. OlaOluwa S. Yaya & Xuan Vinh Vo & Ahamuefula E. Ogbonna & Adeolu O. Adewuyi, 2022. "Modelling cryptocurrency high–low prices using fractional cointegrating VAR," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 489-505, January.
    2. Alia Afzal & Philipp Sibbertsen, 2021. "Modeling fractional cointegration between high and low stock prices in Asian countries," Empirical Economics, Springer, vol. 60(2), pages 661-682, February.
    3. Søren Johansen & Morten Ørregaard Nielsen, 2018. "Nonstationary cointegration in the fractionally cointegrated VAR model," CREATES Research Papers 2018-17, Department of Economics and Business Economics, Aarhus University.
    4. Huang, Zhuo & Liu, Hao & Wang, Tianyi, 2016. "Modeling long memory volatility using realized measures of volatility: A realized HAR GARCH model," Economic Modelling, Elsevier, vol. 52(PB), pages 812-821.
    5. Monge, Manuel & Romero Rojo, María Fátima & Gil-Alana, Luis Alberiko, 2023. "The impact of geopolitical risk on the behavior of oil prices and freight rates," Energy, Elsevier, vol. 269(C).
    6. Monge, Manuel & Lazcano, Ana & Parada, José Luis, 2023. "Growth vs value investing: Persistence and time trend before and after COVID-19," Research in International Business and Finance, Elsevier, vol. 65(C).
    7. Cipollini, Andrea & Lo Cascio, Iolanda & Muzzioli, Silvia, 2018. "Risk aversion connectedness in five European countries," Economic Modelling, Elsevier, vol. 71(C), pages 68-79.
    8. Caporale, Guglielmo Maria & Gil-Alana, Luis A. & Poza, Carlos, 2020. "High and low prices and the range in the European stock markets: A long-memory approach," Research in International Business and Finance, Elsevier, vol. 52(C).
    9. Stoupos, Nikolaos & Kiohos, Apostolos, 2021. "Energy commodities and advanced stock markets: A post-crisis approach," Resources Policy, Elsevier, vol. 70(C).
    10. Yaya, OlaOluwa S & Gil-Alana, Luis A., 2018. "High and Low Intraday Commodity Prices: A Fractional Integration and Cointegration Approach," MPRA Paper 90518, University Library of Munich, Germany.

  25. Jozef Baruník, Evzen Kocenda and Lukáa Vácha, 2015. "Volatility Spillovers Across Petroleum Markets," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    See citations under working paper version above.
  26. Avdulaj, Krenar & Barunik, Jozef, 2015. "Are benefits from oil–stocks diversification gone? New evidence from a dynamic copula and high frequency data," Energy Economics, Elsevier, vol. 51(C), pages 31-44.
    See citations under working paper version above.
  27. Jozef Barunik & Lukas Vacha, 2015. "Realized wavelet-based estimation of integrated variance and jumps in the presence of noise," Quantitative Finance, Taylor & Francis Journals, vol. 15(8), pages 1347-1364, August.
    See citations under working paper version above.
  28. Jozef Barunik & Jiri Kukacka, 2015. "Realizing stock market crashes: stochastic cusp catastrophe model of returns under time-varying volatility," Quantitative Finance, Taylor & Francis Journals, vol. 15(6), pages 959-973, June.
    See citations under working paper version above.
  29. Michal Franta & Jozef Baruník & Roman Horváth & Katerina Smídková, 2014. "Are Bayesian Fan Charts Useful? The Effect of Zero Lower Bound and Evaluation of Financial Stability Stress Tests," International Journal of Central Banking, International Journal of Central Banking, vol. 10(1), pages 159-188, March.

    Cited by:

    1. Andrew Binning & Junior Maih, 2016. "Forecast uncertainty in the neighborhood of the effective lower bound: How much asymmetry should we expect?," Working Paper 2016/13, Norges Bank.
    2. Ahmad Razi & Po Ling Loke, 2017. "Fan Chart: The art and science of communicating uncertainty," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Statistical implications of the new financial landscape, volume 43, Bank for International Settlements.
    3. Jan Bruha & Jiri Polansky & Jaromir Tonner & Stanislav Tvrz & Osvald Vasicek & Jan Babecky & Kamil Galuscak & Lubomir Lizal & Diana Zigraiova, 2016. "Topics in Labour Markets," Occasional Publications - Edited Volumes, Czech National Bank, edition 1, volume 14, number rb14/1 edited by Jan Babecky, January.
    4. Christopher McDonald & Craig Thamotheram & Shaun P. Vahey & Elizabeth C. Wakerly, 2016. "Assessing the economic value of probabilistic forecasts in the presence of an inflation target," CAMA Working Papers 2016-40, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    5. Michal Franta, 2016. "The Effect of Nonlinearity between Credit Conditions and Economic Activity on Density Forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(2), pages 147-166, March.
    6. Oxana Babecka Kucharcukova & Alexis Derviz & Vaclav Hausenblas & Michal Hlavacek & Mark Joy & Narcisa Kadlcakova & Lubos Komarek & Zlatuse Komarkova & Tomas Konecny & Ivana Kubicova & Jitka Lesanovska, 2014. "Macroprudential Research: Selected Issues," Occasional Publications - Edited Volumes, Czech National Bank, edition 2, volume 12, number rb12/2 edited by Jan Babecky & Borek Vasicek, January.
    7. Farooq Akram & Andrew Binning & Junior Maih, 2016. "Joint Prediction Bands for Macroeconomic Risk Management," Working Papers No 5/2016, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    8. Ohnsorge,Franziska Lieselotte & Stocker,Marc & Some,Modeste Y., 2016. "Quantifying uncertainties in global growth forecasts," Policy Research Working Paper Series 7770, The World Bank.
    9. Miroslav Plasil & Jakub Seidler & Petr Hlavac & Volha Audzei & Jakub Mateju & Michal Kejak & Simona Malovana & Jan Frait, 2016. "Financial Cycles and Macroprudential and Monetary Policies," Occasional Publications - Edited Volumes, Czech National Bank, edition 2, volume 14, number rb14/2 edited by Jan Babecky & Michal Hlavacek, January.
    10. Malte Knüppel & Fabian Krüger, 2022. "Forecast uncertainty, disagreement, and the linear pool," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(1), pages 23-41, January.
    11. Michal Franta, 2015. "Rare Shocks vs. Non-linearities: What Drives Extreme Events in the Economy? Some Empirical Evidence," Working Papers 2015/04, Czech National Bank.
    12. Hamid Baghestani & Liliana Danila, 2014. "Interest Rate and Exchange Rate Forecasting in the Czech Republic: Do Analysts Know Better than a Random Walk?," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 64(4), pages 282-295, September.
    13. Milan Szabo & Zlatuse Komarkova & Martin Casta, 2020. "Vulnerable growth: Bayesian GDP-at-Risk," Occasional Publications - Chapters in Edited Volumes,, Czech National Bank.
    14. Kamil Galuscak & Adam Gersl & Marcela Gronychova & Petr Hlavac & Petr Jakubik & Lubos Komarek & Zlatuse Komarkova & Tomas Konecny & Jakub Seidler, 2014. "Stress-Testing Analyses of the Czech Financial System," Occasional Publications - Edited Volumes, Czech National Bank, edition 1, volume 12, number rb12/1 edited by Jan Babecky & Roman Horvath, January.
    15. Knüppel, Malte & Krüger, Fabian, 2017. "Forecast Uncertainty, Disagreement, and Linear Pools of Density Forecasts," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168294, Verein für Socialpolitik / German Economic Association.
    16. Irving Fisher Committee, 2017. "Statistical implications of the new financial landscape," IFC Bulletins, Bank for International Settlements, number 43.
    17. Lubomír Lízal & Jirí Schwarz, 2013. "Foreign exchange interventions as an (un)conventional monetary policy tool," BIS Papers chapters, in: Bank for International Settlements (ed.), Sovereign risk: a world without risk-free assets?, volume 73, pages 127-143, Bank for International Settlements.
    18. Frantisek Brazdik & Jan Bruha & Michal Franta & David Havrlant & Tibor Hledik & Tomas Holub & Zuzana Humplova & Frantisek Kopriva & Jiri Polansky & Marek Rusnak & Jaromir Tonner, 2015. "Forecasting," Occasional Publications - Edited Volumes, Czech National Bank, edition 1, volume 13, number rb13/1 edited by Jan Babecky & Kamil Galuscak, January.
    19. Michal Andrle & Oxana Babecka Kucharcukova & Jaromir Baxa & Jan Bruha & Peter Claeys & Jan Filacek & Jakub Mateju & Miroslav Plasil & Serhat Solmaz & Borek Vasicek, 2015. "Monetary Policy Challenges in a Low-Inflation Environment," Occasional Publications - Edited Volumes, Czech National Bank, edition 2, volume 13, number rb13/2 edited by Jan Babecky & Michal Franta, January.
    20. Damian Stelmasiak & Grzegorz Szafrański, 2016. "Forecasting the Polish Inflation Using Bayesian VAR Models with Seasonality," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 8(1), pages 21-42, March.
    21. Milan Szabo, 2020. "Growth-at-Risk: Bayesian Approach," Working Papers 2020/3, Czech National Bank.
    22. Michal Franta & Tomas Holub & Petr Kral & Ivana Kubicova & Katerina Smidkova & Borek Vasicek, 2014. "The Exchange Rate as an Instrument at Zero Interest Rates: The Case of the Czech Republic," Research and Policy Notes 2014/03, Czech National Bank.
    23. Jackson, Emerson Abraham & Tamuke, Edmund, 2021. "The Science and Art of Communicating Fan Chart Uncertainty: The case of Inflation Outcome in Sierra Leone," MPRA Paper 105892, University Library of Munich, Germany, revised 05 Jan 2021.

  30. Jozef BARUNÍK & Lukáš VÁCHA, 2013. "Contagion among Central and Eastern European Stock Markets during the Financial Crisis," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(5), pages 443-453, November.
    See citations under working paper version above.
  31. Kukacka, Jiri & Barunik, Jozef, 2013. "Behavioural breaks in the heterogeneous agent model: The impact of herding, overconfidence, and market sentiment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(23), pages 5920-5938.
    See citations under working paper version above.
  32. Krenar AVDULAJ & Jozef BARUNIK, 2013. "Can We Still Benefit from International Diversification? The Case of the Czech and German Stock Markets," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(5), pages 425-442, November.
    See citations under working paper version above.
  33. 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.

    Cited by:

    1. Kukacka, Jiri & Barunik, Jozef, 2017. "Estimation of financial agent-based models with simulated maximum likelihood," Journal of Economic Dynamics and Control, Elsevier, vol. 85(C), pages 21-45.
    2. Jan Polach & Jiri Kukacka, 2019. "Prospect Theory in the Heterogeneous Agent Model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(1), pages 147-174, March.
    3. Jiri Kukacka & Jozef Barunik, 2012. "Behavioural breaks in the heterogeneous agent model: the impact of herding, overconfidence, and market sentiment," Papers 1205.3763, arXiv.org, revised May 2013.

  34. Vacha, Lukas & Barunik, Jozef, 2012. "Co-movement of energy commodities revisited: Evidence from wavelet coherence analysis," Energy Economics, Elsevier, vol. 34(1), pages 241-247.
    See citations under working paper version above.
  35. 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.
    See citations under working paper version above.
  36. 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.
  37. Jozef Baruník & Branislav Soták, 2010. "Vplyv rôznych foriem vlastníctva na efektivitu českých a slovenských bánk: prístup analýzy stochastických hraníc [Influence of Different Ownership Forms on Efficiency of Czech and Slovak Banks: Sto," Politická ekonomie, Prague University of Economics and Business, vol. 2010(2), pages 207-224.

    Cited by:

    1. Iveta Palečková, 2015. "Banking efficiency in the Czech Republic and Slovakia using the DEA Window Analysis," Working Papers 0012, Silesian University, School of Business Administration.
    2. Esther Wanjugu Gitundu & Sifunjo E. Kisaka & Symon Kibet Kiprop & Lawrence Kangogo Kibet, 2016. "The Effects of Ownership and Corporate Governance Reforms on Efficiency of Privatized Companies in Kenya," International Journal of Economics and Financial Issues, Econjournals, vol. 6(1), pages 323-331.

  38. Jozef Baruník & Lukáš Vácha & Miloslav Vošvrda, 2010. "Tail Behavior of the Central European Stock Markets during the Financial Crisis," Czech Economic Review, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, vol. 4(3), pages 281-294, November.
    See citations under working paper version above.
  39. Barunik, Jozef & Vacha, Lukas, 2010. "Monte Carlo-based tail exponent estimator," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4863-4874.
    See citations under working paper version above.
  40. Barunik, J. & Vosvrda, M., 2009. "Can a stochastic cusp catastrophe model explain stock market crashes?," Journal of Economic Dynamics and Control, Elsevier, vol. 33(10), pages 1824-1836, October.

    Cited by:

    1. Kukacka, Jiri & Barunik, Jozef, 2017. "Estimation of financial agent-based models with simulated maximum likelihood," Journal of Economic Dynamics and Control, Elsevier, vol. 85(C), pages 21-45.
    2. Xu, Yan & Hu, Bin & Wu, Jiang & Zhang, Jianhua, 2014. "Nonlinear analysis of the cooperation of strategic alliances through stochastic catastrophe theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 400(C), pages 100-108.
    3. Chiarella, Carl & He, Xue-Zhong & Zheng, Min, 2011. "An analysis of the effect of noise in a heterogeneous agent financial market model," Journal of Economic Dynamics and Control, Elsevier, vol. 35(1), pages 148-162, January.

  41. Lukáš Vácha & Jozef Barunik & Miloslav Vošvrda, 2009. "Smart Agents and Sentiment in the Heterogeneous Agent Model," Prague Economic Papers, Prague University of Economics and Business, vol. 2009(3), pages 209-219.

    Cited by:

    1. Jiri Kukacka & Jozef Barunik, 2012. "Behavioural breaks in the heterogeneous agent model: the impact of herding, overconfidence, and market sentiment," Papers 1205.3763, arXiv.org, revised May 2013.

  42. Jozef Barunik & Lukas Vacha & Miloslav Vosvrda, 2009. "Smart predictors in the heterogeneous agent model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 4(2), pages 163-172, November.

    Cited by:

    1. Kukacka, Jiri & Barunik, Jozef, 2017. "Estimation of financial agent-based models with simulated maximum likelihood," Journal of Economic Dynamics and Control, Elsevier, vol. 85(C), pages 21-45.
    2. Jan Polach & Jiri Kukacka, 2019. "Prospect Theory in the Heterogeneous Agent Model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(1), pages 147-174, March.
    3. Jiri Kukacka & Jozef Barunik, 2012. "Behavioural breaks in the heterogeneous agent model: the impact of herding, overconfidence, and market sentiment," Papers 1205.3763, arXiv.org, revised May 2013.
    4. Gao-Feng Gu & Xiong Xiong & Hai-Chuan Xu & Wei Zhang & Yong-Jie Zhang & Wei Chen & Wei-Xing Zhou, 2017. "An empirical behavioural order-driven model with price limit rules," Papers 1704.04354, arXiv.org.
    5. 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.

  43. Jozef Baruník, 2008. "How Do Neural Networks Enhance the Predictability of Central European Stock Returns?," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 58(07-08), pages 358-376, Oktober.

    Cited by:

    1. Timotej Jagric & Vita Jagric & Davorin Kracun, 2011. "Does Non-linearity Matter in Retail Credit Risk Modeling?," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 61(4), pages 384-402, August.

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