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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. "Predicting the volatility of major energy commodity prices: the dynamic persistence model," Papers 2402.01354, arXiv.org, revised Jul 2024.

  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. Xuewei Zhou & Zisheng Ouyang & Rangan Gupta & Qiang Ji, 2024. "Time-Varying Multilayer Networks Analysis of Frequency Connectedness in Commodity Futures Markets," Working Papers 202422, University of Pretoria, Department of Economics.
    2. Huifu Nong, 2024. "Integration and risk transmission across supply, demand, and prices in China’s housing market," Economic Change and Restructuring, Springer, vol. 57(3), pages 1-28, June.
    3. 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. Jozef Barunik & Mattia Bevilacqua & Robert Faff, 2021. "Dynamic industry uncertainty networks and the business cycle," Papers 2101.06957, arXiv.org, revised Mar 2021.
    2. Xuewei Zhou & Zisheng Ouyang & Rangan Gupta & Qiang Ji, 2024. "Time-Varying Multilayer Networks Analysis of Frequency Connectedness in Commodity Futures Markets," Working Papers 202422, University of Pretoria, Department of Economics.
    3. Mykola Babiak & Jozef Barunik, 2021. "Currency Network Risk," Papers 2101.09738, arXiv.org, revised Jul 2021.

  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. 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.
    2. Jozef Barunik & Lubos Hanus, 2022. "Learning Probability Distributions in Macroeconomics and Finance," Papers 2204.06848, arXiv.org.
    3. Philippe Goulet Coulombe & Maximilian Goebel, 2023. "Maximally Machine-Learnable Portfolios," Papers 2306.05568, arXiv.org, revised Apr 2024.
    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. Qing Yang & Zhenning Hong & Ruyan Tian & Tingting Ye & Liangliang Zhang, 2020. "Asset Allocation via Machine Learning and Applications to Equity Portfolio Management," Papers 2011.00572, arXiv.org, revised Nov 2020.
    6. Penaranda, Francisco & Sentana, Enrique, 2024. "Portfolio management with big data," CEPR Discussion Papers 19314, C.E.P.R. Discussion Papers.

  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 & 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).
    2. 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).

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

    Cited by:

    1. Timo Dimitriadis & Yannick Hoga, 2023. "Regressions under Adverse Conditions," Papers 2311.13327, arXiv.org, revised Jul 2024.
    2. 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.
    3. Jozef Barunik & Mattia Bevilacqua & Robert Faff, 2021. "Dynamic industry uncertainty networks and the business cycle," Papers 2101.06957, arXiv.org, revised Mar 2021.
    4. 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.
    5. 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).
    6. Baruník, Jozef & Ellington, Michael, 2024. "Persistence in financial connectedness and systemic risk," European Journal of Operational Research, Elsevier, vol. 314(1), pages 393-407.
    7. 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).
    8. Maki, Daiki, 2024. "Evaluation of volatility spillovers for asymmetric realized covariance," The North American Journal of Economics and Finance, Elsevier, vol. 73(C).
    9. Jozef Barunik & Mattia Bevilacqua & Michael Ellington, 2023. "Common Firm-level Investor Fears: Evidence from Equity Options," Papers 2309.03968, arXiv.org.
    10. Ellington, Michael, 2022. "Fat tails, serial dependence, and implied volatility index connections," European Journal of Operational Research, Elsevier, vol. 299(2), pages 768-779.
    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. Niţoi, Mihai & Pochea, Maria Miruna, 2022. "The nexus between bank connectedness and investors’ sentiment," Finance Research Letters, Elsevier, vol. 44(C).
    13. 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.
    14. 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).
    15. 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).
    16. Ye, Liping & Geng, Jiang-Bo, 2021. "Measuring the connectedness of global health sector stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    17. Bevilacqua, Mattia & Tunaru, Radu & Vioto, Davide, 2023. "Options-based systemic risk, financial distress, and macroeconomic downturns," Journal of Financial Markets, Elsevier, vol. 65(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. 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).
    2. Tiwari, Aviral Kumar & Aikins Abakah, Emmanuel Joel & Doğan, Buhari & Adekoya, Oluwasegun B. & Wohar, Mark, 2024. "Asymmetric spillover effects in energy markets," International Review of Economics & Finance, Elsevier, vol. 92(C), pages 470-502.
    3. 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).
    4. Evžen Kočenda & Michala Moravcová & Evžen Kocenda, 2024. "Frequency Volatility Connectedness and Portfolio Hedging of U.S. Energy Commodities," CESifo Working Paper Series 10889, CESifo.
    5. 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).
    6. 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.
    7. 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).
    8. 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.
    9. 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.
    10. Mr. Adrian Alter & Mr. Selim A Elekdag, 2016. "Emerging Market Corporate Leverage and Global Financial Conditions," IMF Working Papers 2016/243, International Monetary Fund.
    11. 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).
    12. 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.
    13. Sophio Togonidze & Evzen Kocenda, 2020. "Macroeconomic Responses of Emerging Market Economies to Oil Price Shocks: Analysis by Region and Resource Profile," Working Papers IES 2020/35, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Sep 2020.
    14. 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).
    15. 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).
    16. 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.
    17. Vaclav Broz & Evzen Kocenda, 2020. "Mortgage-related bank penalties and systemic risk among U.S. banks," KIER Working Papers 1024, Kyoto University, Institute of Economic Research.
    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. 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).
    20. Nong, Huifu & Yu, Ziliang & Li, Yang, 2024. "Financial shock transmission in China's banking and housing sectors: A network analysis," Economic Analysis and Policy, Elsevier, vol. 82(C), pages 701-723.
    21. Fousekis, Panos & Tzaferi, Dimitra, 2021. "Returns and volume: Frequency connectedness in cryptocurrency markets," Economic Modelling, Elsevier, vol. 95(C), pages 13-20.
    22. 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).
    23. 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.
    24. 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).
    25. 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).
    26. 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).
    27. 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.
    28. Lovcha, Yuliya & Perez-Laborda, Alejandro, 2022. "Long-memory and volatility spillovers across petroleum futures," Energy, Elsevier, vol. 243(C).
    29. 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).
    30. 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).
    31. 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.
    32. Albrecht, Peter & Kočenda, Evžen, 2024. "Volatility connectedness on the central European forex markets," International Review of Financial Analysis, Elsevier, vol. 93(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. Shang, Jin & Hamori, Shigeyuki, 2024. "Quantile time-frequency connectedness analysis between crude oil, gold, financial markets, and macroeconomic indicators: Evidence from the US and EU," Energy Economics, Elsevier, vol. 132(C).
    35. 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.
    36. 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.
    37. Huynh, Toan Luu Duc, 2021. "Does Bitcoin React to Trump’s Tweets?," Journal of Behavioral and Experimental Finance, Elsevier, vol. 31(C).
    38. 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).

  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. 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.
    2. 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).
    3. 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.

  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. Baruník, Jozef & Hanus, Luboš, 2024. "Fan charts in era of big data and learning," Finance Research Letters, Elsevier, vol. 61(C).
    5. 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. 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.
    2. Giorgio Fagiolo & Mattia Guerini & Francesco Lamperti & Alessio Moneta & Andrea Roventini, 2019. "Validation of Agent-Based Models in Economics and Finance," Post-Print halshs-02375423, HAL.
    3. 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.
    4. Lamperti, Francesco, 2018. "An information theoretic criterion for empirical validation of simulation models," Econometrics and Statistics, Elsevier, vol. 5(C), pages 83-106.

  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. 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).
    2. 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).
    3. Aysan, Ahmet Faruk & Caporin, Massimiliano & Cepni, Oguzhan, 2024. "Not all words are equal: Sentiment and jumps in the cryptocurrency market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 91(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. Baruník Jozef & Fišer Pavel, 2024. "Co-Jumping of Treasury Yield Curve Rates," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 28(3), pages 481-506.
    6. 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).
    7. 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).
    8. 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.
    9. Karim, Sitara & Shafiullah, Muhammad & Naeem, Muhammad Abubakr, 2024. "When one domino falls, others follow: A machine learning analysis of extreme risk spillovers in developed stock markets," International Review of Financial Analysis, Elsevier, vol. 93(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. 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.
    2. 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).
    3. Tiwari, Aviral Kumar & Nasreen, Samia & Shahbaz, Muhammad & Hammoudeh, Shawkat, 2020. "Time-frequency causality and connectedness between international prices of energy, food, industry, agriculture and metals," Energy Economics, Elsevier, vol. 85(C).
    4. 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).
    5. 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.
    6. Lovcha, Yuliya & Perez-Laborda, Alejandro, 2020. "Dynamic frequency connectedness between oil and natural gas volatilities," Economic Modelling, Elsevier, vol. 84(C), pages 181-189.
    7. 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.
    8. 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.
    9. 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).
    10. 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).
    11. Gong, Xu & Xu, Jun, 2022. "Geopolitical risk and dynamic connectedness between commodity markets," Energy Economics, Elsevier, vol. 110(C).
    12. 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).
    13. 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.
    14. Lovcha, Yuliya & Perez-Laborda, Alejandro, 2022. "Long-memory and volatility spillovers across petroleum futures," Energy, Elsevier, vol. 243(C).
    15. 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).
    16. 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).
    17. 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).
    18. 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.
    19. 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.
    20. 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).

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    Cited by:

    1. Barde, Sylvain, 2024. "Bayesian estimation of large-scale simulation models with Gaussian process regression surrogates," Computational Statistics & Data Analysis, Elsevier, vol. 196(C).
    2. Zhang, Jinyu & Zhang, Qiaosen & Li, Yong & Wang, Qianchao, 2023. "Sequential Bayesian inference for agent-based models with application to the Chinese business cycle," Economic Modelling, Elsevier, vol. 126(C).
    3. Seri, Raffaello & Martinoli, Mario & Secchi, Davide & Centorrino, Samuele, 2021. "Model calibration and validation via confidence sets," Econometrics and Statistics, Elsevier, vol. 20(C), pages 62-86.
    4. Farmer, J. Doyne & Dyer, Joel & Cannon, Patrick & Schmon, Sebastian, 2022. "Black-box Bayesian inference for economic agent-based models," INET Oxford Working Papers 2022-05, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.
    5. Campiglio, Emanuele & Lamperti, Francesco & Terranova, Roberta, 2024. "Believe me when I say green! Heterogeneous expectations and climate policy uncertainty," LSE Research Online Documents on Economics 124234, London School of Economics and Political Science, LSE Library.
    6. Francesco Lamperti & Andrea Roventini & Amir Sani, 2017. "Agent-Based Model Calibration using Machine Learning Surrogates," Papers 1703.10639, arXiv.org, revised Apr 2017.
    7. Grazzini, Jakob & Richiardi, Matteo G. & Tsionas, Mike, 2017. "Bayesian estimation of agent-based models," Journal of Economic Dynamics and Control, Elsevier, vol. 77(C), pages 26-47.
    8. Shiono, Takashi, 2021. "Estimation of agent-based models using Bayesian deep learning approach of BayesFlow," Journal of Economic Dynamics and Control, Elsevier, vol. 125(C).
    9. Mario Martinoli & Alessio Moneta & Gianluca Pallante, 2022. "Calibration and Validation of Macroeconomic Simulation Models by Statistical Causal Search," LEM Papers Series 2022/33, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    10. Kukacka, Jiri & Jang, Tae-Seok & Sacht, Stephen, 2018. "On the estimation of behavioral macroeconomic models via simulated maximum likelihood," Economics Working Papers 2018-11, Christian-Albrechts-University of Kiel, Department of Economics.
    11. Domenico Delli Gatti & Jakob Grazzini, 2019. "Rising to the Challenge: Bayesian Estimation and Forecasting Techniques for Macroeconomic Agent-Based Models," CESifo Working Paper Series 7894, CESifo.
    12. 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.
    13. Mohammad Ghaderi, 2020. "Public Health Interventions in the Face of Pandemics: Network Structure, Social Distancing, and Heterogeneity," Working Papers 1193, Barcelona School of Economics.
    14. 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.
    15. Lucas Fievet & Didier Sornette, 2018. "Calibrating emergent phenomena in stock markets with agent based models," PLOS ONE, Public Library of Science, vol. 13(3), pages 1-17, March.
    16. Thorsten Hens & Klaus R. Schenk‐Hoppé, 2020. "Patience Is a Virtue: In Value Investing," International Review of Finance, International Review of Finance Ltd., vol. 20(4), pages 1019-1031, December.
    17. 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.
    18. Simone Berardi & Gabriele Tedeschi, 2016. "How banks’ strategies influence financial cycles: An approach to identifying micro behavior," Working Papers 2016/24, Economics Department, Universitat Jaume I, Castellón (Spain).
    19. Donovan Platt, 2019. "A Comparison of Economic Agent-Based Model Calibration Methods," Papers 1902.05938, arXiv.org.
    20. Özge Dilaver & Robert Jump & Paul Levine, 2016. "Agent-based Macroeconomics and Dynamic Stochastic General Equilibrium Models: Where do we go from here?," School of Economics Discussion Papers 0116, School of Economics, University of Surrey.
    21. Emna Mnif & Anis Jarboui & M. Kabir Hassan & Khaireddine Mouakhar, 2020. "Big data tools for Islamic financial analysis," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 27(1), pages 10-21, January.
    22. Filippo Gusella & Engelbert Stockhammer, 2020. "Testing fundamentalist-momentum trader financial cycles. An empirical analysis via the Kalman filter," Working Papers PKWP2009, Post Keynesian Economics Society (PKES).
    23. Filippo Gusella, 2022. "Detecting And Measuring Financial Cycles In Heterogeneous Agents Models: An Empirical Analysis," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 25(02n03), pages 1-22, March.
    24. 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).
    25. Barde, Sylvain, 2020. "Macroeconomic simulation comparison with a multivariate extension of the Markov information criterion," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
    26. Filippo Gusella, 2019. "Modelling Minskyan financial cycles with fundamentalist and extrapolative price strategies: An empirical analysis via the Kalman filter approach," Working Papers - Economics wp2019_24.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    27. Giorgio Fagiolo & Mattia Guerini & Francesco Lamperti & Alessio Moneta & Andrea Roventini, 2019. "Validation of Agent-Based Models in Economics and Finance," Post-Print halshs-02375423, HAL.
    28. Tilfani, Oussama & Kristoufek, Ladislav & Ferreira, Paulo & El Boukfaoui, My Youssef, 2022. "Heterogeneity in economic relationships: Scale dependence through the multivariate fractal regression," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 588(C).
    29. Grilli, Ruggero & Tedeschi, Gabriele & Gallegati, Mauro, 2020. "Business fluctuations in a behavioral switching model: Gridlock effects and credit crunch phenomena in financial networks," Journal of Economic Dynamics and Control, Elsevier, vol. 114(C).
    30. Filippo Gusella & Giorgio Ricchiuti, 2022. "A State-Space Approach for Time-Series Prediction of an Heterogeneous Agent Model," Working Papers - Economics wp2022_20.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    31. 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.
    32. Platt, Donovan, 2020. "A comparison of economic agent-based model calibration methods," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    33. Sylvain Barde, 2022. "Bayesian Estimation of Large-Scale Simulation Models with Gaussian Process Regression Surrogates," Studies in Economics 2203, School of Economics, University of Kent.
    34. Deborah Noguera & Gabriel Montes-Rojas, 2023. "Minskyan model with credit rationing in a network economy," SN Business & Economics, Springer, vol. 3(3), pages 1-26, March.
    35. Proaño, Christian R. & Kukacka, Jiri & Makarewicz, Tomasz, 2024. "Belief-driven dynamics in a behavioral SEIRD macroeconomic model with sceptics," Journal of Economic Behavior & Organization, Elsevier, vol. 217(C), pages 312-333.
    36. Domenico Delli Gatti & Filippo Gusella & Giorgio Ricchiuti, 2024. "Endogenous vs Exogenous Instability: An Out-of-Sample Comparison," CESifo Working Paper Series 11082, CESifo.
    37. Jan Polach & Jiri Kukacka, 2016. "Prospect Theory in the Heterogeneous Agent Model," Working Papers IES 2016/14, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Jul 2016.
    38. Dyer, Joel & Cannon, Patrick & Farmer, J. Doyne & Schmon, Sebastian M., 2024. "Black-box Bayesian inference for agent-based models," Journal of Economic Dynamics and Control, Elsevier, vol. 161(C).
    39. 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.
    40. Tubbenhauer, Tobias & Fieberg, Christian & Poddig, Thorsten, 2021. "Multi-agent-based VaR forecasting," Journal of Economic Dynamics and Control, Elsevier, vol. 131(C).
    41. Yanqiao Zheng & Xiaobing Zhao & Xiaoqi Zhang & Xinyue Ye & Qiwen Dai, 2019. "Mining the Hidden Link Structure from Distribution Flows for a Spatial Social Network," Complexity, Hindawi, vol. 2019, pages 1-17, May.
    42. Bewaji, Oluwasegun, 2024. "A computational model of bilateral credit limits in payment systems and other financial market infrastructures," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 5(1).
    43. 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.
    44. Tedeschi, Gabriele & Recchioni, Maria Cristina & Berardi, Simone, 2019. "An approach to identifying micro behavior: How banks’ strategies influence financial cycles," Journal of Economic Behavior & Organization, Elsevier, vol. 162(C), pages 329-346.
    45. Donovan Platt, 2022. "Bayesian Estimation of Economic Simulation Models Using Neural Networks," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 599-650, February.
    46. Ghaderi, Mohammad, 2022. "Public health interventions in the face of pandemics: Network structure, social distancing, and heterogeneity," European Journal of Operational Research, Elsevier, vol. 298(3), pages 1016-1031.
    47. Troost, Christian & Huber, Robert & Bell, Andrew R. & van Delden, Hedwig & Filatova, Tatiana & Le, Quang Bao & Lippe, Melvin & Niamir, Leila & Polhill, J. Gareth & Sun, Zhanli & Berger, Thomas, 2023. "How to keep it adequate: A protocol for ensuring validity in agent-based simulation," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 159, pages 1-21.
    48. Mohammad Ghaderi, 2020. "Public health interventions in the face of pandemics: network structure, social distancing, and heterogeneity," Economics Working Papers 1732, Department of Economics and Business, Universitat Pompeu Fabra.
    49. Serena Brianzoni & Giovanni Campisi & Graziella Pacelli, 2023. "Coexisting Attractors in a Heterogeneous Agent Model in Discrete Time," Mathematics, MDPI, vol. 11(10), pages 1-12, May.

  18. Jozef Barunik & Evzen Kocenda & Lukas Vacha, 2016. "Asymmetric volatility connectedness on forex markets," Papers 1607.08214, arXiv.org.

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    1. 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).
    2. 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).
    3. Okorie, David Iheke & Lin, Boqiang, 2022. "Givers never lack: Nigerian oil & gas asymmetric network analyses," Energy Economics, Elsevier, vol. 108(C).
    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. Stenfors, Alexis & Chatziantoniou, Ioannis & Gabauer, David, 2022. "Independent policy, dependent outcomes: A game of cross-country dominoes across European yield curves," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    6. 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).
    7. Pham, Linh & Huynh, Toan Luu Duc & Hanif, Waqas, 2023. "Time-varying asymmetric spillovers among cryptocurrency, green and fossil-fuel investments," Global Finance Journal, Elsevier, vol. 58(C).
    8. Gomez-Gonzalez, Jose Eduardo & Hirs-Garzon, Jorge & Uribe, Jorge M., 2020. "Spillovers beyond the variance: exploring the natural gas and oil higher order risk linkages with the global financial markets," Working papers 46, Red Investigadores de Economía.
    9. Tiwari, Aviral Kumar & Aikins Abakah, Emmanuel Joel & Doğan, Buhari & Adekoya, Oluwasegun B. & Wohar, Mark, 2024. "Asymmetric spillover effects in energy markets," International Review of Economics & Finance, Elsevier, vol. 92(C), pages 470-502.
    10. Guan, Bo & Mazouz, Khelifa & Xu, Yongdeng, 2024. "Asymmetric volatility spillover between crude oil and other asset markets," Energy Economics, Elsevier, vol. 130(C).
    11. 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.
    12. 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.
    13. Mensi, Walid & Ko, Hee-Un & Sensoy, Ahmet & Kang, Sang Hoon, 2024. "Higher-order moment connectedness between stock and commodity markets and portfolio management," Resources Policy, Elsevier, vol. 89(C).
    14. Fasanya, Ismail O. & Oyewole, Oluwatomisin J. & Oliyide, Johnson A., 2022. "Investors' sentiments and the dynamic connectedness between cryptocurrency and precious metals markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 86(C), pages 347-364.
    15. Kinkyo, Takuji, 2020. "Volatility interdependence on foreign exchange markets: The contribution of cross-rates," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    16. Chiang, Shu-hen & Chen, Chien-Fu, 2022. "From systematic to systemic risk among G7 members: Do the stock or real estate markets matter?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    17. Khyati Kathuria & Nand Kumar, 2022. "Pandemic‐induced fear and government policy response as a measure of uncertainty in the foreign exchange market: Evidence from (a)symmetric wild bootstrap likelihood ratio test," Pacific Economic Review, Wiley Blackwell, vol. 27(4), pages 361-379, October.
    18. 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).
    19. Z. Umar & O.B. Adekoya & M. Gubareva & Sabri Boubaker, 2023. "Returns and Volatility Connectedness among the EurozoDne Equity Markets," Post-Print hal-04434044, HAL.
    20. 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).
    21. Raza, Syed Ali & Guesmi, Khaled & Belaid, Fateh & Shah, Nida, 2022. "Time-frequency causality and connectedness between oil price shocks and the world food prices," Research in International Business and Finance, Elsevier, vol. 62(C).
    22. Bevilacqua, Mattia & Morelli, David & Tunaru, Radu, 2019. "The determinants of the model-free positive and negative volatilities," Journal of International Money and Finance, Elsevier, vol. 92(C), pages 1-24.
    23. Evžen Kocenda & Michala Moravcová, 2018. "Intraday Effect of News on Emerging European Forex Markets: An Event Study Analysis," CESifo Working Paper Series 7239, CESifo.
    24. Bouri, Elie & Lucey, Brian & Roubaud, David, 2020. "Dynamics and determinants of spillovers across the option-implied volatilities of US equities," The Quarterly Review of Economics and Finance, Elsevier, vol. 75(C), pages 257-264.
    25. Balcilar, Mehmet & Ozdemir, Zeynel Abidin & Ozdemir, Huseyin & Wohar, Mark E., 2020. "Transmission of US and EU Economic Policy Uncertainty Shock to Asian Economies in Bad and Good Times," IZA Discussion Papers 13274, Institute of Labor Economics (IZA).
    26. Zeng, Ting & Yang, Mengying & Shen, Yifan, 2020. "Fancy Bitcoin and conventional financial assets: Measuring market integration based on connectedness networks," Economic Modelling, Elsevier, vol. 90(C), pages 209-220.
    27. Wen, Tiange & Wang, Gang-Jin, 2020. "Volatility connectedness in global foreign exchange markets," Journal of Multinational Financial Management, Elsevier, vol. 54(C).
    28. Agudze, Komla & Ibhagui, Oyakhilome, 2020. "Oil Price Dynamics and Currency-Hedging Behavior," MPRA Paper 100949, University Library of Munich, Germany.
    29. 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.
    30. 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.
    31. 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.
    32. Amal Abricha & Amine Ben Amar & Makram Bellalah, 2024. "Commodity futures markets under stress and stress-free periods: Further insights from a quantile connectedness approach," Post-Print hal-04515196, HAL.
    33. 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).
    34. Mohammad Isleimeyyeh & Amine Ben Amar & Stéphane Goutte & Ramzi Benkraiem, 2022. "Commodity markets dynamics: What do cross-commodities over different nearest-to-maturities tell us?," Post-Print hal-03674806, HAL.
    35. Moeeni , Shahram & Tayebi , Komeil, 2018. "Is It Necessary to Restrict Forex Financial Trading? A Modified Model," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 13(1), pages 63-80, January.
    36. Gorman, Michael & Orlowski, Lucjan T. & Roessler, Matthew H., 2020. "Dynamic interactions between Central European currencies and the euro," Economic Systems, Elsevier, vol. 44(3).
    37. Salah Uddin, Gazi & Lucey, Brian & Rahman, Md Lutfur & Stenvall, David, 2024. "Quantile coherency across bonds, commodities, currencies, and equities," Journal of Commodity Markets, Elsevier, vol. 33(C).
    38. 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.
    39. Raza, Syed Ali & Guesmi, Khaled & Benkraiem, Ramzi & Anwar, Rija, 2024. "Precious metals and currency markets during the Russia-Ukraine conflict’s inflationary periods," Research in International Business and Finance, Elsevier, vol. 67(PA).
    40. Ying-Ying Shen & Zhi-Qiang Jiang & Jun-Chao Ma & Gang-Jin Wang & Wei-Xing Zhou, 2022. "Sector connectedness in the Chinese stock markets," Empirical Economics, Springer, vol. 62(2), pages 825-852, February.
    41. 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.
    42. Aikins Abakah, Emmanuel Joel & Gil-Alana, Luis A. & Arthur, Emmanuel Kwesi & Tiwari, Aviral Kumar, 2022. "Measuring volatility persistence in leveraged loan markets in the presence of structural breaks," International Review of Economics & Finance, Elsevier, vol. 78(C), pages 141-152.
    43. Balcilar, Mehmet & Ozdemir, Zeynel Abidin & Ozdemir, Huseyin & Wohar, Mark E., 2020. "Fed’s unconventional monetary policy and risk spillover in the US financial markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 78(C), pages 42-52.
    44. 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).
    45. Maghyereh, Aktham & Awartani, Basel & Virk, Nader S., 2022. "Asymmetric risk transmissions between oil, gold and US equities: Recent evidence from the realized variance of the futures prices," Resources Policy, Elsevier, vol. 79(C).
    46. Reboredo, Juan Carlos & Ugolini, Andrea & Hernandez, Jose Arreola, 2021. "Dynamic spillovers and network structure among commodity, currency, and stock markets," Resources Policy, Elsevier, vol. 74(C).
    47. 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.
    48. Evzen Kocenda & Michala Moravcova, 2017. "Exchange Rate Co-movements, Hedging and Volatility Spillovers in New EU Forex Markets," Working Papers IES 2017/27, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Nov 2017.
    49. Joseph Paul Chunga & Ping YU, 2024. "The impact of external shocks on volatility persistence and market efficiency of the foreign exchange rate regime: evidence from Malawi," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-14, December.
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    53. Suleman, Muhammad Tahir & McIver, Ron & Kang, Sang Hoon, 2021. "Asymmetric volatility connectedness between Islamic stock and commodity markets," Global Finance Journal, Elsevier, vol. 49(C).
    54. Kundan Mukhia & Anish Rai & SR Luwang & Md Nurujjaman & Sushovan Majhi & Chittaranjan Hens, 2024. "Complex network analysis of cryptocurrency market during crashes," Papers 2405.05642, arXiv.org.
    55. Zhang, Zhikai & Wang, Yudong & Li, Bin, 2023. "Asymmetric spillover of geopolitical risk and oil price volatility: A global perspective," Resources Policy, Elsevier, vol. 83(C).
    56. Shahzad, Syed Jawad Hussain & Naeem, Muhammad Abubakr & Peng, Zhe & Bouri, Elie, 2021. "Asymmetric volatility spillover among Chinese sectors during COVID-19," International Review of Financial Analysis, Elsevier, vol. 75(C).
    57. Mudassar Hasan & Muhammad Abubakr Naeem & Muhammad Arif & Syed Jawad Hussain Shahzad & Xuan Vinh Vo, 2022. "Liquidity connectedness in cryptocurrency market," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-25, December.
    58. Thai Hung, Ngo & Nguyen, Linh Thi My & Vinh Vo, Xuan, 2022. "Exchange rate volatility connectedness during Covid-19 outbreak: DECO-GARCH and Transfer Entropy approaches," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    59. Iqbal, Najaf & Naeem, Muhammad Abubakr & Suleman, Muhammed Tahir, 2022. "Quantifying the asymmetric spillovers in sustainable investments," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 77(C).
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    62. David Y. Aharon & Zaghum Umar & Xuan Vinh Vo, 2021. "Dynamic spillovers between the term structure of interest rates, bitcoin, and safe-haven currencies," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-25, December.
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    64. Maki, Daiki, 2024. "Evaluation of volatility spillovers for asymmetric realized covariance," The North American Journal of Economics and Finance, Elsevier, vol. 73(C).
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    66. 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).
    67. Abrar, Afsheen & Naeem, Muhammad Abubakr & Karim, Sitara & Lucey, Brian M. & Vigne, Samuel A., 2024. "Shining in or fading out: Do precious metals sparkle for cryptocurrencies?," Resources Policy, Elsevier, vol. 90(C).
    68. Chang, Ya-Ting & Gau, Yin-Feng & Hsu, Chih-Chiang, 2022. "Liquidity spillover in foreign exchange markets," Finance Research Letters, Elsevier, vol. 44(C).
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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. Chang, Shu-Lien & Lee, Yun-Huan, 2019. "Returns spillovers between tourism ETFs," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    4. 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.
    5. Sharma, Gagan Deep & Sarker, Tapan & Rao, Amar & Talan, Gaurav & Jain, Mansi, 2022. "Revisiting conventional and green finance spillover in post-COVID world: Evidence from robust econometric models," Global Finance Journal, Elsevier, vol. 51(C).
    6. 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.
    7. Aurelio F. Bariviera & Ignasi Merediz‐Solà, 2021. "Where Do We Stand In Cryptocurrencies Economic Research? A Survey Based On Hybrid Analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 377-407, April.
    8. 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.
    9. 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.
    10. 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).
    11. 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.
    12. 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).
    13. 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.
    14. 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).

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

    Cited by:

    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. Volker Seiler, 2024. "The relationship between Chinese and FOB prices of rare earth elements – Evidence in the time and frequency domain," Post-Print hal-04549980, HAL.
    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. 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.
    5. Yousaf, Imran & Mensi, Walid & Vo, Xuan Vinh & Kang, Sang Hoon, 2024. "Dynamic spillovers and connectedness between crude oil and green bond markets," Resources Policy, Elsevier, vol. 89(C).
    6. 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).
    7. Dai, Zhifeng & Zhu, Haoyang & Zhang, Xinhua, 2022. "Dynamic spillover effects and portfolio strategies between crude oil, gold and Chinese stock markets related to new energy vehicle," Energy Economics, Elsevier, vol. 109(C).
    8. Kingstone Nyakurukwa & Yudhvir Seetharam, 2023. "Higher moment connectedness of cryptocurrencies: a time-frequency approach," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 47(3), pages 793-814, September.
    9. Stenfors, Alexis & Chatziantoniou, Ioannis & Gabauer, David, 2022. "Independent policy, dependent outcomes: A game of cross-country dominoes across European yield curves," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    10. 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.
    11. Ben Salem, Leila & Zayati, Montassar & Nouira, Ridha & Rault, Christophe, 2024. "Volatility spillover between oil prices and main exchange rates: Evidence from a DCC-GARCH-connectedness approach," Resources Policy, Elsevier, vol. 91(C).
    12. Chen, Yanhui & Zhou, Xiaoyu & Chen, Shun & Mi, Jackson Jinhong, 2024. "LNG freight rate and LNG price, carbon price, geopolitical risk: A dynamic connectedness analysis," Energy, Elsevier, vol. 302(C).
    13. Ringstad, Ingrid Emilie Flessum & Tselika, Kyriaki, 2023. "Time and frequency dynamics of connectedness between green bonds, clean energy markets and carbon prices," Discussion Papers 2023/18, Norwegian School of Economics, Department of Business and Management Science.
    14. Aslanidis, Nektarios & Bariviera, Aurelio F. & Perez-Laborda, Alejandro, 2021. "Are cryptocurrencies becoming more interconnected?," Economics Letters, Elsevier, vol. 199(C).
    15. Gunay, Samet & Goodell, John W. & Muhammed, Shahnawaz & Kirimhan, Destan, 2023. "Frequency connectedness between FinTech, NFT and DeFi: Considering linkages to investor sentiment," International Review of Financial Analysis, Elsevier, vol. 90(C).
    16. Zhou, Yuqin & Wu, Shan & Zhang, Zeyi, 2022. "Multidimensional risk spillovers among carbon, energy and nonferrous metals markets: Evidence from the quantile VAR network," Energy Economics, Elsevier, vol. 114(C).
    17. Mehmet Balcilar & David Gabauer & Rangan Gupta & Christian Pierdzioch, 2023. "Climate Risks and Forecasting Stock Market Returns in Advanced Economies over a Century," Mathematics, MDPI, vol. 11(9), pages 1-21, April.
    18. Wei, Yu & Wang, Yizhi & Vigne, Samuel A. & Ma, Zhenyu, 2023. "Alarming contagion effects: The dangerous ripple effect of extreme price spillovers across crude oil, carbon emission allowance, and agriculture futures markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 88(C).
    19. Apostolakis, George N. & Floros, Christos & Gkillas, Konstantinos & Wohar, Mark, 2024. "Volatility spillovers across the spot and futures oil markets after news announcements," The North American Journal of Economics and Finance, Elsevier, vol. 69(PA).
    20. Li, Hailing & Pei, Xiaoyun & Yang, Yimin & Zhang, Hua, 2024. "Assessing the impact of energy-related uncertainty on G20 stock market returns: A decomposed contemporaneous and lagged R2 connectedness approach," Energy Economics, Elsevier, vol. 132(C).
    21. Mensi, Walid & Shafiullah, Muhammad & Vo, Xuan Vinh & Kang, Sang Hoon, 2021. "Volatility spillovers between strategic commodity futures and stock markets and portfolio implications: Evidence from developed and emerging economies," Resources Policy, Elsevier, vol. 71(C).
    22. Dai, Zhifeng & Zhu, Junxin & Zhang, Xinhua, 2022. "Time-frequency connectedness and cross-quantile dependence between crude oil, Chinese commodity market, stock market and investor sentiment," Energy Economics, Elsevier, vol. 114(C).
    23. Zhang, Yingying & Xu, Shaojun, 2023. "Spillover connectedness between oil and China's industry stock markets: A perspective of carbon emissions," Finance Research Letters, Elsevier, vol. 54(C).
    24. Zheng, Jinlin & Wen, Baoyu & Jiang, Yaohui & Wang, Xiaohan & Shen, Yue, 2023. "Risk spillovers across geopolitical risk and global financial markets," Energy Economics, Elsevier, vol. 127(PA).
    25. Md. Bokhtiar Hasan & Gazi Salah Uddin & Md. Sumon Ali & Md. Mamunur Rashid & Donghyun Park & Sang Hoon Kang, 2024. "Examining time–frequency quantile dependence between green bond and green equity markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-28, December.
    26. Sheng, Lin Wen & Uddin, Gazi Salah & Sen, Ding & Hao, Zhu Shi, 2024. "The asymmetric volatility spillover across Shanghai, Hong Kong and the U.S. stock markets: A regime weighted measure and its forecast inference," International Review of Financial Analysis, Elsevier, vol. 91(C).
    27. Cui Jinxin & Zou Huiwen, 2020. "Connectedness Among Economic Policy Uncertainties: Evidence from the Time and Frequency Domain Perspectives," Journal of Systems Science and Information, De Gruyter, vol. 8(5), pages 401-433, October.
    28. Tiwari, Aviral Kumar & Aikins Abakah, Emmanuel Joel & Doğan, Buhari & Adekoya, Oluwasegun B. & Wohar, Mark, 2024. "Asymmetric spillover effects in energy markets," International Review of Economics & Finance, Elsevier, vol. 92(C), pages 470-502.
    29. Gao, Wang & Wei, Jiajia & Zhang, Hongwei & Zhang, Haizhen, 2024. "Does climate policy uncertainty exacerbate extreme risk spillovers between green economy and energy metals?," Resources Policy, Elsevier, vol. 91(C).
    30. Jozef Baruník & Evžen Kocenda, 2019. "Total, Asymmetric and Frequency Connectedness Between Oil and Forex Markets," CESifo Working Paper Series 7756, CESifo.
    31. Le, Thanh Ha, 2023. "Quantile time-frequency connectedness between cryptocurrency volatility and renewable energy volatility during the COVID-19 pandemic and Ukraine-Russia conflicts," Renewable Energy, Elsevier, vol. 202(C), pages 613-625.
    32. S. Boubaker & S. Karim & M.A. Naeem & G.D. Sharma, 2023. "Financial Markets, Energy Shocks, and Extreme Volatility Spillovers," Post-Print hal-04435469, HAL.
    33. Wang, Zi-Xin & Liu, Bing-Yue & Fan, Ying, 2023. "Network connectedness between China's crude oil futures and sector stock indices," Energy Economics, Elsevier, vol. 125(C).
    34. Bai, Lan & Wei, Yu & Zhang, Jiahao & Wang, Yizhi & Lucey, Brian M., 2023. "Diversification effects of China's carbon neutral bond on renewable energy stock markets: A minimum connectedness portfolio approach," Energy Economics, Elsevier, vol. 123(C).
    35. 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.
    36. Wu, Tao & An, Feng & Gao, Xiangyun & Wang, Ze, 2023. "Hidden causality between oil prices and exchange rates," Resources Policy, Elsevier, vol. 82(C).
    37. Mensi, Walid & Ko, Hee-Un & Sensoy, Ahmet & Kang, Sang Hoon, 2024. "Higher-order moment connectedness between stock and commodity markets and portfolio management," Resources Policy, Elsevier, vol. 89(C).
    38. Liu, Jiatong & Zhu, You & Wang, Gang-Jin & Xie, Chi & Wang, Qilin, 2024. "Risk contagion of NFT: A time-frequency risk spillover perspective in the Carbon-NFT-Stock system," Finance Research Letters, Elsevier, vol. 59(C).
    39. Geoffrey M. Ngene & Jinghua Wang, 2024. "Transitory and permanent shock transmissions between real estate investment trusts and other assets: Evidence from time‐frequency decomposition and machine learning," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 64(1), pages 539-573, March.
    40. Bastianin, Andrea & Casoli, Chiara & Galeotti, Marzio, 2023. "The connectedness of Energy Transition Metals," FEEM Working Papers 336984, Fondazione Eni Enrico Mattei (FEEM).
    41. Evžen Kočenda & Michala Moravcová & Evžen Kocenda, 2024. "Frequency Volatility Connectedness and Portfolio Hedging of U.S. Energy Commodities," CESifo Working Paper Series 10889, CESifo.
    42. Goswami, Mangal & Pontines, Victor & Mohammed, Yassier, 2023. "Portfolio capital flows and the US dollar exchange rate: Viewed from the lens of time and frequency dynamics of connectedness," International Review of Financial Analysis, Elsevier, vol. 89(C).
    43. Jiang, Wei & Dong, Lingfei & Chen, Yunfei, 2023. "Time-frequency connectedness among traditional/new energy, green finance, and ESG in pre- and post-Russia-Ukraine war periods," Resources Policy, Elsevier, vol. 83(C).
    44. Umar, Zaghum & Abrar, Afsheen & Hadhri, Sinda & Sokolova, Tatiana, 2023. "The connectedness of oil shocks, green bonds, sukuks and conventional bonds," Energy Economics, Elsevier, vol. 119(C).
    45. Zhang, Ping & Yin, Shiqi & Sha, Yezhou, 2023. "Global systemic risk dynamic network connectedness during the COVID-19: Evidence from nonlinear Granger causality," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 85(C).
    46. Banerjee, Ameet Kumar & Pradhan, H.K. & Sensoy, Ahmet & Goodell, John W., 2024. "Assessing the US financial sector post three bank collapses: Signals from fintech and financial sector ETFs," International Review of Financial Analysis, Elsevier, vol. 91(C).
    47. Axel Per Hedström & Gazi Salah Uddin & Md Lutfur Rahman & Bo Sjö, 2024. "Systemic risk in the Scandinavian banking sector," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(1), pages 581-608, January.
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    49. Naeem, Muhammad Abubakr & Shahzad, Mohammad Rahim & Karim, Sitara & Assaf, Rima, 2023. "Tail risk transmission in technology-driven markets," Global Finance Journal, Elsevier, vol. 57(C).
    50. Wan, Jieru & Yin, Libo & Wu, You, 2024. "Return and volatility connectedness across global ESG stock indexes: Evidence from the time-frequency domain analysis," International Review of Economics & Finance, Elsevier, vol. 89(PB), pages 397-428.
    51. Jiang, Wei & Dong, Lingfei & Liu, Xinyi, 2023. "How does COVID-19 affect the spillover effects of green finance, carbon markets, and renewable/non-renewable energy markets? Evidence from China," Energy, Elsevier, vol. 281(C).
    52. Ouyang, Zisheng & Zhou, Xuewei & Wang, Gang-jin & Liu, Shuwen & Lu, Min, 2024. "Multilayer networks in the frequency domain: Measuring volatility connectedness among Chinese financial institutions," International Review of Economics & Finance, Elsevier, vol. 92(C), pages 909-928.
    53. 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).
    54. Munir Khamis & Dalal Aassouli, 2023. "The Eligibility of Green Bonds as Safe Haven Assets: A Systematic Review," Sustainability, MDPI, vol. 15(8), pages 1-27, April.
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    348. Adeleke, Musefiu A. & Awodumi, Olabanji B. & Adewuyi, Adeolu O., 2022. "Return and volatility connectedness among commodity markets during major crises periods: Static and dynamic analyses with asymmetries," Resources Policy, Elsevier, vol. 79(C).
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    350. Rabbani, Mustafa Raza & Billah, Syed Mabruk & Shaik, Muneer & Rahman, Mashuk & Boujlil, Rhada, 2023. "Dynamic connectedness, spillover, and optimal hedging strategy among FinTech, Sukuk, and Islamic equity markets," Global Finance Journal, Elsevier, vol. 58(C).
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    354. 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).
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    Cited by:

    1. Guo, Lili & Huang, Xinya & Li, Yanjiao & Li, Houjian, 2023. "Forecasting crude oil futures price using machine learning methods: Evidence from China," Energy Economics, Elsevier, vol. 127(PA).
    2. Fanelli, Viviana & Maddalena, Lucia & Musti, Silvana, 2016. "Modelling electricity futures prices using seasonal path-dependent volatility," Applied Energy, Elsevier, vol. 173(C), pages 92-102.
    3. Chai, Jian & Lu, Quanying & Hu, Yi & Wang, Shouyang & Lai, Kin Keung & Liu, Hongtao, 2018. "Analysis and Bayes statistical probability inference of crude oil price change point," Technological Forecasting and Social Change, Elsevier, vol. 126(C), pages 271-283.
    4. Horváth, Lajos & Liu, Zhenya & Rice, Gregory & Wang, Shixuan, 2020. "A functional time series analysis of forward curves derived from commodity futures," International Journal of Forecasting, Elsevier, vol. 36(2), pages 646-665.
    5. Mei-Teing Chong & Chin-Hong Puah & Shazali Abu Mansor, 2018. "Oil Price Dynamics Forecasting: An Indicator-Pivoted Paradigm," International Journal of Energy Economics and Policy, Econjournals, vol. 8(3), pages 307-311.
    6. 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.
    7. Mario Figueiredo & Yuri F. Saporito, 2023. "Forecasting the term structure of commodities future prices using machine learning," Digital Finance, Springer, vol. 5(1), pages 57-90, March.
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    13. Bekiroglu, Korkut & Duru, Okan & Gulay, Emrah & Su, Rong & Lagoa, Constantino, 2018. "Predictive analytics of crude oil prices by utilizing the intelligent model search engine," Applied Energy, Elsevier, vol. 228(C), pages 2387-2397.
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    17. Pablo Cansado-Bravo & Carlos Rodríguez-Monroy, 2018. "Persistence of Oil Prices in Gas Import Prices and the Resilience of the Oil-Indexation Mechanism. The Case of Spanish Gas Import Prices," Energies, MDPI, vol. 11(12), pages 1-17, December.
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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. 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.
    2. Maghyereh, Aktham & Abdoh, Hussein, 2022. "Extreme dependence between structural oil shocks and stock markets in GCC countries," Resources Policy, Elsevier, vol. 76(C).
    3. 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).
    4. Barbara Będowska-Sójka & Agata Kliber & Laivi Laidroo, 2023. "Has the pandemic changed the relationships between fintechs and banks?," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 33(4), pages 15-33.
    5. 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).
    6. Haffar, Adlane & Le Fur, Éric, 2022. "Time-varying dependence of Bitcoin," The Quarterly Review of Economics and Finance, Elsevier, vol. 86(C), pages 211-220.
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    Cited by:

    1. Jozef Barunik & Barbora Malinska, 2015. "Forecasting the term structure of crude oil futures prices with neural networks," Papers 1504.04819, arXiv.org.

  24. Jozef Barunik & Evzen Kocenda & Lukas Vacha, 2014. "How does bad and good volatility spill over across petroleum markets?," Papers 1405.2445, arXiv.org.

    Cited by:

    1. 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).
    2. 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.
    3. Umar, Muhammad & Farid, Saqib & Naeem, Muhammad Abubakr, 2022. "Time-frequency connectedness among clean-energy stocks and fossil fuel markets: Comparison between financial, oil and pandemic crisis," Energy, Elsevier, vol. 240(C).
    4. Baumöhl, Eduard & Kočenda, Evžen & Lyócsa, Štefan & Výrost, Tomáš, 2018. "Networks of volatility spillovers among stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1555-1574.
    5. 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).
    6. Guan, Bo & Mazouz, Khelifa & Xu, Yongdeng, 2024. "Asymmetric volatility spillover between crude oil and other asset markets," Energy Economics, Elsevier, vol. 130(C).
    7. 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.
    8. 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.
    9. Mensi, Walid & Ko, Hee-Un & Sensoy, Ahmet & Kang, Sang Hoon, 2024. "Higher-order moment connectedness between stock and commodity markets and portfolio management," Resources Policy, Elsevier, vol. 89(C).
    10. 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.
    11. Bastianin, Andrea & Casoli, Chiara & Galeotti, Marzio, 2023. "The connectedness of Energy Transition Metals," FEEM Working Papers 336984, Fondazione Eni Enrico Mattei (FEEM).
    12. Evžen Kočenda & Michala Moravcová & Evžen Kocenda, 2024. "Frequency Volatility Connectedness and Portfolio Hedging of U.S. Energy Commodities," CESifo Working Paper Series 10889, CESifo.
    13. Hung Do & Rabindra Nepal & Russell Smyth, 2020. "Interconnectedness in the Australian national electricity market: A higher moment analysis," CAMA Working Papers 2020-49, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    14. 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).
    15. 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).
    16. Jozef Baruník & Evžen Kocenda & Lukáš Vácha, 2015. "Asymmetric Connectedness on the U.S. Stock Market: Bad and Good Volatility Spillover," CESifo Working Paper Series 5305, CESifo.
    17. Han, Lin & Kordzakhia, Nino & Trück, Stefan, 2020. "Volatility spillovers in Australian electricity markets," Energy Economics, Elsevier, vol. 90(C).
    18. 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.
    19. 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).
    20. Lovcha, Yuliya & Perez-Laborda, Alejandro, 2020. "Dynamic frequency connectedness between oil and natural gas volatilities," Economic Modelling, Elsevier, vol. 84(C), pages 181-189.
    21. Uddin, Gazi Salah & Yahya, Muhammad & Park, Donghyun & Hedström, Axel & Tian, Shu, 2024. "Bond market spillover networks of ASEAN-4 markets: Is the global pandemic different?," International Review of Economics & Finance, Elsevier, vol. 92(C), pages 1028-1044.
    22. Evrim Mandacı, Pınar & Cagli, Efe Çaglar & Taşkın, Dilvin, 2020. "Dynamic connectedness and portfolio strategies: Energy and metal markets," Resources Policy, Elsevier, vol. 68(C).
    23. 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).
    24. 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.
    25. 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).
    26. Sophio Togonidze & Evzen Kocenda, 2020. "Macroeconomic Responses of Emerging Market Economies to Oil Price Shocks: Analysis by Region and Resource Profile," Working Papers IES 2020/35, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Sep 2020.
    27. 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.
    28. 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).
    29. 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).
    30. Maghyereh, Aktham & Awartani, Basel & Virk, Nader S., 2022. "Asymmetric risk transmissions between oil, gold and US equities: Recent evidence from the realized variance of the futures prices," Resources Policy, Elsevier, vol. 79(C).
    31. 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.
    32. 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).
    33. 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).
    34. 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.
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    36. Dahl, Roy Endré & Jonsson, Erlendur, 2018. "Volatility spillover in seafood markets," Journal of Commodity Markets, Elsevier, vol. 12(C), pages 44-59.
    37. 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.
    38. 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.
    39. Restrepo, Natalia & Uribe, Jorge M. & Manotas, Diego, 2018. "Financial risk network architecture of energy firms," Applied Energy, Elsevier, vol. 215(C), pages 630-642.
    40. 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.
    41. 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.
    42. Čech, František & Zítek, Michal, 2022. "Marine fuel hedging under the sulfur cap regulations," Energy Economics, Elsevier, vol. 113(C).
    43. 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.
    44. 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).
    45. 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.
    46. 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).
    47. Wang, Xunxiao & Wang, Yudong, 2019. "Volatility spillovers between crude oil and Chinese sectoral equity markets: Evidence from a frequency dynamics perspective," Energy Economics, Elsevier, vol. 80(C), pages 995-1009.
    48. 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.
    49. Lovcha, Yuliya & Perez-Laborda, Alejandro, 2022. "Long-memory and volatility spillovers across petroleum futures," Energy, Elsevier, vol. 243(C).
    50. 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).
    51. 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).
    52. 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.
    53. Albrecht, Peter & Kočenda, Evžen, 2024. "Volatility connectedness on the central European forex markets," International Review of Financial Analysis, Elsevier, vol. 93(C).
    54. 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).
    55. 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.
    56. 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).
    57. Guo, Sui & Li, Huajiao & An, Haizhong & Ma, Ning & Sun, Qingru & Feng, Sida & Sun, Guangzhao & Liu, Yanxin, 2024. "Detecting the horizontal/vertical price relationship patterns in the global oil industry chain through network analysis," Energy, Elsevier, vol. 296(C).
    58. Andriosopoulos, Kostas & Galariotis, Emilios & Spyrou, Spyros, 2017. "Contagion, volatility persistence and volatility spill-overs: The case of energy markets during the European financial crisis," Energy Economics, Elsevier, vol. 66(C), pages 217-227.
    59. 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).
    60. 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.
    61. 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).
    62. 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).
    63. 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).
    64. 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).
    65. 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.
    66. 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.
    67. 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.
    68. 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.
    69. Karim Belcaid & Sara El Aoufi & Mamdouh Abdulaziz Saleh Al-Faryan, 2024. "Dynamics of Contagion Risk Among World Markets in Times of Crises: A Financial Network Perspective," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 31(4), pages 1007-1033, December.
    70. Zelazny Jan, 2016. "Financialization and Commodity Market Stability," Financial Internet Quarterly (formerly e-Finanse), Sciendo, vol. 12(4), pages 33-42, December.
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    72. 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.
    73. 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.
    74. 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. 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.
    2. Xin Jin & John M. Maheu & Qiao Yang, 2019. "Bayesian parametric and semiparametric factor models for large realized covariance matrices," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(5), pages 641-660, August.
    3. Rangan Gupta & Christian Pierdzioch, 2024. "Multi-Task Forecasting of the Realized Volatilities of Agricultural Commodity Prices," Working Papers 202423, University of Pretoria, Department of Economics.
    4. 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.
    5. 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).
    6. Dark, Jonathan, 2024. "An adaptive long memory conditional correlation model," Journal of Empirical Finance, Elsevier, vol. 75(C).
    7. 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.
    8. Andrea BUCCI, 2017. "Forecasting Realized Volatility A Review," Journal of Advanced Studies in Finance, ASERS Publishing, vol. 8(2), pages 94-138.
    9. 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).
    10. 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.
    11. Hwang, Eunju & Hong, Won-Tak, 2021. "A multivariate HAR-RV model with heteroscedastic errors and its WLS estimation," Economics Letters, Elsevier, vol. 203(C).
    12. 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.
    13. 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.
    14. 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).
    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).
    16. 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.

  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. 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.
    2. 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).
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. Migliavacca, Milena & Goodell, John W. & Paltrinieri, Andrea, 2023. "A bibliometric review of portfolio diversification literature," International Review of Financial Analysis, Elsevier, vol. 90(C).
    9. 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).
    10. 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).
    11. Nguyen, Hoang & Virbickaitė, Audronė, 2023. "Modeling stock-oil co-dependence with Dynamic Stochastic MIDAS Copula models," Energy Economics, Elsevier, vol. 124(C).
    12. 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.
    13. 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).
    14. 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).
    15. 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).
    16. 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.
    17. 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.
    18. 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).
    19. 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.
    20. 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.
    21. 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.
    22. 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).
    23. 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.
    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. Ryoko Ito, 2016. "Asymptotic Theory for Beta-t-GARCH," Cambridge Working Papers in Economics 1607, Faculty of Economics, University of Cambridge.
    26. 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.
    27. 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.
    28. 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.
    29. 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.
    30. 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).
    31. 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.
    32. 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.
    33. 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.
    34. 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.
    35. Parthajit Kayal & Janani Sri SG, 2020. "Going Beyond Gold: Can Equities be Safe-Haven?," Working Papers 2020-203, Madras School of Economics,Chennai,India.
    36. 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.
    37. 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.
    38. 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.
    39. 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).
    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. 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).
    42. 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.
    43. 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).
    44. 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.
    45. 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).

  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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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).
    9. 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.
    10. Yilmaz, Adil & Unal, Gazanfer & Karatasoglu, Cengiz, 2016. "Wavelet Based Analysis Of Major Real Estate Markets," MPRA Paper 74083, University Library of Munich, Germany.
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    60. 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.
    61. 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).
    62. Aloui, Chaker & Hkiri, Besma & Lau, Marco Chi Keung & Yarovaya, Larisa, 2018. "Information transmission across stock indices and stock index futures: International evidence using wavelet framework," Research in International Business and Finance, Elsevier, vol. 44(C), pages 411-421.
    63. Mohamed Arbi Madani & Zied Ftiti, 2022. "Is gold a hedge or safe haven against oil and currency market movements? A revisit using multifractal approach," Annals of Operations Research, Springer, vol. 313(1), pages 367-400, June.
    64. Shang, Jin & Hamori, Shigeyuki, 2024. "Quantile time-frequency connectedness analysis between crude oil, gold, financial markets, and macroeconomic indicators: Evidence from the US and EU," Energy Economics, Elsevier, vol. 132(C).
    65. 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.
    66. Zhou, Yang & Xie, Chi & Wang, Gang-Jin & Gong, Jue & Li, Zhao-Chen & Zhu, You, 2024. "Who dominate the information flowing between innovative and traditional financial assets? A multiscale entropy-based approach," International Review of Economics & Finance, Elsevier, vol. 93(PB), pages 329-358.
    67. 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.
    68. 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).
    69. 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.
    70. 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.
    71. 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).
    72. 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.
    73. 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).
    74. 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.
    75. 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).
    76. 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.
    77. 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.
    78. 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).
    79. Emre Kahraman & Gazanfer Unal, 2016. "Multiple Wavelet Coherency Analysis and Forecasting of Metal Prices," Papers 1602.01960, arXiv.org.
    80. 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.
    81. Huang, Shupei & An, Haizhong & Gao, Xiangyun & Wen, Shaobo & Hao, Xiaoqing, 2017. "The multiscale impact of exchange rates on the oil-stock nexus: Evidence from China and Russia," Applied Energy, Elsevier, vol. 194(C), pages 667-678.
    82. 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.
    83. Li, Yue & W. Goodell, John & Shen, Dehua, 2021. "Does happiness forecast implied volatility? Evidence from nonparametric wave-based Granger causality testing," The Quarterly Review of Economics and Finance, Elsevier, vol. 81(C), pages 113-122.
    84. Hung, Ngo Thai & Vo, Xuan Vinh, 2021. "Directional spillover effects and time-frequency nexus between oil, gold and stock markets: Evidence from pre and during COVID-19 outbreak," International Review of Financial Analysis, Elsevier, vol. 76(C).
    85. Mensi, Walid & Hernandez, Jose Arroeola & Yoon, Seong-Min & Vo, Xuan Vinh & Kang, Sang Hoon, 2021. "Spillovers and connectedness between major precious metals and major currency markets: The role of frequency factor," International Review of Financial Analysis, Elsevier, vol. 74(C).
    86. Tiwari, Aviral Kumar & Mishra, Bibhuti Ranjan & Solarin, Sakiru Adebola, 2021. "Analysing the spillovers between crude oil prices, stock prices and metal prices: The importance of frequency domain in USA," Energy, Elsevier, vol. 220(C).
    87. Awaworyi Churchill, Sefa & Inekwe, John & Ivanovski, Kris & Smyth, Russell, 2019. "Dynamics of oil price, precious metal prices and the exchange rate in the long-run," Energy Economics, Elsevier, vol. 84(C).

  31. Krenar Avdulaj & Jozef Barunik, 2013. "Can we still benefit from international diversification? The case of the Czech and German stock markets," Papers 1308.6120, arXiv.org, revised Sep 2013.

    Cited by:

    1. 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.
    2. Sekuła Paweł, 2019. "Causality Analysis Between Stock Market Indices," Financial Sciences. Nauki o Finansach, Sciendo, vol. 24(1), pages 74-93, March.
    3. 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.
    4. 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.
    5. 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.

  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. Dennis Wesselbaum, 2017. "Catastrophe theory and the financial crisis," Scottish Journal of Political Economy, Scottish Economic Society, vol. 64(4), pages 376-391, September.
    2. Michael S. Harr'e & Adam Harris & Scott McCallum, 2019. "Singularities and Catastrophes in Economics: Historical Perspectives and Future Directions," Papers 1907.05582, arXiv.org.
    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. 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).
    5. 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.
    6. 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.
    7. 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).
    8. 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.
    9. Michael S. Harr'e, 2018. "Multi-agent Economics and the Emergence of Critical Markets," Papers 1809.01332, arXiv.org.
    10. 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.

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

    Cited by:

    1. 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.
    2. Zhao, Yixiu & Upreti, Vineet & Cai, Yuzhi, 2021. "Stock returns, quantile autocorrelation, and volatility forecasting," International Review of Financial Analysis, Elsevier, vol. 73(C).
    3. 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).
    4. 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.
    5. Jozef Barunik & Lubos Hanus, 2022. "Learning Probability Distributions in Macroeconomics and Finance," Papers 2204.06848, arXiv.org.
    6. 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.
    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.
    8. 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.
    9. Kawakami, Tabito, 2023. "Quantile prediction for Bitcoin returns using financial assets’ realized measures," Finance Research Letters, Elsevier, vol. 55(PA).
    10. 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.
    11. 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.
    12. Chao Wang & Richard Gerlach, 2019. "Semi-parametric Realized Nonlinear Conditional Autoregressive Expectile and Expected Shortfall," Papers 1906.09961, arXiv.org.
    13. Stanislav Anatolyev & Jozef Barunik, 2017. "Forecasting dynamic return distributions based on ordered binary choice," Papers 1711.05681, arXiv.org, revised Jan 2019.
    14. 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.
    15. 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).
    16. 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.
    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. 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).
    2. 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.
    3. 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.
    4. 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.
    5. Barunik, Jozef & Vacha, Lukas, 2018. "Do co-jumps impact correlations in currency markets?," Journal of Financial Markets, Elsevier, vol. 37(C), pages 97-119.
    6. 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.
    7. 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.
    8. Stelios Bekiros & Jose Arreola Hernandez & Gazi Salah Uddin & Ahmed Taneem Muzaffar, 2020. "On the predictability of crude oil market: A hybrid multiscale wavelet approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(4), pages 599-614, July.
    9. 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.
    10. 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.
    11. Degiannakis, Stavros & Filis, George & Hassani, Hossein, 2015. "Forecasting implied volatility indices worldwide: A new approach," MPRA Paper 72084, University Library of Munich, Germany.
    12. 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).
    13. 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.
    14. 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).
    15. Baruník, Jozef & Ellington, Michael, 2024. "Persistence in financial connectedness and systemic risk," European Journal of Operational Research, Elsevier, vol. 314(1), pages 393-407.
    16. 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).
    17. 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.
    18. 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.
    19. Shafiullah, Muhammad & Senthilkumar, Arunachalam & Lucey, Brian M. & Naeem, Muhammad Abubakr, 2024. "Deciphering asymmetric spillovers in US industries: Insights from higher-order moments," Research in International Business and Finance, Elsevier, vol. 70(PA).
    20. 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.
    21. 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).
    22. 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.
    23. 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.
    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. 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.
    27. Baruník Jozef & Fišer Pavel, 2024. "Co-Jumping of Treasury Yield Curve Rates," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 28(3), pages 481-506.
    28. 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.
    29. 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.
    30. 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.
    31. 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).
    32. 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.
    33. 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).
    34. 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.
    35. 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).
    36. 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.
    37. 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.
    38. 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.
    39. 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.
    40. 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).
    41. 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.
    42. 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.
    43. Lu, Fei & Ma, Feng & Bouri, Elie & Liao, Yin, 2024. "Do commodity futures have a steering effect on the spot stock market in China? New evidence from volatility forecasting," International Review of Financial Analysis, Elsevier, vol. 94(C).
    44. 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.
    45. Leong, Soon Heng & Urga, Giovanni, 2023. "A practical multivariate approach to testing volatility spillover," Journal of Economic Dynamics and Control, Elsevier, vol. 153(C).
    46. 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.
    47. Yong Shi & Wei Dai & Wen Long & Bo Li, 2021. "Deep Kernel Gaussian Process Based Financial Market Predictions," Papers 2105.12293, arXiv.org.
    48. 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.

  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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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).
    6. 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.
    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. 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).
    9. 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.
    10. 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.
    11. 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.
    12. Jan Polach & Jiri Kukacka, 2016. "Prospect Theory in the Heterogeneous Agent Model," Working Papers IES 2016/14, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Jul 2016.
    13. 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.

  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.

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    1. 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.
    2. 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".

  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. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.

  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. Cagli, Efe Caglar & Taskin, Dilvin & Evrim Mandaci, Pınar, 2019. "The short- and long-run efficiency of energy, precious metals, and base metals markets: Evidence from the exponential smooth transition autoregressive models," Energy Economics, Elsevier, vol. 84(C).
    2. 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.
    3. 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.
    4. 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.
    5. 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).
    6. 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.
    7. 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.
    8. Yildirim, Ramazan & Masih, Mansur, 2018. "Investigating International Portfolio Diversification Opportunities for the Asian Islamic Stock Market Investors," MPRA Paper 90281, University Library of Munich, Germany.
    9. Power, Gabriel J. & Eaves, James & Turvey, Calum & Vedenov, Dmitry, 2017. "Catching the curl: Wavelet thresholding improves forward curve modelling," Economic Modelling, Elsevier, vol. 64(C), pages 312-321.
    10. Naveed Raza & Syed Jawad Hussain Shahzad & Aviral Kumar Tiwari & Muhammad Shahbaz, 2016. "Asymmetric impact of gold, oil prices and their volatilities on stock prices of emerging markets," Post-Print hal-02013747, HAL.
    11. Shahzad, Syed Jawad Hussain & Mensi, Walid & Hammoudeh, Shawkat & Rehman, Mobeen Ur & Al-Yahyaee, Khamis H., 2018. "Extreme dependence and risk spillovers between oil and Islamic stock markets," Emerging Markets Review, Elsevier, vol. 34(C), pages 42-63.
    12. Xu, Yingying, 2020. "Will energy transitions impact financial systems?," Energy, Elsevier, vol. 194(C).
    13. 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.
    14. Mbarki, Imen & Khan, Muhammad Arif & Karim, Sitara & Paltrinieri, Andrea & Lucey, Brian M., 2023. "Unveiling commodities-financial markets intersections from a bibliometric perspective," Resources Policy, Elsevier, vol. 83(C).
    15. Naveed Raza & Ahmad Ibn Ibrahimy & Azwadi Ali & Sajid Ali, 2016. "Gold and Islamic stocks: A hedge and safe haven comparison in time frequency domain for BRICS markets," Journal of Developing Areas, Tennessee State University, College of Business, vol. 50(6), pages 305-318, Special I.
    16. Su, Zhi & Lu, Man & Yin, Libo, 2018. "Oil prices and news-based uncertainty: Novel evidence," Energy Economics, Elsevier, vol. 72(C), pages 331-340.
    17. M. Utku Ozmen & Erdal Yilmaz, 2016. "Co-movement of Exchange Rates with Interest Rate Differential, Risk Premium and FED Policy in �Fragile Economies�," Working Papers 1621, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    18. Umairah, Fatin & Masih, Mansur, 2017. "Should the Malaysian islamic stock market investors invest in regional and international equity markets to gain portfolio diversification benefits?," MPRA Paper 82117, University Library of Munich, Germany.
    19. 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.
    20. Wu, Kai & Zhu, Jingran & Xu, Mingli & Yang, Lu, 2020. "Can crude oil drive the co-movement in the international stock market? Evidence from partial wavelet coherence analysis," The North American Journal of Economics and Finance, Elsevier, vol. 53(C).
    21. Ladislav Kristoufek, 2013. "Fractal Markets Hypothesis and the Global Financial Crisis: Wavelet Power Evidence," Papers 1310.1446, arXiv.org.
    22. Wen-Yi CHEN & Yu-Hui LIN, 2016. "Co-Movement of Healthcare Financing in OECD Countries: Evidence from Discrete Wavelet Analyses," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 40-56, September.
    23. Shupei Huang & Haizhong An & Xiangyun Gao & Meihui Jiang, 2016. "The Multiscale Fluctuations of the Correlation between Oil Price and Wind Energy Stock," Sustainability, MDPI, vol. 8(6), pages 1-14, June.
    24. Afshan, Sahar & Sharif, Arshian & Loganathan, Nanthakumar & Jammazi, Rania, 2018. "Time–frequency causality between stock prices and exchange rates: Further evidences from cointegration and wavelet analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 495(C), pages 225-244.
    25. Lukas Vacha & Karel Janda & Ladislav Kristoufek & David Zilberman, 2012. "Time-Frequency Dynamics of Biofuels-Fuels-Food System," Papers 1209.0900, arXiv.org.
    26. Mustafa Gülerce & Gazanfer Ünal, 2017. "Forecasting Of Oil And Agricultural Commodity Prices: Varma Versus Arma," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 12(03), pages 1-30, September.
    27. Farouk, Faizal & Masih, Mansur, 2014. "Are There Profit (Returns) in Shariah-Compliant Exchange Traded Funds? The Multiscale Propensity," MPRA Paper 58869, University Library of Munich, Germany.
    28. Qunwei Wang & Xingyu Dai & Dequn Zhou, 2020. "Dynamic Correlation and Risk Contagion Between “Black” Futures in China: A Multi-scale Variational Mode Decomposition Approach," Computational Economics, Springer;Society for Computational Economics, vol. 55(4), pages 1117-1150, April.
    29. Mokhtar, Maznita & Masih, Mansur, 2014. "Are diversification benefits obtainable within the same asset class? New evidence from Malaysian Islamic REITS," MPRA Paper 56990, University Library of Munich, Germany.
    30. Lubos Hanus & Lukas Vacha, 2015. "Business cycle synchronization within the European Union: A wavelet cohesion approach," Papers 1506.03106, arXiv.org, revised Feb 2016.
    31. Yang, Lu & Cai, Xiao Jing & Hamori, Shigeyuki, 2017. "Does the crude oil price influence the exchange rates of oil-importing and oil-exporting countries differently? A wavelet coherence analysis," International Review of Economics & Finance, Elsevier, vol. 49(C), pages 536-547.
    32. Bilgili, Faik & Mugaloglu, Erhan & Koçak, Emrah, 2018. "The impact of oil prices on CO2 emissions in China: A Wavelet coherence approach," MPRA Paper 90170, University Library of Munich, Germany.
    33. Ahmed, Walid M.A., 2022. "On the higher-order moment interdependence of stock and commodity markets: A wavelet coherence analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 83(C), pages 135-151.
    34. Abdullah, Ahmad Monir & Saiti, Buerhan & Masih, Abul Mansur M., 2014. "Diversification in Crude Oil and Other Commodities: A Comparative Analysis," MPRA Paper 56988, University Library of Munich, Germany.
    35. Bošnjak Mile & Kordić Gordana & Novak Ivan, 2021. "Real Effective Exchange Rate and Industrial Productivity in Croatia: Wavelet Coherence Analysis," South East European Journal of Economics and Business, Sciendo, vol. 16(1), pages 30-37, June.
    36. Jinxin Cui & Aktham Maghyereh, 2022. "Time–frequency co-movement and risk connectedness among cryptocurrencies: new evidence from the higher-order moments before and during the COVID-19 pandemic," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-56, December.
    37. Boryana Bogdanova, 2014. "Measuring the degree of integration within a group of stock markets," Economic Thought journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 6, pages 26-46.
    38. Jiang, Yonghong & Jiang, Cheng & Nie, He & Mo, Bin, 2019. "The time-varying linkages between global oil market and China's commodity sectors: Evidence from DCC-GJR-GARCH analyses," Energy, Elsevier, vol. 166(C), pages 577-586.
    39. 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.
    40. Muhammad Azmat Hayat & Huma Ghulam & Maryam Batool & Muhammad Zahid Naeem & Abdullah Ejaz & Cristi Spulbar & Ramona Birau, 2021. "Investigating the Causal Linkages among Inflation, Interest Rate, and Economic Growth in Pakistan under the Influence of COVID-19 Pandemic: A Wavelet Transformation Approach," JRFM, MDPI, vol. 14(6), pages 1-22, June.
    41. 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).
    42. Luboš Hanus & Lukáš Vácha, 2020. "Growth cycle synchronization of the Visegrad Four and the European Union," Empirical Economics, Springer, vol. 58(4), pages 1779-1795, April.
    43. Huang, Xiaohong & Huang, Shupei, 2020. "Identifying the comovement of price between China's and international crude oil futures: A time-frequency perspective," International Review of Financial Analysis, Elsevier, vol. 72(C).
    44. Eman F. Attia & Sharihan Mohamed Aly & Ahmed said ElRawas & Ebtehal Orabi Awad, 2023. "Portfolio diversification benefits before and during the times of COVID-19: evidence from USA," Future Business Journal, Springer, vol. 9(1), pages 1-15, December.
    45. Umar, Zaghum & Gubareva, Mariya, 2020. "A time–frequency analysis of the impact of the Covid-19 induced panic on the volatility of currency and cryptocurrency markets," Journal of Behavioral and Experimental Finance, Elsevier, vol. 28(C).
    46. 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.
    47. 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.
    48. 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).
    49. Milan Bašta & Peter Molnár, 2019. "Long‐term dynamics of the VIX index and its tradable counterpart VXX," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(3), pages 322-341, March.
    50. Jozef Barunik & Evzen Kocenda & Lukas Vacha, 2013. "Gold, Oil, and Stocks," Papers 1308.0210, arXiv.org, revised Mar 2014.
    51. Bekiros, Stelios & Nguyen, Duc Khuong & Uddin, Gazi Salah & Sjö, Bo, 2016. "On the time scale behavior of equity-commodity links: Implications for portfolio management," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 41(C), pages 30-46.
    52. Shahzad, Syed Jawad Hussain & Nor, Safwan Mohd & Kumar, Ronald Ravinesh & Mensi, Walid, 2017. "Interdependence and contagion among industry-level US credit markets: An application of wavelet and VMD based copula approaches," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 310-324.
    53. João Martins, 2022. "Bond Yields Movement Similarities and Synchronization in the G7: A Time–Frequency Analysis," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 18(2), pages 189-214, July.
    54. Monge, Manuel & Cristóbal, Enrique, 2021. "Terrorism and the behavior of oil production and prices in OPEC," Resources Policy, Elsevier, vol. 74(C).
    55. Monge, Manuel & Gil-Alana, Luis A., 2021. "Lithium industry and the U.S. crude oil prices. A fractional cointegration VAR and a Continuous Wavelet Transform analysis," Resources Policy, Elsevier, vol. 72(C).
    56. Ender Demir & Mehmet Huseyin Bilgin & Gokhan Karabulut & Asli Cansin Doker, 2020. "The relationship between cryptocurrencies and COVID-19 pandemic," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 10(3), pages 349-360, September.
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    58. Gao Wenxin & Wen Jun & Zakaria Muhammad & Mahmood Hamid, 2022. "Nonlinear and Asymmetric Impact of Oil Prices on Exchange Rates: Evidence from South Asia," Economics - The Open-Access, Open-Assessment Journal, De Gruyter, vol. 16(1), pages 243-256, January.
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    61. Huang, Shupei & An, Haizhong & Wen, Shaobo & An, Feng, 2017. "Revisiting driving factors of oil price shocks across time scales," Energy, Elsevier, vol. 139(C), pages 617-629.
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    70. 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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    217. Nagayev, Ruslan & Disli, Mustafa & Inghelbrecht, Koen & Ng, Adam, 2016. "On the dynamic links between commodities and Islamic equity," Energy Economics, Elsevier, vol. 58(C), pages 125-140.
    218. Luís Aguiar-Conraria & Maria Joana Soares, 2014. "The Continuous Wavelet Transform: Moving Beyond Uni- And Bivariate Analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 28(2), pages 344-375, April.
    219. Agyemang, Abraham & Chowdhury, Iftekhar & Balli, Faruk, 2021. "Quantifying Return Spillovers in Global Real Estate Markets," Journal of Housing Economics, Elsevier, vol. 52(C).
    220. Meng, Xiangcai & Huang, Chia-Hsing, 2021. "The time-frequency analysis of conventional and unconventional monetary policy: Evidence from Japan," Japan and the World Economy, Elsevier, vol. 59(C).
    221. Raza, Naveed & Ibrahimy, Ahmad & Ali, Azwadi, 2015. "Gold and Islamic Stocks: A Hedge and Safe Haven Comparison in Time - Grequency domain for BRICS," MPRA Paper 69366, University Library of Munich, Germany.
    222. Huang, Shupei & An, Haizhong & Gao, Xiangyun & Wen, Shaobo & Hao, Xiaoqing, 2017. "The multiscale impact of exchange rates on the oil-stock nexus: Evidence from China and Russia," Applied Energy, Elsevier, vol. 194(C), pages 667-678.
    223. Sudipta Das, 2021. "The Time–Frequency Relationship between Oil Price, Stock Returns and Exchange Rate," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(2), pages 129-149, November.
    224. Yue-Jun Zhang & Shu-Hui Li, 2019. "The impact of investor sentiment on crude oil market risks: evidence from the wavelet approach," Quantitative Finance, Taylor & Francis Journals, vol. 19(8), pages 1357-1371, August.
    225. Yahya, Muhammad & Oglend, Atle & Dahl, Roy Endré, 2019. "Temporal and spectral dependence between crude oil and agricultural commodities: A wavelet-based copula approach," Energy Economics, Elsevier, vol. 80(C), pages 277-296.
    226. 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.
    227. Sun, Xiaolei & Chen, Xiuwen & Wang, Jun & Li, Jianping, 2020. "Multi-scale interactions between economic policy uncertainty and oil prices in time-frequency domains," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    228. Md Hakim Ali & Md Akther Uddin & Md. Atiqur Rahman Khan & Blake Goud, 2021. "Faith‐based versus value‐based finance: Is there any portfolio diversification benefit between responsible and Islamic finance?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5570-5583, October.
    229. Meng, Xiangcai & Huang, Chia-Hsing, 2019. "The time-frequency co-movement of Asian effective exchange rates: A wavelet approach with daily data," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 131-148.
    230. Sheng Cheng & Wei Liu & Qisheng Jiang & Yan Cao, 2023. "Multi–Scale Risk Connectedness Between Economic Policy Uncertainty of China and Global Oil Prices in Time–Frequency Domains," Computational Economics, Springer;Society for Computational Economics, vol. 61(4), pages 1593-1616, April.
    231. Sousa, Rita & Aguiar-Conraria, Luís & Soares, Maria Joana, 2014. "Carbon financial markets: A time–frequency analysis of CO2 prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 414(C), pages 118-127.
    232. Andreani, Michele & Giri, Federico, 2023. "Not a short-run noise! The low-frequency volatility of energy inflation," Finance Research Letters, Elsevier, vol. 51(C).
    233. 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).
    234. Yang, Lu & Hamori, Shigeyuki, 2015. "Interdependence between the bond markets of CEEC-3 and Germany: A wavelet coherence analysis," The North American Journal of Economics and Finance, Elsevier, vol. 32(C), pages 124-138.
    235. Swamy, Vighneswara, 2020. "Macroeconomic transmission of Eurozone shocks to India—A mean-adjusted Bayesian VAR approach," Economic Analysis and Policy, Elsevier, vol. 68(C), pages 126-150.
    236. Vácha, Lukáš & Šmolík, Filip & Baxa, Jaromír, 2019. "Comovement and disintegration of EU sovereign bond markets during the crisis," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 541-556.
    237. 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.

  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. 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).
    2. 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.
    3. Faria, Gonçalo & Verona, Fabio, 2020. "The yield curve and the stock market: Mind the long run," Journal of Financial Markets, Elsevier, vol. 50(C).
    4. 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.
    5. Barunik, Jozef & Vacha, Lukas, 2018. "Do co-jumps impact correlations in currency markets?," Journal of Financial Markets, Elsevier, vol. 37(C), pages 97-119.
    6. 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.
    7. 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.
    8. 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).
    9. 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).
    10. 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.
    11. 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).
    12. Gonçalo Faria & Fabio Verona, 2017. "Forecasting stock market returns by summing the frequency-decomposed parts," CEF.UP Working Papers 1702, Universidade do Porto, Faculdade de Economia do Porto.
    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. Gonçalo Faria & Fabio Verona, 2016. "Forecasting the equity risk premium with frequency-decomposed predictors," Working Papers de Economia (Economics Working Papers) 06, Católica Porto Business School, Universidade Católica Portuguesa.
    16. 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.
    17. Gonçalo Faria & Fabio Verona, 2021. "Time-frequency forecast of the equity premium," Quantitative Finance, Taylor & Francis Journals, vol. 21(12), pages 2119-2135, December.
    18. 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).
    19. 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.

  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. Kristoufek, Ladislav & Vosvrda, Miloslav, 2014. "Measuring capital market efficiency: Long-term memory, fractal dimension and approximate entropy," FinMaP-Working Papers 18, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    3. 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.
    4. David, S.A. & Inácio, C.M.C. & Quintino, D.D. & Machado, J.A.T., 2020. "Measuring the Brazilian ethanol and gasoline market efficiency using DFA-Hurst and fractal dimension," Energy Economics, Elsevier, vol. 85(C).
    5. 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).
    6. Chen, Cheng & Wang, Yudong, 2017. "Understanding the multifractality in portfolio excess returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 346-355.
    7. Nava, Noemi & Di Matteo, T. & Aste, Tomaso, 2016. "Anomalous volatility scaling in high frequency financial data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 434-445.
    8. Sarker, Alivia & Mali, Provash, 2021. "Detrended multifractal characterization of Indian rainfall records," Chaos, Solitons & Fractals, Elsevier, vol. 151(C).
    9. 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.
    10. 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.
    11. 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.
    12. Riccardo Junior Buonocore & Tomaso Aste & Tiziana Di Matteo, 2015. "Measuring multiscaling in financial time-series," Papers 1509.05471, arXiv.org, revised Sep 2015.
    13. 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.
    14. 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.
    15. Krenar Avdulaj & Ladislav Kristoufek, 2020. "On Tail Dependence and Multifractality," Mathematics, MDPI, vol. 8(10), pages 1-13, October.
    16. 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.
    17. Salat, Hadrien & Murcio, Roberto & Arcaute, Elsa, 2017. "Multifractal methodology," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 467-487.
    18. 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.
    19. 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).
    20. 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.
    21. 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.
    22. Saâdaoui, Foued, 2023. "Skewed multifractal scaling of stock markets during the COVID-19 pandemic," Chaos, Solitons & Fractals, Elsevier, vol. 170(C).
    23. 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.
    24. John Goddard & Enrico Onali, 2016. "Long memory and multifractality: A joint test," Papers 1601.00903, arXiv.org.
    25. 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.
    26. 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).
    27. Schadner, Wolfgang, 2022. "U.S. Politics from a multifractal perspective," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
    28. Saâdaoui, Foued, 2024. "Segmented multifractal detrended fluctuation analysis for assessing inefficiency in North African stock markets," Chaos, Solitons & Fractals, Elsevier, vol. 181(C).
    29. 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.
    30. 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.
    31. Choi, Sun-Yong, 2021. "Analysis of stock market efficiency during crisis periods in the US stock market: Differences between the global financial crisis and COVID-19 pandemic," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).
    32. 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.
    33. Ladislav Kristoufek & Miloslav Vosvrda, 2012. "Measuring capital market efficiency: Global and local correlations structure," Papers 1208.1298, arXiv.org.
    34. Akash P. POOJARI & Siva Kiran GUPTHA & G Raghavender RAJU, 2022. "Multifractal analysis of equities. Evidence from the emerging and frontier banking sectors," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 0(3(632), A), pages 61-80, Autumn.
    35. Aurelio F. Bariviera, 2020. "One model is not enough: heterogeneity in cryptocurrencies' multifractal profiles," Papers 2003.09720, arXiv.org, revised Jun 2020.
    36. Lee, Hojin & Chang, Woojin, 2015. "Multifractal regime detecting method for financial time series," Chaos, Solitons & Fractals, Elsevier, vol. 70(C), pages 117-129.
    37. 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.
    38. Sensoy, Ahmet & Hacihasanoglu, Erk, 2014. "Time-varying long range dependence in energy futures markets," Energy Economics, Elsevier, vol. 46(C), pages 318-327.
    39. 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).
    40. 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.
    41. Mensi, Walid & Lee, Yun-Jung & Al-Yahyaee, Khamis Hamed & Sensoy, Ahmet & Yoon, Seong-Min, 2019. "Intraday downward/upward multifractality and long memory in Bitcoin and Ethereum markets: An asymmetric multifractal detrended fluctuation analysis," Finance Research Letters, Elsevier, vol. 31(C), pages 19-25.
    42. 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.
    43. Tao, Qizhi & Wei, Yu & Liu, Jiapeng & Zhang, Ting, 2018. "Modeling and forecasting multifractal volatility established upon the heterogeneous market hypothesis," International Review of Economics & Finance, Elsevier, vol. 54(C), pages 143-153.
    44. Chen, Wang & Wei, Yu & Lang, Qiaoqi & Lin, Yu & Liu, Maojuan, 2014. "Financial market volatility and contagion effect: A copula–multifractal volatility approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 398(C), pages 289-300.
    45. Siokis, Fotios M., 2014. "European economies in crisis: A multifractal analysis of disruptive economic events and the effects of financial assistance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 283-292.
    46. 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.
    47. Noemi Nava & T. Di Matteo & Tomaso Aste, 2015. "Anomalous volatility scaling in high frequency financial data," Papers 1503.08465, arXiv.org, revised Dec 2015.
    48. Ladislav Kristoufek, 2013. "Testing power-law cross-correlations: Rescaled covariance test," Papers 1307.4727, arXiv.org, revised Aug 2013.
    49. Cao, Guangxi & Xu, Wei, 2016. "Nonlinear structure analysis of carbon and energy markets with MFDCCA based on maximum overlap wavelet transform," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 505-523.
    50. Pagnottoni, Paolo & Spelta, Alessandro & Pecora, Nicolò & Flori, Andrea & Pammolli, Fabio, 2021. "Financial earthquakes: SARS-CoV-2 news shock propagation in stock and sovereign bond markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 582(C).
    51. Wu, Liang & Chen, Lei & Ding, Yiming & Zhao, Tongzhou, 2018. "Testing for the source of multifractality in water level records," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 824-839.
    52. 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.
    53. 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.
    54. 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.
    55. Saâdaoui, Foued, 2018. "Testing for multifractality of Islamic stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 263-273.
    56. 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).
    57. 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.
    58. 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).
    59. 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).
    60. 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).
    61. 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.
    62. Schadner, Wolfgang, 2021. "On the persistence of market sentiment: A multifractal fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    63. Laura Raisa Miloş & Cornel Haţiegan & Marius Cristian Miloş & Flavia Mirela Barna & Claudiu Boțoc, 2020. "Multifractal Detrended Fluctuation Analysis (MF-DFA) of Stock Market Indexes. Empirical Evidence from Seven Central and Eastern European Markets," Sustainability, MDPI, vol. 12(2), pages 1-15, January.

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

    Cited by:

    1. Fernández-Martínez, M. & Sánchez-Granero, M.A. & Trinidad Segovia, J.E., 2013. "Measuring the self-similarity exponent in Lévy stable processes of financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(21), pages 5330-5345.
    2. Kristoufek, Ladislav & Vosvrda, Miloslav, 2014. "Measuring capital market efficiency: Long-term memory, fractal dimension and approximate entropy," FinMaP-Working Papers 18, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    3. Ladislav Kristoufek, 2015. "Power-law correlations in finance-related Google searches, and their cross-correlations with volatility and traded volume: Evidence from the Dow Jones Industrial components," Papers 1502.00225, arXiv.org.
    4. Buonocore, R.J. & Aste, T. & Di Matteo, T., 2016. "Measuring multiscaling in financial time-series," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 38-47.
    5. Kristoufek, Ladislav, 2013. "Mixed-correlated ARFIMA processes for power-law cross-correlations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(24), pages 6484-6493.
    6. Ferreira, Paulo & Kristoufek, Ladislav, 2017. "What is new about covered interest parity condition in the European Union? Evidence from fractal cross-correlation regressions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 554-566.
    7. Dutta, Srimonti & Ghosh, Dipak & Chatterjee, Sucharita, 2016. "Multifractal detrended Cross Correlation Analysis of Foreign Exchange and SENSEX fluctuation in Indian perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 463(C), pages 188-201.
    8. Tiwari, Aviral Kumar & Umar, Zaghum & Alqahtani, Faisal, 2021. "Existence of long memory in crude oil and petroleum products: Generalised Hurst exponent approach," Research in International Business and Finance, Elsevier, vol. 57(C).
    9. Barunik, Jozef & Aste, Tomaso & Di Matteo, T. & Liu, Ruipeng, 2012. "Understanding the source of multifractality in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(17), pages 4234-4251.
    10. Hiremath, Gourishankar S. & Kattuman, Paul, 2017. "Foreign portfolio flows and emerging stock market: Is the midnight bell ringing in India?," Research in International Business and Finance, Elsevier, vol. 42(C), pages 544-558.
    11. Sensoy, Ahmet & Tabak, Benjamin M., 2016. "Dynamic efficiency of stock markets and exchange rates," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 353-371.
    12. Raffaello Morales & T. Di Matteo & Ruggero Gramatica & Tomaso Aste, 2011. "Dynamical Hurst exponent as a tool to monitor unstable periods in financial time series," Papers 1109.0465, arXiv.org.
    13. Zunino, Luciano & Tabak, Benjamin M. & Serinaldi, Francesco & Zanin, Massimiliano & Pérez, Darío G. & Rosso, Osvaldo A., 2011. "Commodity predictability analysis with a permutation information theory approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(5), pages 876-890.
    14. Zhang, Guofu & Li, Jingjing, 2018. "Multifractal analysis of Shanghai and Hong Kong stock markets before and after the connect program," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 611-622.
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  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. Mensi, Walid & Hkiri, Besma & Al-Yahyaee, Khamis H. & Kang, Sang Hoon, 2018. "Analyzing time–frequency co-movements across gold and oil prices with BRICS stock markets: A VaR based on wavelet approach," International Review of Economics & Finance, Elsevier, vol. 54(C), pages 74-102.
    2. McNevin, Bruce D. & Nix, Joan, 2018. "The beta heuristic from a time/frequency perspective: A wavelet analysis of the market risk of sectors," Economic Modelling, Elsevier, vol. 68(C), pages 570-585.
    3. Ijaz Younis & Cheng Longsheng & Muhammad Farhan Basheer & Ahmed Shafique Joyo, 2020. "Stock market comovements among Asian emerging economies: A wavelet-based approach," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-23, October.
    4. Semih Emre Cekin & Besma Hkiri & Aviral Kumar Tiwari & Rangan Gupta, 2019. "The Relationship between Monetary Policy and Uncertainty in Advanced Economies: Evidence from Time- and Frequency-Domains," Working Papers 201904, University of Pretoria, Department of Economics.
    5. Aloui, Chaker & Hkiri, Besma & Nguyen, Duc Khuong, 2016. "Real growth co-movements and business cycle synchronization in the GCC countries: Evidence from time-frequency analysis," Economic Modelling, Elsevier, vol. 52(PB), pages 322-331.
    6. Masih, Mansur & Majid, Hamdan Abdul, 2013. "Comovement of Selected International Stock Market Indices:A Continuous Wavelet Transformation and Cross Wavelet Transformation Analysis," MPRA Paper 58313, University Library of Munich, Germany.
    7. Taheri Bazkhaneh , Saleh & Ehsani , Mohammad Ali & Gilak Hakimabadi , Mohammad Taqi & Farzinvash , Asodollah, 2018. "Analysis of the Relationship between the Business Cycle and Inflation Gap in Time-Frequency Domain," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 13(3), pages 401-422, July.
    8. Jusoh, Hashim & Bacha, Obiyathulla & Masih, Abul Mansur M., 2014. "Multi-scale Lead-Lag Relationship between the Stock and Futures Markets: Malaysia as a Case Study," MPRA Paper 56954, University Library of Munich, Germany.
    9. Avishek Bhandari, 2020. "A wavelet analysis of inter-dependence, contagion and long memory among global equity markets," Papers 2003.14110, arXiv.org.
    10. Besma Hkiri & Juncal Cunado & Mehmet Balcilar & Rangan Gupta, 2019. "Time-Varying Relationship between Conventional and Unconventional Monetary Policies and Risk Aversion: International Evidence from Time- and Frequency-Domains," Working Papers 201965, University of Pretoria, Department of Economics.
    11. Avishek BHANDARI, 2017. "Wavelets based multiscale analysis of select global equity returns," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 0(4(613), W), pages 75-88, Winter.
    12. M. Kannadhasan & Debojyoti Das, 2019. "Has Co-Movement Dynamics in Brazil, Russia, India, China and South Africa (BRICS) Markets Changed After Global Financial Crisis? New Evidence from Wavelet Analysis," Asian Academy of Management Journal of Accounting and Finance (AAMJAF), Penerbit Universiti Sains Malaysia, vol. 15(1), pages 1-26.
    13. Ben-Salha, Ousama & Hkiri, Besma & Aloui, Chaker, 2018. "Sectoral energy consumption by source and output in the U.S.: New evidence from wavelet-based approach," Energy Economics, Elsevier, vol. 72(C), pages 75-96.

  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. Horváth, Roman & Vaško, Dan, 2016. "Central bank transparency and financial stability," Journal of Financial Stability, Elsevier, vol. 22(C), pages 45-56.
    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.

  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.

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    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. Baruník Jozef & Fišer Pavel, 2024. "Co-Jumping of Treasury Yield Curve Rates," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 28(3), pages 481-506.
    See citations under working paper version above.
  4. 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.
  5. 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. 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.
    2. Chavas, Jean-Paul & Li, Jian & Wang, Linjie, 2024. "Option pricing revisited: The role of price volatility and dynamics," Journal of Commodity Markets, Elsevier, vol. 33(C).
    3. Shafiullah, Muhammad & Senthilkumar, Arunachalam & Lucey, Brian M. & Naeem, Muhammad Abubakr, 2024. "Deciphering asymmetric spillovers in US industries: Insights from higher-order moments," Research in International Business and Finance, Elsevier, vol. 70(PA).
    4. 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.
    5. 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).
    6. Qicheng Zhao & Zhouwei Wang & Yuping Song, 2024. "Systematic Research on Multi-dimensional and Multiple Correlation Contagion Networks of Extreme Risk in China’s Banking Industry," Computational Economics, Springer;Society for Computational Economics, vol. 64(2), pages 1137-1162, August.
    7. Chavas, Jean-Paul & Li, Jian & Wang, Linjie, 2024. "Option Pricing Revisited: The Role of Price Volatility and Dynamics," 2024 Annual Meeting, July 28-30, New Orleans, LA 343544, Agricultural and Applied Economics Association.
    8. Karim, Sitara & Shafiullah, Muhammad & Naeem, Muhammad Abubakr, 2024. "When one domino falls, others follow: A machine learning analysis of extreme risk spillovers in developed stock markets," International Review of Financial Analysis, Elsevier, vol. 93(C).
    9. 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.

  6. Jozef Baruník & Evžen KoÄ enda, 2019. "Total, Asymmetric and Frequency Connectedness between Oil and Forex Markets," The Energy Journal, , vol. 40(2_suppl), pages 157-174, December.
    See citations under working paper version above.
  7. 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.
  8. 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.
  9. 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.
  10. 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.
  11. 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.
  12. 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. Chao Wang & Richard Gerlach, 2019. "Semi-parametric Realized Nonlinear Conditional Autoregressive Expectile and Expected Shortfall," Papers 1906.09961, arXiv.org.
    3. 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.

  13. 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.
  14. 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.
  15. 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.
  16. 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. Okorie, David Iheke & Lin, Boqiang, 2022. "Givers never lack: Nigerian oil & gas asymmetric network analyses," Energy Economics, Elsevier, vol. 108(C).
    3. 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).
    4. 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.
    5. Guan, Bo & Mazouz, Khelifa & Xu, Yongdeng, 2024. "Asymmetric volatility spillover between crude oil and other asset markets," Energy Economics, Elsevier, vol. 130(C).
    6. Davide Ciferri & Maria Chiara D’Errico & Paolo Polinori, 2020. "Integration and convergence in European electricity markets," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 37(2), pages 463-492, July.
    7. 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.
    8. 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).
    9. 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.
    10. Hung Do & Rabindra Nepal & Russell Smyth, 2020. "Interconnectedness in the Australian national electricity market: A higher moment analysis," CAMA Working Papers 2020-49, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    11. Han, Lin & Kordzakhia, Nino & Trück, Stefan, 2020. "Volatility spillovers in Australian electricity markets," Energy Economics, Elsevier, vol. 90(C).
    12. 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).
    13. 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).
    14. 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.
    15. 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).
    16. Sheikh, Umaid A. & Asadi, Mehrad & Roubaud, David & Hammoudeh, Shawkat, 2024. "Global uncertainties and Australian financial markets: Quantile time-frequency connectedness," International Review of Financial Analysis, Elsevier, vol. 92(C).
    17. Lovcha, Yuliya & Perez-Laborda, Alejandro, 2020. "Dynamic frequency connectedness between oil and natural gas volatilities," Economic Modelling, Elsevier, vol. 84(C), pages 181-189.
    18. 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).
    19. 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).
    20. 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).
    21. 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.
    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. 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.
    24. 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.
    25. 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.
    26. Xiao, Jihong & Wang, Yudong, 2021. "Investor attention and oil market volatility: Does economic policy uncertainty matter?," Energy Economics, Elsevier, vol. 97(C).
    27. Afees A. Salisu & Raymond Swaray, 2017. "Forecasting the return volatility of energy prices: A GARCH MIDAS approach," Working Papers 029, Centre for Econometric and Allied Research, University of Ibadan.
    28. Apergis, Nicholas & Pan, Wei-Fong & Reade, James & Wang, Shixuan, 2023. "Modelling Australian electricity prices using indicator saturation," Energy Economics, Elsevier, vol. 120(C).
    29. 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.
    30. 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).
    31. Pan, Wenchao & Guo, Zhichen & Zhang, Jiayan Shi Yaxuan & Luo, Lingle, 2024. "Forecasting of coal and electricity prices in China: Evidence from the quantum bee colony-support vector regression neural network," Energy Economics, Elsevier, vol. 134(C).
    32. Ren, Xiaocong & Huang, Zilong & He, Yiqun, 2024. "Financial warning for coal mining investments: Evidence from the fruit fly optimisation algorithm with backpropagation neural networks," Energy Economics, Elsevier, vol. 134(C).
    33. 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).
    34. 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.
    35. 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).
    36. 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.
    37. Lovcha, Yuliya & Perez-Laborda, Alejandro, 2022. "Long-memory and volatility spillovers across petroleum futures," Energy, Elsevier, vol. 243(C).
    38. 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).
    39. Awaworyi Churchill, Sefa & Smyth, Russell & Farrell, Lisa, 2020. "Fuel poverty and subjective wellbeing," Energy Economics, Elsevier, vol. 86(C).
    40. Wang, Hu & Li, Shouwei, 2021. "Asymmetric volatility spillovers between crude oil and China's financial markets," Energy, Elsevier, vol. 233(C).
    41. 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.
    42. Chen, Huayi & Shi, Huai-Long & Zhou, Wei-Xing, 2024. "Carbon volatility connectedness and the role of external uncertainties: Evidence from China," Journal of Commodity Markets, Elsevier, vol. 33(C).
    43. 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.
    44. Asafo-Adjei, Emmanuel & Tiwari, Aviral Kumar & Abakah, Emmanuel Joel Aikins & Lee, Chi-Chuan, 2024. "Risk synchronization in Australia stock market: A sector analysis," International Review of Economics & Finance, Elsevier, vol. 93(PA), pages 582-610.
    45. 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.
    46. 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.
    47. 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.
    48. 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).
    49. 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.

  17. 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.
  18. 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.
  19. 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.
  20. 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. 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).
    2. Cipollini, Andrea & Lo Cascio, Iolanda & Muzzioli, Silvia, 2018. "Risk aversion connectedness in five European countries," Economic Modelling, Elsevier, vol. 71(C), pages 68-79.
    3. 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.
    4. 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.

  21. 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.
  22. 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.
  23. 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.
  24. 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.
  25. 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.
  26. 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. Morten Ø. Nielsen & S Johansen, 2018. "Nonstationary Cointegration In The Fractionally Cointegrated Var Model," Working Paper 1405, Economics Department, Queen's University.
    2. Cipollini, Andrea & Lo Cascio, Iolanda & Muzzioli, Silvia, 2018. "Risk aversion connectedness in five European countries," Economic Modelling, Elsevier, vol. 71(C), pages 68-79.
    3. Yaya, OaOluwa S & Vo, Xuan Vinh & Ogbonna, Ahamuefula E & Adewuyi, Adeolu O, 2020. "Modelling Cryptocurrency High-Low Prices using Fractional Cointegrating VAR," MPRA Paper 102190, University Library of Munich, Germany, revised 02 Aug 2020.
    4. Stoupos, Nikolaos & Kiohos, Apostolos, 2021. "Energy commodities and advanced stock markets: A post-crisis approach," Resources Policy, Elsevier, vol. 70(C).
    5. 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.
    6. 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.
    7. Monge, Manuel & Claudio-Quiroga, Gloria & Poza, Carlos, 2024. "Chinese economic behavior in times of covid-19. A new leading economic indicator based on Google trends," International Economics, Elsevier, vol. 177(C).
    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. 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.
    10. 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).
    11. 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).

  27. 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.
  28. 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.
  29. 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.
  30. 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.
  31. 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. 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.
    2. 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.
    3. Milan Szabo, 2020. "Growth-at-Risk: Bayesian Approach," Working Papers 2020/3, Czech National Bank.
    4. 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.
    5. 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.
    6. Milan Szabo & Zlatuse Komarkova & Martin Casta, 2020. "Vulnerable growth: Bayesian GDP-at-Risk," Occasional Publications - Chapters in Edited Volumes,, Czech National Bank.
    7. Michal Franta, 2013. "The Effect of Non-Linearity Between Credit Conditions and Economic Activity on Density Forecasts," Working Papers 2013/09, Czech National Bank.
    8. Irving Fisher Committee, 2017. "Statistical implications of the new financial landscape," IFC Bulletins, Bank for International Settlements, number 43.
    9. 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.
    10. 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.
    11. 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.
    12. Farooq Akram & Andrew Binning & Junior Maih, 2016. "Joint prediction bands for macroeconomic risk management," Working Paper 2016/7, Norges Bank.
    13. Ohnsorge,Franziska Lieselotte & Stocker,Marc & Some,Modeste Y., 2016. "Quantifying uncertainties in global growth forecasts," Policy Research Working Paper Series 7770, The World Bank.
    14. 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.
    15. 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.
    16. 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.
    17. 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.

  32. 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.
  33. 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.
  34. 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.
  35. 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, 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.
    2. Jan Polach & Jiri Kukacka, 2016. "Prospect Theory in the Heterogeneous Agent Model," Working Papers IES 2016/14, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Jul 2016.
    3. 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.

  36. 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.
  37. 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.
  38. 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.
  39. 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. 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.
    2. 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.

  40. 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.
  41. 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.
  42. 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. 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.
    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. 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.

  43. 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. 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.

  44. 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. 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.
    2. 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.
    3. 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.
    4. Jan Polach & Jiri Kukacka, 2016. "Prospect Theory in the Heterogeneous Agent Model," Working Papers IES 2016/14, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Jul 2016.
    5. 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.

  45. 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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