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Štefan Lyócsa
(Stefan Lyocsa)

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. Lyócsa, Štefan & Baumöhl, Eduard & Vŷrost, Tomáš, 2021. "YOLO trading: Riding with the herd during the GameStop episode," EconStor Preprints 230679, ZBW - Leibniz Information Centre for Economics.

    Cited by:

    1. Nobanee, Haitham & Ellili, Nejla Ould Daoud, 2023. "What do we know about meme stocks? A bibliometric and systematic review, current streams, developments, and directions for future research," International Review of Economics & Finance, Elsevier, vol. 85(C), pages 589-602.
    2. Li-Chen Cheng & Wei-Ting Lu & Benjamin Yeo, 2023. "Predicting abnormal trading behavior from internet rumor propagation: a machine learning approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-23, December.
    3. Felix Reichenbach & Martin Walther, 2023. "Financial recommendations on Reddit, stock returns and cumulative prospect theory," Digital Finance, Springer, vol. 5(2), pages 421-448, June.
    4. Yousaf, Imran & Pham, Linh & Goodell, John W., 2023. "The connectedness between meme tokens, meme stocks, and other asset classes: Evidence from a quantile connectedness approach," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    5. Halousková, Martina & Stašek, Daniel & Horváth, Matúš, 2022. "The role of investor attention in global asset price variation during the invasion of Ukraine," Finance Research Letters, Elsevier, vol. 50(C).
    6. Kwansoo Kim & Sang-Yong Tom Lee & Robert J. Kauffman, 2023. "Social informedness and investor sentiment in the GameStop short squeeze," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-24, December.
    7. Suchanek, Max, 2024. "Social interactions in short squeeze scenarios," International Review of Economics & Finance, Elsevier, vol. 91(C), pages 898-919.
    8. Lyócsa, Štefan & Halousková, Martina & Haugom, Erik, 2023. "The US banking crisis in 2023: Intraday attention and price variation of banks at risk," Finance Research Letters, Elsevier, vol. 57(C).
    9. Banerjee, Ameet Kumar & Sensoy, Ahmet & Goodell, John W. & Mahapatra, Biplab, 2024. "Impact of media hype and fake news on commodity futures prices: A deep learning approach over the COVID-19 period," Finance Research Letters, Elsevier, vol. 59(C).

  2. Lyócsa, Štefan & Baumöhl, Eduard & Výrost, Tomáš & Molnár, Peter, 2020. "Fear of the coronavirus and the stock markets," EconStor Preprints 219336, ZBW - Leibniz Information Centre for Economics.

    Cited by:

    1. Lyócsa, Štefan & Molnár, Peter, 2020. "Stock market oscillations during the corona crash: The role of fear and uncertainty," Finance Research Letters, Elsevier, vol. 36(C).
    2. Kamal, Javed Bin & Wohar, Mark, 2023. "Heterogenous responses of stock markets to covid related news and sentiments: Evidence from the 1st year of pandemic," International Economics, Elsevier, vol. 173(C), pages 68-85.
    3. Costola, Michele & Hinz, Oliver & Nofer, Michael & Pelizzon, Loriana, 2023. "Machine learning sentiment analysis, COVID-19 news and stock market reactions," Research in International Business and Finance, Elsevier, vol. 64(C).
    4. Linhai Zhao & Ehsan Rasoulinezhad & Tapan Sarker & Farhad Taghizadeh-Hesary, 2023. "Effects of COVID-19 on Global Financial Markets: Evidence from Qualitative Research for Developed and Developing Economies," The European Journal of Development Research, Palgrave Macmillan;European Association of Development Research and Training Institutes (EADI), vol. 35(1), pages 148-166, February.
    5. Ștefan Cristian Gherghina & Daniel Ștefan Armeanu & Camelia Cătălina Joldeș, 2020. "Stock Market Reactions to COVID-19 Pandemic Outbreak: Quantitative Evidence from ARDL Bounds Tests and Granger Causality Analysis," IJERPH, MDPI, vol. 17(18), pages 1-35, September.
    6. Nikolaos Apostolopoulos & Panagiotis Liargovas & Nikolaos Rodousakis & George Soklis, 2022. "COVID-19 in US Economy: Structural Analysis and Policy Proposals," Sustainability, MDPI, vol. 14(13), pages 1-15, June.
    7. Nepp, Alexander & Okhrin, Ostap & Egorova, Julia & Dzhuraeva, Zarnigor & Zykov, Alexander, 2022. "What threatens stock markets more - The coronavirus or the hype around it?," International Review of Economics & Finance, Elsevier, vol. 78(C), pages 519-539.
    8. Suripto & Supriyanto, 2021. "The Effect of the COVID-19 Pandemic on Stock Prices with the Event Window Approach: A Case Study of State Gas Companies, in the Energy Sector," International Journal of Energy Economics and Policy, Econjournals, vol. 11(3), pages 155-162.
    9. Alshater, Muneer M. & Alqaralleh, Huthaifa & El Khoury, Rim, 2023. "Dynamic asymmetric connectedness in technological sectors," The Journal of Economic Asymmetries, Elsevier, vol. 27(C).
    10. Munusamy Dharani & M. Kabir Hassan & Makeen Huda & Mohammad Zoynul Abedin, 2023. "Covid-19 pandemic and stock returns in India," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 47(1), pages 251-266, March.
    11. Willem Thorbecke, 2020. "The Impact of the COVID-19 Pandemic on the U.S. Economy: Evidence from the Stock Market," JRFM, MDPI, vol. 13(10), pages 1-30, October.
    12. Iyer, Subramanian Rama & Simkins, Betty J., 2022. "COVID-19 and the Economy: Summary of research and future directions," Finance Research Letters, Elsevier, vol. 47(PB).
    13. Dash, Saumya Ranjan & Maitra, Debasish, 2022. "The COVID-19 pandemic uncertainty, investor sentiment, and global equity markets: Evidence from the time-frequency co-movements," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    14. Szczygielski, Jan Jakub & Charteris, Ailie & Bwanya, Princess Rutendo & Brzeszczyński, Janusz, 2023. "Which COVID-19 information really impacts stock markets?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 84(C).
    15. Papadamou, Stephanos & Fassas, Athanasios P. & Kenourgios, Dimitris & Dimitriou, Dimitrios, 2023. "Effects of the first wave of COVID-19 pandemic on implied stock market volatility: International evidence using a google trend measure," The Journal of Economic Asymmetries, Elsevier, vol. 28(C).
    16. Möller, Rouven & Reichmann, Doron, 2023. "COVID-19 related TV news and stock returns: Evidence from major US TV stations," The Quarterly Review of Economics and Finance, Elsevier, vol. 87(C), pages 95-109.
    17. Cervantes, Paula & Díaz, Antonio & Esparcia, Carlos & Huélamo, Diego, 2022. "The impact of COVID-19 induced panic on stock market returns: A two-year experience," Economic Analysis and Policy, Elsevier, vol. 76(C), pages 1075-1097.
    18. Puhr, Harald & Müllner, Jakob, 2022. "Foreign to all but fluent in many: The effect of multinationality on shock resilience," Journal of World Business, Elsevier, vol. 57(6).
    19. Bermudez, P. de Zea & Marín, J. Miguel & Rue, Håvard & Veiga, Helena, 2024. "Integrated nested Laplace approximations for threshold stochastic volatility models," Econometrics and Statistics, Elsevier, vol. 30(C), pages 15-35.
    20. Mazumder, Sharif & Saha, Pritam, 2021. "COVID-19: Fear of pandemic and short-term IPO performance," Finance Research Letters, Elsevier, vol. 43(C).
    21. Halousková, Martina & Stašek, Daniel & Horváth, Matúš, 2022. "The role of investor attention in global asset price variation during the invasion of Ukraine," Finance Research Letters, Elsevier, vol. 50(C).
    22. 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).
    23. Tiwari, Aviral Kumar & Abakah, Emmanuel Joel Aikins & Bonsu, Christiana Osei & Karikari, Nana Kwasi & Hammoudeh, Shawkat, 2022. "The effects of public sentiments and feelings on stock market behavior: Evidence from Australia," Journal of Economic Behavior & Organization, Elsevier, vol. 193(C), pages 443-472.
    24. Lyócsa, Štefan & Baumöhl, Eduard & Výrost, Tomáš, 2022. "YOLO trading: Riding with the herd during the GameStop episode," Finance Research Letters, Elsevier, vol. 46(PA).
    25. Lyócsa, Štefan & Halousková, Martina & Haugom, Erik, 2023. "The US banking crisis in 2023: Intraday attention and price variation of banks at risk," Finance Research Letters, Elsevier, vol. 57(C).
    26. Naidu, Dharmendra & Ranjeeni, Kumari, 2021. "Effect of coronavirus fear on the performance of Australian stock returns: Evidence from an event study," Pacific-Basin Finance Journal, Elsevier, vol. 66(C).
    27. Lo, Gaye-Del & Marcelin, Isaac & Bassène, Théophile & Sène, Babacar, 2022. "The Russo-Ukrainian war and financial markets: the role of dependence on Russian commodities," Finance Research Letters, Elsevier, vol. 50(C).
    28. Michele Costola & Michael Donadelli & Luca Gerotto & Ivan Gufler, 2022. "Global risks, the macroeconomy, and asset prices," Empirical Economics, Springer, vol. 63(5), pages 2357-2388, November.
    29. Matos, Paulo & Costa, Antonio & da Silva, Cristiano, 2021. "COVID-19, stock market and sectoral contagion in US: a time-frequency analysis," Research in International Business and Finance, Elsevier, vol. 57(C).
    30. Emre Cevik & Buket Kirci Altinkeski & Emrah Ismail Cevik & Sel Dibooglu, 2022. "Investor sentiments and stock markets during the COVID-19 pandemic," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-34, December.
    31. Fiszeder, Piotr & Fałdziński, Marcin & Molnár, Peter, 2023. "Attention to oil prices and its impact on the oil, gold and stock markets and their covariance," Energy Economics, Elsevier, vol. 120(C).
    32. Kang, Yong Joo & Park, Dojoon & Eom, Young Ho, 2024. "Global contagion of US COVID-19 panic news," Emerging Markets Review, Elsevier, vol. 59(C).
    33. Szczygielski, Jan Jakub & Charteris, Ailie & Bwanya, Princess Rutendo & Brzeszczyński, Janusz, 2024. "Google search trends and stock markets: Sentiment, attention or uncertainty?," International Review of Financial Analysis, Elsevier, vol. 91(C).
    34. Szczygielski, Jan Jakub & Charteris, Ailie & Obojska, Lidia, 2023. "Do commodity markets catch a cold from stock markets? Modelling uncertainty spillovers using Google search trends and wavelet coherence," International Review of Financial Analysis, Elsevier, vol. 87(C).
    35. Le, Thai-Ha & Le, Anh Tu & Le, Ha-Chi, 2021. "The historic oil price fluctuation during the Covid-19 pandemic: What are the causes?," Research in International Business and Finance, Elsevier, vol. 58(C).
    36. Au Yong, Hue Hwa & Laing, Elaine, 2021. "Stock market reaction to COVID-19: Evidence from U.S. Firms’ International exposure," International Review of Financial Analysis, Elsevier, vol. 76(C).
    37. Su, Zhi & Liu, Peng & Fang, Tong, 2022. "Pandemic-induced fear and stock market returns: Evidence from China," Global Finance Journal, Elsevier, vol. 54(C).
    38. Akhtaruzzaman, Md & Boubaker, Sabri & Umar, Zaghum, 2022. "COVID–19 media coverage and ESG leader indices," Finance Research Letters, Elsevier, vol. 45(C).
    39. Zhang, Junru & Zheng, Chen & Shan, Yuan George, 2024. "What accounts for the effect of sustainability engagement on stock price crash risk during the COVID-19 pandemic—Agency theory or legitimacy theory?," International Review of Financial Analysis, Elsevier, vol. 93(C).
    40. Aloui, Donia & Zouaoui, Riadh & Rachdi, Houssem & Guesmi, Khaled & Yarovaya, Larisa, 2024. "The impact of ECB’s Quantitative Easing on cryptocurrency markets during times of crisis," Research in International Business and Finance, Elsevier, vol. 69(C).
    41. Debalke, Negash Mulatu, 2023. "Examining volatility and spillover effects between markets for sovereign bonds of African countries and the world’s long term interest rate," MPRA Paper 117491, University Library of Munich, Germany.

  3. Výrost, Tomas & Lyócsa, Štefan & Baumöhl, Eduard, 2018. "Network-based asset allocation strategies," EconStor Preprints 180063, ZBW - Leibniz Information Centre for Economics.

    Cited by:

    1. Mengting Li & Qifa Xu & Cuixia Jiang & Yezheng Liu, 2024. "The role of long‐ and short‐run correlation networks in international portfolio selection," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(3), pages 3147-3176, July.
    2. Yizhuo Zhang & Rui Chen & Ding Ma, 2020. "A Weighted and Directed Perspective of Global Stock Market Connectedness: A Variance Decomposition and GERGM Framework," Sustainability, MDPI, vol. 12(11), pages 1-23, June.
    3. Xu, Yuhong & Zhao, Xinyao, 2024. "How does node centrality in a financial network affect asset price prediction?," The North American Journal of Economics and Finance, Elsevier, vol. 73(C).
    4. Deev, Oleg & Lyócsa, Štefan, 2020. "Connectedness of financial institutions in Europe: A network approach across quantiles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 550(C).
    5. Vito Ciciretti & Alberto Pallotta, 2024. "Network Risk Parity: graph theory-based portfolio construction," Journal of Asset Management, Palgrave Macmillan, vol. 25(2), pages 136-146, March.
    6. Zhong, Yannan & Xu, Weijun & Li, Hongyi & Zhong, Weiwei, 2024. "Distributed mean reversion online portfolio strategy with stock network," European Journal of Operational Research, Elsevier, vol. 314(3), pages 1143-1158.
    7. Wang, Yifu & Lu, Wanbo & Lin, Min-Bin & Ren, Rui & Härdle, Wolfgang Karl, 2024. "Cross-exchange crypto risk: A high-frequency dynamic network perspective," International Review of Financial Analysis, Elsevier, vol. 94(C).
    8. Yajie Yang & Longfeng Zhao & Lin Chen & Chao Wang & Jihui Han, 2021. "Portfolio optimization with idiosyncratic and systemic risks for financial networks," Papers 2111.11286, arXiv.org.
    9. Esmalifalak, Hamidreza, 2022. "Euclidean (dis)similarity in financial network analysis," Global Finance Journal, Elsevier, vol. 53(C).
    10. Mengting Li & Qifa Xu & Cuixia Jiang & Qinna Zhao, 2023. "The role of tail network topological characteristic in portfolio selection: A TNA‐PMC model," International Review of Finance, International Review of Finance Ltd., vol. 23(1), pages 37-57, March.
    11. Mayoral, Silvia & Moreno, David & Zareei, Abalfazl, 2022. "Using a hedging network to minimize portfolio risk," Finance Research Letters, Elsevier, vol. 44(C).
    12. Xu, Qifa & Li, Mengting & Jiang, Cuixia, 2021. "Network-augmented time-varying parametric portfolio selection: Evidence from the Chinese stock market," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    13. Ben Amor, Souhir & Althof, Michael & Härdle, Wolfgang Karl, 2022. "Financial Risk Meter for emerging markets," Research in International Business and Finance, Elsevier, vol. 60(C).
    14. Ciciretti, Vito & Bucci, Andrea, 2023. "Building optimal regime-switching portfolios," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    15. Nicolás Magner & Jaime F. Lavín & Mauricio A. Valle, 2022. "Modeling Synchronization Risk among Sustainable Exchange Trade Funds: A Statistical and Network Analysis Approach," Mathematics, MDPI, vol. 10(19), pages 1-30, October.
    16. Du, Ruijin & Dong, Gaogao & Tian, Lixin & Wang, Yougui & Zhao, Longfeng & Zhang, Xin & Vilela, André L.M. & Stanley, H. Eugene, 2019. "Identifying the peak point of systemic risk in international crude oil importing trade," Energy, Elsevier, vol. 176(C), pages 281-291.

  4. Baumöhl, Eduard & Lyócsa, Štefan, 2017. "Directional predictability from stock market sector indices to gold: A cross-quantilogram analysis," MPRA Paper 76915, University Library of Munich, Germany.

    Cited by:

    1. Kang, Sang Hoon & Arreola Hernandez, Jose & Rehman, Mobeen Ur & Shahzad, Syed Jawad Hussain & Yoon, Seong-Min, 2023. "Spillovers and hedging between US equity sectors and gold, oil, islamic stocks and implied volatilities," Resources Policy, Elsevier, vol. 81(C).
    2. Syuhada, Khreshna & Hakim, Arief & Suprijanto, Djoko & Muchtadi-Alamsyah, Intan & Arbi, Lukman, 2022. "Is Tether a safe haven of safe haven amid COVID-19? An assessment against Bitcoin and oil using improved measures of risk," Resources Policy, Elsevier, vol. 79(C).
    3. Arif, Muhammad & Naeem, Muhammad Abubakr & Farid, Saqib & Nepal, Rabindra & Jamasb, Tooraj, 2022. "Diversifier or more? Hedge and safe haven properties of green bonds during COVID-19," Energy Policy, Elsevier, vol. 168(C).
    4. Ali, Sajid & Bouri, Elie & Czudaj, Robert Lukas & Shahzad, Syed Jawad Hussain, 2020. "Revisiting the valuable roles of commodities for international stock markets," Resources Policy, Elsevier, vol. 66(C).
    5. Corbet, Shaen & Katsiampa, Paraskevi & Lau, Chi Keung Marco, 2020. "Measuring quantile dependence and testing directional predictability between Bitcoin, altcoins and traditional financial assets," International Review of Financial Analysis, Elsevier, vol. 71(C).
    6. Hampl, Filip & Vágnerová Linnertová, Dagmar & Horváth, Matúš, 2024. "Crypto havens during war times? Evidence from the Russian invasion of Ukraine," The North American Journal of Economics and Finance, Elsevier, vol. 71(C).
    7. Sohag, Kazi & Shams, S.M. Riad & Gainetdinova, Anna & Nappo, Fabio, 2023. "Frequency connectedness and cross-quantile dependence among medicare, medicine prices and health-tech equity," Technovation, Elsevier, vol. 120(C).
    8. Sokhanvar, Amin & Hammoudeh, Shawkat, 2024. "Comparative analysis of responses of risky and safe haven assets to stock market risk before and after the yield curve inversions in the U.S," International Review of Economics & Finance, Elsevier, vol. 94(C).
    9. Algieri, Bernardina & Leccadito, Arturo, 2019. "Ask CARL: Forecasting tail probabilities for energy commodities," Energy Economics, Elsevier, vol. 84(C).
    10. Al-Yahyaee, Khamis Hamed & Mensi, Walid & Rehman, Mobeen Ur & Vo, Xuan Vinh & Kang, Sang Hoon, 2020. "Do Islamic stocks outperform conventional stock sectors during normal and crisis periods? Extreme co-movements and portfolio management analysis," Pacific-Basin Finance Journal, Elsevier, vol. 62(C).
    11. Hasan, Md. Bokhtiar & Hassan, M. Kabir & Alhomaidi, Asem, 2023. "How do sectoral Islamic equity markets react to geopolitical risk, economic policy uncertainty, and oil price shocks?," The Journal of Economic Asymmetries, Elsevier, vol. 28(C).
    12. Staněk Gyönyör, Lucie & Horváth, Matúš, 2024. "Does ESG affect stock market dependence? An empirical exploration of S&P 1200 companies shows the divergent nature of E–S–G pillars," Research in International Business and Finance, Elsevier, vol. 69(C).
    13. Ali, Fahad & Bouri, Elie & Naifar, Nader & Shahzad, Syed Jawad Hussain & AlAhmad, Mohammad, 2022. "An examination of whether gold-backed Islamic cryptocurrencies are safe havens for international Islamic equity markets," Research in International Business and Finance, Elsevier, vol. 63(C).
    14. Donald Lien & Zijun Wang, 2019. "Quantile information share," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(1), pages 38-55, January.
    15. Chang, Hao-Wen & Chang, Tsangyao & Wang, Mei-Chih, 2024. "Revisit the impact of exchange rate on stock market returns during the pandemic period," The North American Journal of Economics and Finance, Elsevier, vol. 70(C).
    16. Giovanni De Luca & Monica Rosciano, 2020. "Quantile Dependence in Tourism Demand Time Series: Evidence in the Southern Italy Market," Sustainability, MDPI, vol. 12(8), pages 1-18, April.
    17. Patel, Ritesh & Gubareva, Mariya & Chishti, Muhammad Zubair, 2024. "Assessing the connectedness between cryptocurrency environment attention index and green cryptos, energy cryptos, and green financial assets," Research in International Business and Finance, Elsevier, vol. 70(PA).
    18. Bouri, Elie & Jalkh, Naji, 2024. "Flight-to-safety across time and market conditions," International Review of Economics & Finance, Elsevier, vol. 94(C).
    19. Lv, Wendai & Li, Bin, 2023. "Climate policy uncertainty and stock market volatility: Evidence from different sectors," Finance Research Letters, Elsevier, vol. 51(C).
    20. Aviral Kumar Tiwari & Muhammad Shahbaz & Rabeh Khalfaoui & Rizwan Ahmed & Shawkat Hammoudeh, 2024. "Directional predictability from energy markets to exchange rates and stock markets in the emerging market countries (E7 + 1): New evidence from cross‐quantilogram approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(1), pages 719-789, January.
    21. Imran, Zulfiqar Ali & Ahad, Muhammad & Shahzad, Khurram & Ahmad, Mobeen & Hameed, Imran, 2024. "Safe haven properties of industrial stocks against ESG in the United States: Portfolio implication for sustainable investments," Energy Economics, Elsevier, vol. 136(C).
    22. Imran, Zulfiqar Ali & Ahad, Muhammad, 2023. "Safe-haven properties of green bonds for industrial sectors (GICS) in the United States: Evidence from Covid-19 pandemic and Global Financial Crisis," Renewable Energy, Elsevier, vol. 210(C), pages 408-423.
    23. 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.
    24. Mensi, Walid & Al Rababa'a, Abdel Razzaq & Alomari, Mohammad & Vo, Xuan Vinh & Kang, Sang Hoon, 2022. "Dynamic frequency volatility spillovers and connectedness between strategic commodity and stock markets: US-based sectoral analysis," Resources Policy, Elsevier, vol. 79(C).
    25. Ghulam Mujtaba & Asima Siddique & Nader Naifar & Syed Jawad Hussain Shahzad, 2024. "Hedge and safe haven role of commodities for the US and Chinese equity markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(2), pages 2381-2414, April.
    26. Naeem, Muhammad Abubakr & Sadorsky, Perry & Karim, Sitara, 2023. "Sailing across climate-friendly bonds and clean energy stocks: An asymmetric analysis with the Gulf Cooperation Council Stock markets," Energy Economics, Elsevier, vol. 126(C).
    27. Todorova, Neda, 2017. "The intraday directional predictability of large Australian stocks: A cross-quantilogram analysis," Economic Modelling, Elsevier, vol. 64(C), pages 221-230.
    28. Lei, Heng & Xue, Minggao & Liu, Huiling & Ye, Jing, 2023. "Precious metal as a safe haven for global ESG stocks: Portfolio implications for socially responsible investing," Resources Policy, Elsevier, vol. 80(C).
    29. Bouri, Elie & Lien, Donald & Roubaud, David & Shahzad, Syed Jawad Hussain, 2018. "Directional predictability of implied volatility: From crude oil to developed and emerging stock markets," Finance Research Letters, Elsevier, vol. 27(C), pages 65-79.

  5. Eduard Baumöhl & Evžen Kocenda & Stefan Lyócsa & Tomás Vyrost, 2017. "Networks of Volatility Spillovers among Stock Markets," CESifo Working Paper Series 6476, CESifo.

    Cited by:

    1. Lyócsa, Štefan & Výrost, Tomáš & Baumöhl, Eduard, 2019. "Return spillovers around the globe: A network approach," Economic Modelling, Elsevier, vol. 77(C), pages 133-146.
    2. 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.
    3. 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).
    4. Arreola Hernandez, Jose & Kang, Sang Hoon & Shahzad, Syed Jawad Hussain & Yoon, Seong-Min, 2020. "Spillovers and diversification potential of bank equity returns from developed and emerging America," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    5. Zhang, Weiping & Zhuang, Xintian, 2019. "The stability of Chinese stock network and its mechanism," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 748-761.
    6. Palomba, Giulio & Tedeschi, Marco, 2024. "Contagion among European financial indices, evidence from a quantile VAR approach," Economic Systems, Elsevier, vol. 48(2).
    7. Siranova, Maria & Tiruneh, Menbere Workie & Fisera, Boris, 2021. "Creating the illicit capital flows network in Europe – Do the net errors and omissions follow an economic pattern?," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 955-973.
    8. Baumöhl, Eduard & Shahzad, Syed Jawad Hussain, 2019. "Quantile coherency networks of international stock markets," EconStor Preprints 194568, ZBW - Leibniz Information Centre for Economics.
    9. Yizhuo Zhang & Rui Chen & Ding Ma, 2020. "A Weighted and Directed Perspective of Global Stock Market Connectedness: A Variance Decomposition and GERGM Framework," Sustainability, MDPI, vol. 12(11), pages 1-23, June.
    10. Foglia, Matteo & Maci, Giampiero & Pacelli, Vincenzo, 2024. "FinTech and fan tokens: Understanding the risks spillover of digital asset investment," Research in International Business and Finance, Elsevier, vol. 68(C).
    11. Abubakar Jamaladeen & David E. Omoregie & Samuel F. Onipede & Nafiu A. Bashir, 2022. "A regime-switching skew-normal model of contagion in some selected stock markets," SN Business & Economics, Springer, vol. 2(12), pages 1-20, December.
    12. Deev, Oleg & Lyócsa, Štefan, 2020. "Connectedness of financial institutions in Europe: A network approach across quantiles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 550(C).
    13. Saffet Akdag & Ömer İskenderoglu & Andrew Adewale Alola, 2020. "The volatility spillover effects among risk appetite indexes: insight from the VIX and the rise," Letters in Spatial and Resource Sciences, Springer, vol. 13(1), pages 49-65, April.
    14. Jose Arreola Hernandez & Sang Hoon Kang & Seong‐Min Yoon, 2022. "Interdependence and portfolio optimisation of bank equity returns from developed and emerging Europe," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 678-696, January.
    15. Roy, Archi & Soni, Anchal & Deb, Soudeep, 2023. "A wavelet-based methodology to compare the impact of pandemic versus Russia–Ukraine conflict on crude oil sector and its interconnectedness with other energy and non-energy markets," Energy Economics, Elsevier, vol. 124(C).
    16. Jose Arreola Hernandez & Sang Hoon Kang & Ron P. McIver & Seong-Min Yoon, 2021. "Network Interdependence and Optimization of Bank Portfolios from Developed and Emerging Asia Pacific Countries," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 28(4), pages 613-647, December.
    17. Ling, Yu-Xiu & Xie, Chi & Wang, Gang-Jin, 2022. "Interconnectedness between convertible bonds and underlying stocks in the Chinese capital market: A multilayer network perspective," Emerging Markets Review, Elsevier, vol. 52(C).
    18. Ki-Hong Choi & Ron P. McIver & Salvatore Ferraro & Lei Xu & Sang Hoon Kang, 2021. "Dynamic volatility spillover and network connectedness across ASX sector markets," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 45(4), pages 677-691, October.
    19. Borjigin, Sumuya & Gao, Ting & Sun, Yafei & An, Biao, 2020. "For evil news rides fast, while good news baits later?—A network based analysis in Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 551(C).
    20. Iwanicz-Drozdowska, Małgorzata & Rogowicz, Karol & Kurowski, Łukasz & Smaga, Paweł, 2021. "Two decades of contagion effect on stock markets: Which events are more contagious?," Journal of Financial Stability, Elsevier, vol. 55(C).
    21. Yu, Honghai & Fang, Libing & Sun, Wencong, 2018. "Forecasting performance of global economic policy uncertainty for volatility of Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 931-940.
    22. Chen, Jing & Han, Qian & Ryu, Doojin & Tang, Jing, 2022. "Does the world smile together? A network analysis of global index option implied volatilities," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 77(C).
    23. Qiu, Lu & Yang, Huijie, 2020. "Transfer entropy calculation for short time sequences with application to stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 559(C).
    24. Wen, Tiange & Wang, Gang-Jin, 2020. "Volatility connectedness in global foreign exchange markets," Journal of Multinational Financial Management, Elsevier, vol. 54(C).
    25. Huang, Jionghao & Li, Ziruo & Xia, Xiaohua, 2021. "Network diffusion of international oil volatility risk in China's stock market: Quantile interconnectedness modelling and shock decomposition analysis," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 1-39.
    26. Wang, Ze & Gao, Xiangyun & An, Haizhong & Tang, Renwu & Sun, Qingru, 2020. "Identifying influential energy stocks based on spillover network," International Review of Financial Analysis, Elsevier, vol. 68(C).
    27. Zhang, Weiping & Zhuang, Xintian & Wu, Dongmei, 2020. "Spatial connectedness of volatility spillovers in G20 stock markets: Based on block models analysis," Finance Research Letters, Elsevier, vol. 34(C).
    28. Mariya Paskaleva & Ani Stoykova, 2021. "The Influence of Uncertainty on Market Efficiency: Evidence from Selected European Financial Markets," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 8, pages 175-198.
    29. Akhtaruzzaman, Md & Boubaker, Sabri & Umar, Zaghum, 2022. "COVID–19 media coverage and ESG leader indices," Finance Research Letters, Elsevier, vol. 45(C).
    30. Bouri, Elie & Harb, Etienne, 2022. "The size of good and bad volatility shocks does matter for spillovers," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
    31. Guoli Mo & Chunzhi Tan & Weiguo Zhang & Xuezeng Yu, 2023. "Dynamic spatiotemporal correlation coefficient based on adaptive weight," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-43, December.
    32. Muhammad Niaz Khan & Suzanne G. M. Fifield & Nongnuch Tantisantiwong & David M. Power, 2022. "Changes in co-movement and risk transmission between South Asian stock markets amidst the development of regional co-operation," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 36(1), pages 87-117, March.

  6. Roman Horváth & Štefan Lyócsa & Eduard Baumöhl, 2016. "Stock Market Contagion in Central and Eastern Europe: Unexpected Volatility and Extreme Co-exceedance," Working Papers 357, Leibniz Institut für Ost- und Südosteuropaforschung (Institute for East and Southeast European Studies).

    Cited by:

    1. Adriana AnaMaria Davidescu & Eduard Mihai Manta & Razvan Gabriel Hapau & Mihaela Gruiescu & Oana Mihaela Vacaru (Boita), 2023. "Exploring the Contagion Effect from Developed to Emerging CEE Financial Markets," Mathematics, MDPI, vol. 11(3), pages 1-50, January.
    2. Hsiao, Cody Yu-Ling & Chiu, Yi-Bin, 2024. "Financial contagion and networks among the oil and BRICS stock markets during seven episodes of crisis events," Journal of International Money and Finance, Elsevier, vol. 144(C).
    3. Peter Arendas & Jana Kotlebova, 2019. "The Turn of the Month Effect on CEE Stock Markets," IJFS, MDPI, vol. 7(4), pages 1-19, October.
    4. Pavel Gertler & Roman Horváth & Júlia Jonášová, 2020. "Central Bank Communication and Financial Market Comovements in the Euro Area," Open Economies Review, Springer, vol. 31(2), pages 257-272, April.
    5. Lu, Xunfa & He, Pengchao & Zhang, Zhengjun & Apergis, Nicholas & Roubaud, David, 2024. "Extreme co-movements between decomposed oil price shocks and sustainable investments," Energy Economics, Elsevier, vol. 134(C).
    6. 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.

  7. Stefan Lyocsa & Tomas Vyrost & Eduard Baumohl, 2015. "Return spillovers around the globe: A network approach," Papers 1507.06242, arXiv.org, revised Nov 2015.

    Cited by:

    1. Lyócsa, Štefan & Výrost, Tomáš & Baumöhl, Eduard, 2019. "Return spillovers around the globe: A network approach," Economic Modelling, Elsevier, vol. 77(C), pages 133-146.
    2. 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.
    3. Eva Moreno Galbis & François-Charles Wolff & Arnaud Herault, 2020. "How helpful are social networks in finding a job along the economic cycle? Evidence from immigrants in France," Post-Print hal-02944389, HAL.
    4. Wang, Ze & Gao, Xiangyun & Huang, Shupei & Sun, Qingru & Chen, Zhihua & Tang, Renwu & Di, Zengru, 2022. "Measuring systemic risk contribution of global stock markets: A dynamic tail risk network approach," International Review of Financial Analysis, Elsevier, vol. 84(C).
    5. Niţoi, Mihai & Pochea, Maria Miruna, 2020. "Time-varying dependence in European equity markets: A contagion and investor sentiment driven analysis," Economic Modelling, Elsevier, vol. 86(C), pages 133-147.
    6. Yizhuo Zhang & Rui Chen & Ding Ma, 2020. "A Weighted and Directed Perspective of Global Stock Market Connectedness: A Variance Decomposition and GERGM Framework," Sustainability, MDPI, vol. 12(11), pages 1-23, June.
    7. Klein, Tony & Todorova, Neda, 2021. "Night trading with futures in China: The case of Aluminum and Copper," Resources Policy, Elsevier, vol. 73(C).
    8. Zhang, Weiping & Zhuang, Xintian & Wang, Jian & Lu, Yang, 2020. "Connectedness and systemic risk spillovers analysis of Chinese sectors based on tail risk network," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    9. Vidal-Llana, Xenxo & Uribe, Jorge M. & Guillén, Montserrat, 2023. "European stock market volatility connectedness: The role of country and sector membership," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    10. Zhang, Weiping & Zhuang, Xintian & Lu, Yang, 2020. "Spatial spillover effects and risk contagion around G20 stock markets based on volatility network," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    11. Borjigin, Sumuya & Gao, Ting & Sun, Yafei & An, Biao, 2020. "For evil news rides fast, while good news baits later?—A network based analysis in Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 551(C).
    12. Oussama Tilfani & Paulo Ferreira & Andreia Dionisio & My Youssef El Boukfaoui, 2020. "EU Stock Markets vs. Germany, UK and US: Analysis of Dynamic Comovements Using Time-Varying DCCA Correlation Coefficients," JRFM, MDPI, vol. 13(5), pages 1-23, May.
    13. Ren, Yinghua & Zhao, Wanru & You, Wanhai & Zhu, Huiming, 2022. "Multiscale features of extreme risk spillover networks among global stock markets," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    14. Huang, Jionghao & Li, Ziruo & Xia, Xiaohua, 2021. "Network diffusion of international oil volatility risk in China's stock market: Quantile interconnectedness modelling and shock decomposition analysis," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 1-39.

  8. Eduard Baum??hl & ??tefan Ly??csa, 2014. "How smooth is the stock market integration of CEE-3?," William Davidson Institute Working Papers Series wp1079, William Davidson Institute at the University of Michigan.

    Cited by:

    1. Anita Radman Peša & Elżbieta Wrońska-Bukalska & Jurica Bosna, 2017. "ARDL panel estimation of stock market indices and macroeconomic environment of CEE and SEE countries in the last decade of transition," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 16(3), pages 205-221, December.

  9. Tom'av{s} V'yrost & v{S}tefan Ly'ocsa & Eduard Baumohl, 2014. "Granger Causality Stock Market Networks: Temporal Proximity and Preferential Attachment," Papers 1408.2985, arXiv.org.

    Cited by:

    1. Lyócsa, Štefan & Výrost, Tomáš & Baumöhl, Eduard, 2019. "Return spillovers around the globe: A network approach," Economic Modelling, Elsevier, vol. 77(C), pages 133-146.
    2. 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.
    3. Wu, Tao & Gao, Xiangyun & An, Sufang & Liu, Siyao, 2021. "Time-varying pattern causality inference in global stock markets," International Review of Financial Analysis, Elsevier, vol. 77(C).
    4. Hua Chen & J. David Cummins & Tao Sun & Mary A. Weiss, 2020. "The Reinsurance Network Among U.S. Property–Casualty Insurers: Microstructure, Insolvency Risk, and Contagion," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 87(2), pages 253-284, June.
    5. Wang, Ze & Gao, Xiangyun & Tang, Renwu & Liu, Xueyong & Sun, Qingru & Chen, Zhihua, 2019. "Identifying influential nodes based on fluctuation conduction network model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 355-369.
    6. Tian, Hu & Zheng, Xiaolong & Zeng, Daniel Danjun, 2019. "Analyzing the dynamic sectoral influence in Chinese and American stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    7. Charakopoulos, A.K. & Katsouli, G.A. & Karakasidis, T.E., 2018. "Dynamics and causalities of atmospheric and oceanic data identified by complex networks and Granger causality analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 495(C), pages 436-453.
    8. Gong, Chen & Tang, Pan & Wang, Yutong, 2019. "Measuring the network connectedness of global stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    9. Banerjee, Ameet Kumar & Dionisio, Andreia & Pradhan, H.K. & Mahapatra, Biplab, 2021. "Hunting the quicksilver: Using textual news and causality analysis to predict market volatility," International Review of Financial Analysis, Elsevier, vol. 77(C).
    10. Siranova, Maria & Tiruneh, Menbere Workie & Fisera, Boris, 2021. "Creating the illicit capital flows network in Europe – Do the net errors and omissions follow an economic pattern?," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 955-973.
    11. Theodore Panagiotidis & Thanasis Stengos & Orestis Vravosinos, 2018. "On the determinants of bitcoin returns: a LASSO approach," Working Paper series 18-14, Rimini Centre for Economic Analysis.
    12. Štefan Lyócsa & Roman Horváth, 2018. "Stock Market Contagion: a New Approach," Open Economies Review, Springer, vol. 29(3), pages 547-577, July.
    13. Panagiotidis, Theodore & Stengos, Thanasis & Vravosinos, Orestis, 2019. "The effects of markets, uncertainty and search intensity on bitcoin returns," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 220-242.
    14. Jiang, Christine & Zhang, Xiaori & Hu, Bill, 2024. "Government reporting credibility as immunity: Evidence from a public health event," Journal of Multinational Financial Management, Elsevier, vol. 73(C).
    15. Zhou, Xuanru & Zhang, Hua & Zheng, Shuxian & Xing, Wanli & Yang, Hanshi & Zhao, Yifan, 2023. "A study on the transmission of trade behavior of global nickel products from the perspective of the industrial chain," Resources Policy, Elsevier, vol. 81(C).
    16. Gautier Marti & Frank Nielsen & Miko{l}aj Bi'nkowski & Philippe Donnat, 2017. "A review of two decades of correlations, hierarchies, networks and clustering in financial markets," Papers 1703.00485, arXiv.org, revised Nov 2020.
    17. Zhang, Weiping & Zhuang, Xintian & Wang, Jian & Lu, Yang, 2020. "Connectedness and systemic risk spillovers analysis of Chinese sectors based on tail risk network," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    18. Qingru Sun & Xiangyun Gao & Shaobo Wen & Sida Feng & Ze Wang, 2019. "Modeling the impulse response complex network for studying the fluctuation transmission of price indices," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(4), pages 835-858, December.
    19. Gang-Jin Wang & Chi Xie & Kaijian He & H. Eugene Stanley, 2017. "Extreme risk spillover network: application to financial institutions," Quantitative Finance, Taylor & Francis Journals, vol. 17(9), pages 1417-1433, September.
    20. Zhang, Weiping & Zhuang, Xintian & Lu, Yang, 2020. "Spatial spillover effects and risk contagion around G20 stock markets based on volatility network," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    21. Civitarese, Jamil, 2016. "Volatility and correlation-based systemic risk measures in the US market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 459(C), pages 55-67.
    22. Liu, Xueyong & An, Haizhong & Li, Huajiao & Chen, Zhihua & Feng, Sida & Wen, Shaobo, 2017. "Features of spillover networks in international financial markets: Evidence from the G20 countries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 265-278.
    23. Manel Youssef & Khaled Mokni & Ahdi Noomen Ajmi, 2021. "Dynamic connectedness between stock markets in the presence of the COVID-19 pandemic: does economic policy uncertainty matter?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-27, December.
    24. Zhu, Pengfei & Tang, Yong & Wei, Yu & Lu, Tuantuan, 2021. "Multidimensional risk spillovers among crude oil, the US and Chinese stock markets: Evidence during the COVID-19 epidemic," Energy, Elsevier, vol. 231(C).
    25. 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.
    26. Cynthia Sari DEWI & Florentina KURNIASARI & Helena DEWI & Eko ENDARTO & Nurhuda NIZAR, 2021. "Return Spillover Between The U.S., Japanese, And Indonesian Stock Market During Covid-19," Business Excellence and Management, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 11(5), pages 196-207, October.
    27. Huang, Qi-An & Zhao, Jun-Chan & Wu, Xiao-Qun, 2022. "Financial risk propagation between Chinese and American stock markets based on multilayer networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 586(C).
    28. Song, Jae Wook & Ko, Bonggyun & Cho, Poongjin & Chang, Woojin, 2016. "Time-varying causal network of the Korean financial system based on firm-specific risk premiums," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 458(C), pages 287-302.
    29. 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.
    30. Borjigin, Sumuya & Gao, Ting & Sun, Yafei & An, Biao, 2020. "For evil news rides fast, while good news baits later?—A network based analysis in Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 551(C).
    31. Wang, Ping & Gu, Changgui & Yang, Huijie & Wang, Haiying, 2024. "Identify causality by multi-scale structural complexity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 633(C).
    32. Banerjee, Ameet Kumar & Akhtaruzzaman, Md & Dionisio, Andreia & Almeida, Dora & Sensoy, Ahmet, 2022. "Nonlinear nexus between cryptocurrency returns and COVID-19 news sentiment," Journal of Behavioral and Experimental Finance, Elsevier, vol. 36(C).
    33. Cao, Guangxi & Han, Yan & Li, Qingchen & Xu, Wei, 2017. "Asymmetric MF-DCCA method based on risk conduction and its application in the Chinese and foreign stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 119-130.
    34. Yi Su & Yueqi Yu, 2019. "Effects of Technological Innovation Network Embeddedness on the Sustainable Development Capability of New Energy Enterprises," Sustainability, MDPI, vol. 11(20), pages 1-19, October.
    35. Qiu, Lu & Yang, Huijie, 2020. "Transfer entropy calculation for short time sequences with application to stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 559(C).
    36. Wen, Tiange & Wang, Gang-Jin, 2020. "Volatility connectedness in global foreign exchange markets," Journal of Multinational Financial Management, Elsevier, vol. 54(C).
    37. Wang, Luo-Qing & Xu, Yong-Xiang, 2018. "Assessing the relevance of individual characteristics for the structure of similarity networks in new social strata in Shanghai," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 881-889.
    38. Akhtaruzzaman, Md & Boubaker, Sabri & Umar, Zaghum, 2022. "COVID–19 media coverage and ESG leader indices," Finance Research Letters, Elsevier, vol. 45(C).
    39. Chen, Yan & Wang, Gang-Jin & Zhu, You & Xie, Chi & Uddin, Gazi Salah, 2023. "Quantile connectedness and the determinants between FinTech and traditional financial institutions: Evidence from China," Global Finance Journal, Elsevier, vol. 58(C).
    40. Badics, Milan Csaba & Huszar, Zsuzsa R. & Kotro, Balazs B., 2023. "The impact of crisis periods and monetary decisions of the Fed and the ECB on the sovereign yield curve network," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 88(C).
    41. Lahmiri, Salim, 2017. "Asymmetric and persistent responses in price volatility of fertilizers through stable and unstable periods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 405-414.
    42. Stefanos Bennett & Mihai Cucuringu & Gesine Reinert, 2022. "Lead-lag detection and network clustering for multivariate time series with an application to the US equity market," Papers 2201.08283, arXiv.org.
    43. Lahmiri, Salim, 2017. "Cointegration and causal linkages in fertilizer markets across different regimes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 181-189.

  10. Baumohl, Eduard & Lyocsa, Stefan, 2013. "Volatility and dynamic conditional correlations of European emerging stock markets," MPRA Paper 49898, University Library of Munich, Germany.

    Cited by:

    1. Dahiru A. Balaa & Taro Takimotob, 2017. "Stock markets volatility spillovers during financial crises: A DCC-MGARCH with skewed-t density approach," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 17(1), pages 25-48, March.

  11. Lyócsa, Štefan & Baumöhl, Eduard, 2012. "Testing the covariance stationarity of CEE stocks," MPRA Paper 43432, University Library of Munich, Germany.

    Cited by:

    1. Výrost, Tomáš, 2012. "Country effects in CEE3 stock market networks: a preliminary study," MPRA Paper 43481, University Library of Munich, Germany.
    2. Narcisa Kadlcakova & Lubos Komarek & Zlatuse Komarkova & Michal Hlavacek, 2016. "Identification of Asset Price Misalignments on Financial Markets With Extreme Value Theory," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 52(11), pages 2595-2609, November.

  12. Baumöhl, Eduard & Lyócsa, Štefan, 2012. "Constructing weekly returns based on daily stock market data: A puzzle for empirical research?," MPRA Paper 43431, University Library of Munich, Germany.

    Cited by:

    1. Výrost, Tomáš, 2012. "Country effects in CEE3 stock market networks: a preliminary study," MPRA Paper 43481, University Library of Munich, Germany.
    2. Výrost, Tomáš & Lyócsa, Štefan & Baumöhl, Eduard, 2015. "Granger causality stock market networks: Temporal proximity and preferential attachment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 427(C), pages 262-276.
    3. Eduard Baum??hl & ??tefan Ly??csa, 2014. "How smooth is the stock market integration of CEE-3?," William Davidson Institute Working Papers Series wp1079, William Davidson Institute at the University of Michigan.
    4. Akhtaruzzaman, Md & Boubaker, Sabri & Umar, Zaghum, 2022. "COVID–19 media coverage and ESG leader indices," Finance Research Letters, Elsevier, vol. 45(C).

  13. Výrost, Tomáš & Baumöhl, Eduard & Lyócsa, Štefan, 2011. "On the relationship of persistence and number of breaks in volatility: new evidence for three CEE countries," MPRA Paper 27927, University Library of Munich, Germany.

    Cited by:

    1. Baumöhl, Eduard & Lyócsa, Štefan, 2012. "Constructing weekly returns based on daily stock market data: A puzzle for empirical research?," MPRA Paper 43431, University Library of Munich, Germany.
    2. Lyócsa, Štefan & Baumöhl, Eduard, 2012. "Testing the covariance stationarity of CEE stocks," MPRA Paper 43432, University Library of Munich, Germany.

  14. Lyócsa, Štefan & Výrost, Tomáš & Baumöhl, Eduard, 2011. "Unit-root and stationarity testing with empirical application on industrial production of CEE-4 countries," MPRA Paper 29648, University Library of Munich, Germany.

    Cited by:

    1. Georgios Loukopoulos & Dimitrios Antonopoulos, 2015. "Purchasing Power Parity: A Unit Root, Cointegration and VAR Analysis in Emerging and Advanced Countries," Business and Economic Research, Macrothink Institute, vol. 5(1), pages 262-279, June.
    2. Vyrost, Tomas & Baumöhl, Eduard & Lyocsa, Stefan, 2013. "What Drives the Stock Market Integration in the CEE-3?," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 61(1), pages 67-81.
    3. Eduard Baumöhl & Štefan Lyócsa & Tomáš Výrost, 2011. "Volatility Regimes in Macroeconomic Time Series: The Case of the Visegrad Group," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 61(6), pages 530-544, December.
    4. Zarembova, Andrea & Lyocsa, Stefan & Baumöhl, Eduard, 2012. "The Real Convergence of CEE Countries: A Study of Real GDP per capita," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 60(6), pages 642-656.

  15. Baumöhl, Eduard & Výrost, Tomáš & Lyócsa, Štefan, 2011. "Are we able to capture the EU debt crisis? Evidence from PIIGGS countries in panel unit root framework," MPRA Paper 30334, University Library of Munich, Germany.

    Cited by:

    1. Tóth G., Csaba, 2014. "The Forecasting Capacity of Indicators Measuring Budget Sustainability," Public Finance Quarterly, Corvinus University of Budapest, vol. 59(4), pages 511-528.

  16. Baumöhl, Eduard & Lyócsa, Štefan, 2009. "Stationarity of time series and the problem of spurious regression," MPRA Paper 27926, University Library of Munich, Germany.

    Cited by:

    1. Lyócsa, Štefan & Výrost, Tomáš & Baumöhl, Eduard, 2011. "Unit-root and stationarity testing with empirical application on industrial production of CEE-4 countries," MPRA Paper 29648, University Library of Munich, Germany.
    2. Collin Chikwira, 2023. "The Foreign Exchange Auction System’s Effect on SME Stability and Performance," International Journal of Economics and Financial Issues, Econjournals, vol. 13(5), pages 96-108, September.
    3. Noveski Martin, 2018. "Macroeconomic effects of the budget deficit in the Republic of Macedonia," Croatian Review of Economic, Business and Social Statistics, Sciendo, vol. 4(2), pages 5-14, November.
    4. Jammazi, Rania & Aloui, Chaker, 2012. "Crude oil price forecasting: Experimental evidence from wavelet decomposition and neural network modeling," Energy Economics, Elsevier, vol. 34(3), pages 828-841.
    5. Madanlo, Lalaine & Murcia, John Vianne & Tamayo, Adrian, 2016. "Simultaneity of Crime Incidence in Mindanao," MPRA Paper 72648, University Library of Munich, Germany, revised 20 Jul 2016.
    6. Elena Cigu & Daniela Tatiana Agheorghiesei & Anca Florentina Gavriluță (Vatamanu) & Elena Toader, 2018. "Transport Infrastructure Development, Public Performance and Long-Run Economic Growth: A Case Study for the Eu-28 Countries," Sustainability, MDPI, vol. 11(1), pages 1-22, December.
    7. Oliver Ike Inyiama & Caroline N. Ozouli, 2014. "Interactions between Exchange Rate and Financial Performance Indicators in Nigeria Beer Industry: Evidence from Nigeria Breweries Plc," Academic Journal of Interdisciplinary Studies, Richtmann Publishing Ltd, vol. 3, November.

Articles

  1. Lyócsa, Štefan & Todorova, Neda, 2024. "Forecasting of clean energy market volatility: The role of oil and the technology sector," Energy Economics, Elsevier, vol. 132(C).

    Cited by:

    1. Chen, Zhuoyi & Liu, Yuanyuan & Zhang, Hongwei, 2024. "Can geopolitical risks impact the long-run correlation between crude oil and clean energy markets? Evidence from a regime-switching analysis," Renewable Energy, Elsevier, vol. 229(C).

  2. Lyócsa, Štefan & Halousková, Martina & Haugom, Erik, 2023. "The US banking crisis in 2023: Intraday attention and price variation of banks at risk," Finance Research Letters, Elsevier, vol. 57(C).

    Cited by:

    1. Ren, Tingting & Li, Shaofang & Zhang, Siying, 2024. "Stock market extreme risk prediction based on machine learning: Evidence from the American market," The North American Journal of Economics and Finance, Elsevier, vol. 74(C).
    2. Aharon, David Y. & Ali, Shoaib, 2024. "A high-frequency data dive into SVB collapse," Finance Research Letters, Elsevier, vol. 59(C).

  3. Lyócsa, Štefan & Baumöhl, Eduard & Výrost, Tomáš, 2022. "YOLO trading: Riding with the herd during the GameStop episode," Finance Research Letters, Elsevier, vol. 46(PA).
    See citations under working paper version above.
  4. Lyócsa, Štefan & Plíhal, Tomáš, 2022. "Russia’s ruble during the onset of the Russian invasion of Ukraine in early 2022: The role of implied volatility and attention," Finance Research Letters, Elsevier, vol. 48(C).

    Cited by:

    1. Wang, Yi-Ran & Ma, Chao-Qun & Ren, Yi-Shuai, 2022. "A model for CBDC audits based on blockchain technology: Learning from the DCEP," Research in International Business and Finance, Elsevier, vol. 63(C).
    2. Piotr Fiszeder & Marta Ma³ecka, 2022. "Forecasting volatility during the outbreak of Russian invasion of Ukraine: application to commodities, stock indices, currencies, and cryptocurrencies," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 17(4), pages 939-967, December.
    3. Umar, Muhammad & Riaz, Yasir & Yousaf, Imran, 2022. "Impact of Russian-Ukraine war on clean energy, conventional energy, and metal markets: Evidence from event study approach," Resources Policy, Elsevier, vol. 79(C).
    4. Kumar, Pawan & Singh, Vipul Kumar, 2022. "Does crude oil fire the emerging markets currencies contagion spillover? A systemic perspective," Energy Economics, Elsevier, vol. 116(C).
    5. Fang, Yi & Shao, Zhiquan, 2022. "The Russia-Ukraine conflict and volatility risk of commodity markets," Finance Research Letters, Elsevier, vol. 50(C).
    6. Pandey, Dharen Kumar & Lucey, Brian M. & Kumar, Satish, 2023. "Border disputes, conflicts, war, and financial markets research: A systematic review," Research in International Business and Finance, Elsevier, vol. 65(C).
    7. Halousková, Martina & Stašek, Daniel & Horváth, Matúš, 2022. "The role of investor attention in global asset price variation during the invasion of Ukraine," Finance Research Letters, Elsevier, vol. 50(C).
    8. Bonaparte, Yosef & Chatrath, Arjun & Christie-David, Rohan, 2023. "S&P volatility, VIX, and asymptotic volatility estimates," Finance Research Letters, Elsevier, vol. 51(C).
    9. Bonaparte, Yosef, 2023. "Introducing the Cryptocurrency VIX: CVIX✰," Finance Research Letters, Elsevier, vol. 54(C).
    10. Chortane, Sana Gaied & Pandey, Dharen Kumar, 2022. "Does the Russia-Ukraine war lead to currency asymmetries? A US dollar tale," The Journal of Economic Asymmetries, Elsevier, vol. 26(C).

  5. Deev, Oleg & Lyócsa, Štefan & Výrost, Tomáš, 2022. "The looming crisis in the Chinese stock market? Left-tail exposure analysis of Chinese stocks to Evergrande," Finance Research Letters, Elsevier, vol. 49(C).

    Cited by:

    1. Hampl, Filip & Vágnerová Linnertová, Dagmar & Horváth, Matúš, 2024. "Crypto havens during war times? Evidence from the Russian invasion of Ukraine," The North American Journal of Economics and Finance, Elsevier, vol. 71(C).
    2. Li, Guowen & Jing, Zhongbo & Li, Jingyu & Feng, Yuyao, 2023. "Drivers of risk correlation among financial institutions: A study based on a textual risk disclosure perspective," Economic Modelling, Elsevier, vol. 128(C).

  6. Lichner, Ivan & Lyócsa, Štefan & Výrostová, Eva, 2022. "Nominal and discretionary household income convergence: The effect of a crisis in a small open economy," Structural Change and Economic Dynamics, Elsevier, vol. 61(C), pages 18-31.

    Cited by:

    1. Alina CIUREA (MECA), 2022. "Impact of European Union Social Policy during Pandemic on Household Income," Economics and Applied Informatics, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, issue 3, pages 117-124.

  7. Štefan Lyócsa & Petra Vašaničová & Branka Hadji Misheva & Marko Dávid Vateha, 2022. "Default or profit scoring credit systems? Evidence from European and US peer-to-peer lending markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-21, December.

    Cited by:

    1. Gero Friedrich Bone-Winkel & Felix Reichenbach, 2024. "Improving credit risk assessment in P2P lending with explainable machine learning survival analysis," Digital Finance, Springer, vol. 6(3), pages 501-542, September.
    2. Baumöhl, Eduard & Lyócsa, Štefan & Vašaničová, Petra, 2024. "Macroeconomic environment and the future performance of loans: Evidence from three peer-to-peer platforms," International Review of Financial Analysis, Elsevier, vol. 95(PB).
    3. Chong, Zhaohui & Wei, Xiaolin, 2023. "Exploring the spatial linkage network of peer-to-peer lending in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    4. Li, Zhe & Liang, Shuguang & Pan, Xianyou & Pang, Meng, 2024. "Credit risk prediction based on loan profit: Evidence from Chinese SMEs," Research in International Business and Finance, Elsevier, vol. 67(PA).
    5. Liu, Yiting & Baals, Lennart John & Osterrieder, Jörg & Hadji-Misheva, Branka, 2024. "Network centrality and credit risk: A comprehensive analysis of peer-to-peer lending dynamics," Finance Research Letters, Elsevier, vol. 63(C).

  8. Zuzana Košťálová & Eva Horvátová & Štefan Lyócsa & Peter Gernát, 2022. "New Credit Drivers: Results from a Small Open Economy," Eastern European Economics, Taylor & Francis Journals, vol. 60(1), pages 79-112, January.

    Cited by:

    1. Baumöhl, Eduard & Lyócsa, Štefan & Vašaničová, Petra, 2024. "Macroeconomic environment and the future performance of loans: Evidence from three peer-to-peer platforms," International Review of Financial Analysis, Elsevier, vol. 95(PB).

  9. Lyócsa, Štefan & Výrost, Tomáš & Plíhal, Tomáš, 2021. "A tale of tails : New evidence on the growth-return nexus," Finance Research Letters, Elsevier, vol. 38(C).

    Cited by:

    1. Deev, Oleg & Lyócsa, Štefan & Výrost, Tomáš, 2022. "The looming crisis in the Chinese stock market? Left-tail exposure analysis of Chinese stocks to Evergrande," Finance Research Letters, Elsevier, vol. 49(C).
    2. Zuzana Košťálová & Eva Horvátová & Štefan Lyócsa & Peter Gernát, 2022. "New Credit Drivers: Results from a Small Open Economy," Eastern European Economics, Taylor & Francis Journals, vol. 60(1), pages 79-112, January.

  10. Plíhal, Tomáš & Lyócsa, Štefan, 2021. "Modeling realized volatility of the EUR/USD exchange rate: Does implied volatility really matter?," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 811-829.

    Cited by:

    1. Pham, Son Duy & Nguyen, Thao Thac Thanh & Li, Xiao-Ming, 2024. "Stabilizing global foreign exchange markets in the time of COVID-19: The role of vaccinations," Global Finance Journal, Elsevier, vol. 59(C).
    2. Emmanuel Afuecheta & Idika E. Okorie & Saralees Nadarajah & Geraldine E. Nzeribe, 2024. "Forecasting Value at Risk and Expected Shortfall of Foreign Exchange Rate Volatility of Major African Currencies via GARCH and Dynamic Conditional Correlation Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 63(1), pages 271-304, January.
    3. Miguel Lampreia & Erjola Barbullushi & Ismet Voka, 2024. "Usefulness Of Technical Analysis In The Forex Market: The Eur/Usd Pair," Sustainable Regional Development Scientific Journal, Sustainable Regional Development Scientific Journal, vol. 0(1), pages 104-112, July.
    4. Ngene, Geoffrey M. & Wang, Jinghua, 2024. "Arbitrage opportunities and feedback trading in regulated bitcoin futures market: An intraday analysis," International Review of Economics & Finance, Elsevier, vol. 89(PB), pages 743-761.
    5. 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).

  11. Lyócsa, Štefan & Plíhal, Tomáš & Výrost, Tomáš, 2021. "FX market volatility modelling: Can we use low-frequency data?," Finance Research Letters, Elsevier, vol. 40(C).

    Cited by:

    1. Pham, Son Duy & Nguyen, Thao Thac Thanh & Li, Xiao-Ming, 2024. "Stabilizing global foreign exchange markets in the time of COVID-19: The role of vaccinations," Global Finance Journal, Elsevier, vol. 59(C).
    2. Piotr Fiszeder & Marta Ma³ecka, 2022. "Forecasting volatility during the outbreak of Russian invasion of Ukraine: application to commodities, stock indices, currencies, and cryptocurrencies," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 17(4), pages 939-967, December.

  12. Lyócsa, Štefan & Todorova, Neda & Výrost, Tomáš, 2021. "Predicting risk in energy markets: Low-frequency data still matter," Applied Energy, Elsevier, vol. 282(PA).

    Cited by:

    1. Piotr Fiszeder & Marta Ma³ecka, 2022. "Forecasting volatility during the outbreak of Russian invasion of Ukraine: application to commodities, stock indices, currencies, and cryptocurrencies," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 17(4), pages 939-967, December.
    2. Zhang, Tingting & Tang, Zhenpeng & Wu, Junchuan & Du, Xiaoxu & Chen, Kaijie, 2021. "Multi-step-ahead crude oil price forecasting based on two-layer decomposition technique and extreme learning machine optimized by the particle swarm optimization algorithm," Energy, Elsevier, vol. 229(C).
    3. Diego Perrone & Angelo Algieri & Pietropaolo Morrone & Teresa Castiglione, 2021. "Energy and Economic Investigation of a Biodiesel-Fired Engine for Micro-Scale Cogeneration," Energies, MDPI, vol. 14(2), pages 1-28, January.
    4. Anis Jarboui & Emna Mnif, 2024. "Can Clean Energy Stocks Predict Crude Oil Markets Using Hybrid and Advanced Machine Learning Models?," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 31(4), pages 821-844, December.
    5. Huang, Jiefei & Xu, Yang & Song, Yuping, 2022. "A high-frequency approach to VaR measures and forecasts based on the HAR-QREG model with jumps," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P1).
    6. Kuang, Wei, 2022. "The economic value of high-frequency data in equity-oil hedge," Energy, Elsevier, vol. 239(PA).

  13. Lyócsa, Štefan & Molnár, Peter & Výrost, Tomáš, 2021. "Stock market volatility forecasting: Do we need high-frequency data?," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1092-1110.

    Cited by:

    1. Fantazzini, Dean, 2024. "Adaptive Conformal Inference for computing Market Risk Measures: an Analysis with Four Thousands Crypto-Assets," MPRA Paper 121214, University Library of Munich, Germany.
    2. Hasanov, Akram Shavkatovich & Burkhanov, Aktam Usmanovich & Usmonov, Bunyod & Khajimuratov, Nizomjon Shukurullaevich & Khurramova, Madina Mansur qizi, 2024. "The role of sudden variance shifts in predicting volatility in bioenergy crop markets under structural breaks," Energy, Elsevier, vol. 293(C).
    3. Zhu, Haibin & Bai, Lu & He, Lidan & Liu, Zhi, 2023. "Forecasting realized volatility with machine learning: Panel data perspective," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 251-271.
    4. 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.
    5. Fantazzini, Dean, 2023. "Assessing the Credit Risk of Crypto-Assets Using Daily Range Volatility Models," MPRA Paper 117141, University Library of Munich, Germany.
    6. Yan, Xiang & Bai, Jiancheng & Li, Xiafei & Chen, Zhonglu, 2022. "Can dimensional reduction technology make better use of the information of uncertainty indices when predicting volatility of Chinese crude oil futures?," Resources Policy, Elsevier, vol. 75(C).
    7. Haukvik, Nicole & Cheraghali, Hamid & Molnár, Peter, 2024. "The role of investors’ fear in crude oil volatility forecasting," Research in International Business and Finance, Elsevier, vol. 70(PB).
    8. Bauwens, Luc & Xu, Yongdeng, 2023. "The contribution of realized covariance models to the economic value of volatility timing," LIDAM Discussion Papers CORE 2023018, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    9. Hassanniakalager, Arman & Baker, Paul L. & Platanakis, Emmanouil, 2024. "A False Discovery Rate approach to optimal volatility forecasting model selection," International Journal of Forecasting, Elsevier, vol. 40(3), pages 881-902.
    10. Fiszeder, Piotr & Fałdziński, Marcin & Molnár, Peter, 2023. "Modeling and forecasting dynamic conditional correlations with opening, high, low, and closing prices," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 308-321.
    11. 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.
    12. Li, Zhao-Chen & Xie, Chi & Zeng, Zhi-Jian & Wang, Gang-Jin & Zhang, Ting, 2023. "Forecasting global stock market volatilities in an uncertain world," International Review of Financial Analysis, Elsevier, vol. 85(C).
    13. Guo, Yangli & Li, Pan & Wu, Hanlin, 2023. "Jumps in the Chinese crude oil futures volatility forecasting: New evidence," Energy Economics, Elsevier, vol. 126(C).
    14. Zhang, Qun & Zhang, Zhendong & Luo, Jiawen, 2024. "Asymmetric and high-order risk transmission across VIX and Chinese futures markets," International Review of Financial Analysis, Elsevier, vol. 93(C).

  14. Lyócsa, Štefan & Todorova, Neda, 2021. "What drives volatility of the U.S. oil and gas firms?," Energy Economics, Elsevier, vol. 100(C).

    Cited by:

    1. Zhu, Bo & Deng, Yuanyue & Lin, Renda & Hu, Xin & Chen, Pingshe, 2022. "Energy security: Does systemic risk spillover matter? Evidence from China," Energy Economics, Elsevier, vol. 114(C).
    2. Düsterhöft, Maximilian & Schiemann, Frank & Walther, Thomas, 2023. "Let’s talk about risk! Stock market effects of risk disclosure for European energy utilities," Energy Economics, Elsevier, vol. 125(C).
    3. Ali, Muhammad Kashif & Zahoor, Muhammad Khurram & Saeed, Asif & Nosheen, Safia & Thanakijsombat, Thanarerk, 2023. "Institutional and country level determinants of vertical integration: New evidence from the oil and gas industry," Resources Policy, Elsevier, vol. 84(C).

  15. Do, Linh Phuong Catherine & Lyócsa, Štefan & Molnár, Peter, 2021. "Residual electricity demand: An empirical investigation," Applied Energy, Elsevier, vol. 283(C).

    Cited by:

    1. Maria Juliana Suarrez Foréro & Frédéric Lantz & Pierre Nicolas & Patrice Geoffron, 2022. "The Impact of Electric Vehicle Fleets on the European Electricity Markets: Evidences from the German Passenger Car Fleet and Power Generation Sector," Working Papers hal-03898558, HAL.
    2. Gallego, Camilo A., 2022. "Intertemporal effects of imperfect competition through forward contracts in wholesale electricity markets," Energy Economics, Elsevier, vol. 107(C).
    3. Chen, Qi & Kuang, Zhonghong & Liu, Xiaohua & Zhang, Tao, 2022. "Energy storage to solve the diurnal, weekly, and seasonal mismatch and achieve zero-carbon electricity consumption in buildings," Applied Energy, Elsevier, vol. 312(C).
    4. Khawaja Haider Ali & Mohammad Abusara & Asif Ali Tahir & Saptarshi Das, 2023. "Dual-Layer Q-Learning Strategy for Energy Management of Battery Storage in Grid-Connected Microgrids," Energies, MDPI, vol. 16(3), pages 1-17, January.
    5. Maria Juliana Suarrez Foréro & Frédéric Lantz & Pierre Nicolas & Pierre Geoffron, 2022. "The impact of Electric Vehicle fleets on the European Electricity Markets : Evidences from the German Passenger Car Fleet and Power Generation Sector," Working Papers hal-03609361, HAL.

  16. Deev, Oleg & Lyócsa, Štefan, 2020. "Connectedness of financial institutions in Europe: A network approach across quantiles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 550(C).

    Cited by:

    1. Yongli Li & Tianchen Wang & Baiqing Sun & Chao Liu, 2022. "Detecting the lead–lag effect in stock markets: definition, patterns, and investment strategies," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-36, December.
    2. Yizhuo Zhang & Rui Chen & Ding Ma, 2020. "A Weighted and Directed Perspective of Global Stock Market Connectedness: A Variance Decomposition and GERGM Framework," Sustainability, MDPI, vol. 12(11), pages 1-23, June.
    3. Yao, Dongmin & Sun, Rong & Gao, Qiunan, 2022. "The network structure of the China bond market: Characteristics and explanations from trading factors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 598(C).
    4. Giovanni Carnazza & Pierluigi Vellucci, 2022. "Network analysis and Eurozone trade imbalances," Papers 2209.09837, arXiv.org.
    5. Deev, Oleg & Lyócsa, Štefan & Výrost, Tomáš, 2022. "The looming crisis in the Chinese stock market? Left-tail exposure analysis of Chinese stocks to Evergrande," Finance Research Letters, Elsevier, vol. 49(C).
    6. Niu, Xiaojian & Niu, Xiaoli & Wu, Kexing, 2021. "Implicit government guarantees and the externality of portfolio diversification: A complex network approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 572(C).
    7. Zhang, Yan & Xu, Yushi & Zhu, Xintong & Huang, Jionghao, 2024. "Coal price shock propagation through sectoral financial interconnectedness in China's stock market: Quantile coherency network modelling and shock decomposition analysis," Journal of Commodity Markets, Elsevier, vol. 34(C).
    8. Torri, Gabriele & Giacometti, Rosella & Tichý, Tomáš, 2021. "Network tail risk estimation in the European banking system," Journal of Economic Dynamics and Control, Elsevier, vol. 127(C).
    9. Pang, Raymond Ka-Kay & Granados, Oscar M. & Chhajer, Harsh & Legara, Erika Fille T., 2021. "An analysis of network filtering methods to sovereign bond yields during COVID-19," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).
    10. Qian, Biyu & Wang, Gang-Jin & Feng, Yusen & Xie, Chi, 2022. "Partial cross-quantilogram networks: Measuring quantile connectedness of financial institutions," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
    11. Huang, Jionghao & Li, Ziruo & Xia, Xiaohua, 2021. "Network diffusion of international oil volatility risk in China's stock market: Quantile interconnectedness modelling and shock decomposition analysis," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 1-39.
    12. 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.
    13. Chen, Yan & Wang, Gang-Jin & Zhu, You & Xie, Chi & Uddin, Gazi Salah, 2023. "Quantile connectedness and the determinants between FinTech and traditional financial institutions: Evidence from China," Global Finance Journal, Elsevier, vol. 58(C).
    14. Zhang, Yi & Zhou, Long & Chen, Yajiao & Liu, Fang, 2022. "The contagion effect of jump risk across Asian stock markets during the Covid-19 pandemic," The North American Journal of Economics and Finance, Elsevier, vol. 61(C).
    15. Wang, Gang-Jin & Chen, Yan & Zhu, You & Xie, Chi, 2024. "Systemic risk prediction using machine learning: Does network connectedness help prediction?," International Review of Financial Analysis, Elsevier, vol. 93(C).
    16. Jareño, Francisco & González, María de la O & Escolástico, Alba M., 2020. "Extension of the Fama and French model: A study of the largest European financial institutions," International Economics, Elsevier, vol. 164(C), pages 115-139.

  17. Štefan Lyócsa & Petra Vašaničová & Eva Litavcová, 2020. "Quantile dependence of tourism activity between Southern European countries," Applied Economics Letters, Taylor & Francis Journals, vol. 27(3), pages 206-212, February.

    Cited by:

    1. Giovanni De Luca & Monica Rosciano, 2020. "Quantile Dependence in Tourism Demand Time Series: Evidence in the Southern Italy Market," Sustainability, MDPI, vol. 12(8), pages 1-18, April.

  18. Lyócsa, Štefan & Todorova, Neda, 2020. "Trading and non-trading period realized market volatility: Does it matter for forecasting the volatility of US stocks?," International Journal of Forecasting, Elsevier, vol. 36(2), pages 628-645.

    Cited by:

    1. Feng Ma & M. I. M. Wahab & Julien Chevallier & Ziyang Li, 2023. "A tug of war of forecasting the US stock market volatility: Oil futures overnight versus intraday information," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(1), pages 60-75, January.
    2. Klein, Tony & Todorova, Neda, 2021. "Night trading with futures in China: The case of Aluminum and Copper," Resources Policy, Elsevier, vol. 73(C).
    3. Zhang, Li & Li, Yan & Yu, Sixin & Wang, Lu, 2023. "Risk transmission of El Niño-induced climate change to regional Green Economy Index," Economic Analysis and Policy, Elsevier, vol. 79(C), pages 860-872.
    4. Tianyi Wang & Sicong Cheng & Fangsheng Yin & Mei Yu, 2022. "Overnight volatility, realized volatility, and option pricing," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(7), pages 1264-1283, July.
    5. Lyócsa, Štefan & Plíhal, Tomáš & Výrost, Tomáš, 2021. "FX market volatility modelling: Can we use low-frequency data?," Finance Research Letters, Elsevier, vol. 40(C).
    6. Li, Chenxing & Zhang, Zehua & Zhao, Ran, 2024. "Volatility or higher moments: Which is more important in return density forecasts of stochastic volatility model?," Finance Research Letters, Elsevier, vol. 67(PB).
    7. Yu, Jize & Zhang, Li & Peng, Lijuan & Wu, Rui, 2023. "Which component of air quality index drives stock price volatility in China: a decomposition-based forecasting method," Finance Research Letters, Elsevier, vol. 51(C).
    8. Mayukh Dass & Masoud Moradi & Fereshteh Zihagh, 2023. "Forecasting purchase rates of new products introduced in existing categories," Journal of Marketing Analytics, Palgrave Macmillan, vol. 11(3), pages 385-408, September.
    9. Lyócsa, Štefan & Halousková, Martina & Haugom, Erik, 2023. "The US banking crisis in 2023: Intraday attention and price variation of banks at risk," Finance Research Letters, Elsevier, vol. 57(C).
    10. Jayawardena, Nirodha I. & Todorova, Neda & Li, Bin & Su, Jen-Je, 2020. "Volatility forecasting using related markets’ information for the Tokyo stock exchange," Economic Modelling, Elsevier, vol. 90(C), pages 143-158.
    11. Lyócsa, Štefan & Molnár, Peter & Výrost, Tomáš, 2021. "Stock market volatility forecasting: Do we need high-frequency data?," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1092-1110.

  19. Lyócsa, Štefan & Molnár, Peter, 2020. "Stock market oscillations during the corona crash: The role of fear and uncertainty," Finance Research Letters, Elsevier, vol. 36(C).

    Cited by:

    1. Narayan, Paresh Kumar & Phan, Dinh Hoang Bach & Liu, Guangqiang, 2021. "COVID-19 lockdowns, stimulus packages, travel bans, and stock returns," Finance Research Letters, Elsevier, vol. 38(C).
    2. Dong, Yunhe & Luo, Haoyi & Xu, Zijin & Yang, Xing, 2024. "Cash, crisis, and capers: The UK's cashbox policy during COVID-19," Economics Letters, Elsevier, vol. 240(C).
    3. Foglia, Matteo & Addi, Abdelhamid & Angelini, Eliana, 2022. "The Eurozone banking sector in the time of COVID-19: Measuring volatility connectedness," Global Finance Journal, Elsevier, vol. 51(C).
    4. Hanif, Waqas & Mensi, Walid & Vo, Xuan Vinh, 2021. "Impacts of COVID-19 outbreak on the spillovers between US and Chinese stock sectors," Finance Research Letters, Elsevier, vol. 40(C).
    5. Huynh, Toan Luu Duc & Foglia, Matteo & Doukas, John A., 2022. "COVID-19 and Tail-event Driven Network Risk in the Eurozone," Finance Research Letters, Elsevier, vol. 44(C).
    6. Nepp, Alexander & Okhrin, Ostap & Egorova, Julia & Dzhuraeva, Zarnigor & Zykov, Alexander, 2022. "What threatens stock markets more - The coronavirus or the hype around it?," International Review of Economics & Finance, Elsevier, vol. 78(C), pages 519-539.
    7. Huynh, Toan Luu Duc & Foglia, Matteo & Nasir, Muhammad Ali & Angelini, Eliana, 2021. "Feverish sentiment and global equity markets during the COVID-19 pandemic," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 1088-1108.
    8. Evangelos Vasileiou, 2021. "Explaining stock markets' performance during the COVID‐19 crisis: Could Google searches be a significant behavioral indicator?," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 28(3), pages 173-181, July.
    9. 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).
    10. Huang, Yuxuan & Yang, Shenggang & Zhu, Qi, 2021. "Brand equity and the Covid-19 stock market crash: Evidence from U.S. listed firms," Finance Research Letters, Elsevier, vol. 43(C).
    11. Calabrò, Andrea & Frank, Hermann & Minichilli, Alessandro & Suess-Reyes, Julia, 2021. "Business families in times of crises: The backbone of family firm resilience and continuity," Journal of Family Business Strategy, Elsevier, vol. 12(2).
    12. Julien Chevallier, 2020. "COVID-19 Outbreak and CO 2 Emissions: Macro-Financial Linkages," JRFM, MDPI, vol. 14(1), pages 1-18, December.
    13. Xin Li, 2021. "Asymmetric Impact of COVID-19 on China's Stock Market Volatility - Media Effect or Fact?," Asian Economics Letters, Asia-Pacific Applied Economics Association, vol. 2(4), pages 1-6.
    14. Refai, Hisham Al & Zeitun, Rami & Eissa, Mohamed Abdel-Aziz, 2022. "Impact of global health crisis and oil price shocks on stock markets in the GCC," Finance Research Letters, Elsevier, vol. 45(C).
    15. Lyócsa, Štefan & Baumöhl, Eduard & Výrost, Tomáš, 2022. "YOLO trading: Riding with the herd during the GameStop episode," Finance Research Letters, Elsevier, vol. 46(PA).
    16. Lyócsa, Štefan & Halousková, Martina & Haugom, Erik, 2023. "The US banking crisis in 2023: Intraday attention and price variation of banks at risk," Finance Research Letters, Elsevier, vol. 57(C).
    17. Bilal & Adeel Nasir & Umar Farooq & Muhammad Farhan Bashir, 2024. "Stock returns, government response strategies, and daily new case bursts during COVID‐19: A cross‐country perspective," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(1), pages 465-485, January.
    18. Díaz, Fernando & Henríquez, Pablo A. & Winkelried, Diego, 2022. "Stock market volatility and the COVID-19 reproductive number," Research in International Business and Finance, Elsevier, vol. 59(C).
    19. Anna Gloria Billé & Massimiliano Caporin, 2022. "Impact of COVID-19 on financial returns: a spatial dynamic panel data model with random effects," Journal of Spatial Econometrics, Springer, vol. 3(1), pages 1-21, December.

  20. Lyócsa, Štefan & Molnár, Peter & Plíhal, Tomáš & Širaňová, Mária, 2020. "Impact of macroeconomic news, regulation and hacking exchange markets on the volatility of bitcoin," Journal of Economic Dynamics and Control, Elsevier, vol. 119(C).

    Cited by:

    1. Wang, Jying-Nan & Vigne, Samuel A. & Liu, Hung-Chun & Hsu, Yuan-Teng, 2024. "Hacks and the price synchronicity of bitcoin and ether," The Quarterly Review of Economics and Finance, Elsevier, vol. 95(C), pages 294-299.
    2. Goodell, John W. & Gurdgiev, Constantin & Paltrinieri, Andrea & Piserà, Stefano, 2023. "Global energy supply risk: Evidence from the reactions of European natural gas futures to Nord Stream announcements," Energy Economics, Elsevier, vol. 125(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. Bergsli, Lykke Øverland & Lind, Andrea Falk & Molnár, Peter & Polasik, Michał, 2022. "Forecasting volatility of Bitcoin," Research in International Business and Finance, Elsevier, vol. 59(C).
    5. Bucci, Andrea & Palomba, Giulio & Rossi, Eduardo, 2023. "The role of uncertainty in forecasting volatility comovements across stock markets," Economic Modelling, Elsevier, vol. 125(C).
    6. Chen, Yu-Lun & Chang, Yung Ting & Yang, J. Jimmy, 2023. "Cryptocurrency hacking incidents and the price dynamics of Bitcoin spot and futures," Finance Research Letters, Elsevier, vol. 55(PB).
    7. Auer, Raphael & Farag, Marc & Lewrick, Ulf & Orazem, Lovrenc & Zoss, Markus, 2023. "Banking in the shadow of Bitcoin? The institutional adoption of cryptocurrencies," CEPR Discussion Papers 18331, C.E.P.R. Discussion Papers.
    8. Carbó, José Manuel & Gorjón, Sergio, 2024. "Determinants of the price of bitcoin: An analysis with machine learning and interpretability techniques," International Review of Economics & Finance, Elsevier, vol. 92(C), pages 123-140.
    9. Li, Leon & Miu, Peter, 2023. "Are cryptocurrencies a safe haven for stock investors? A regime-switching approach," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 367-385.
    10. Caferra, Rocco & Vidal-Tomás, David, 2021. "Who raised from the abyss? A comparison between cryptocurrency and stock market dynamics during the COVID-19 pandemic," Finance Research Letters, Elsevier, vol. 43(C).
    11. Zhang, Chuanhai & Ma, Huan & Liao, Xiaosai, 2023. "Futures trading activity and the jump risk of spot market: Evidence from the bitcoin market," Pacific-Basin Finance Journal, Elsevier, vol. 78(C).
    12. Conlon, Thomas & Corbet, Shaen & Hou, Yang (Greg) & Hu, Yang & Oxley, Les, 2024. "Bitcoin forks: What drives the branches?," Research in International Business and Finance, Elsevier, vol. 69(C).
    13. Nezir Köse & Hakan Yildirim & Emre Ünal & Boqiang Lin, 2024. "The Bitcoin price and Bitcoin price uncertainty: Evidence of Bitcoin price volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(4), pages 673-695, April.
    14. Simona-Vasilica Oprea & Irina Alexandra Georgescu & Adela Bâra, 2024. "Is Bitcoin ready to be a widespread payment method? Using price volatility and setting strategies for merchants," Electronic Commerce Research, Springer, vol. 24(2), pages 1267-1305, June.
    15. Kyriazis, Nikolaos & Papadamou, Stephanos & Tzeremes, Panayiotis & Corbet, Shaen, 2023. "Can cryptocurrencies provide a viable hedging mechanism for benchmark index investors?," Research in International Business and Finance, Elsevier, vol. 64(C).
    16. Zhang, Zehua & Zhao, Ran, 2023. "Good volatility, bad volatility, and the cross section of cryptocurrency returns," International Review of Financial Analysis, Elsevier, vol. 89(C).
    17. Kawakami, Tabito, 2023. "Quantile prediction for Bitcoin returns using financial assets’ realized measures," Finance Research Letters, Elsevier, vol. 55(PA).
    18. Sofiane Aboura, 2022. "A note on the Bitcoin and Fed Funds rate," Empirical Economics, Springer, vol. 63(5), pages 2577-2603, November.
    19. Milunovich, George & Lee, Seung Ah, 2022. "Measuring the impact of digital exchange cyberattacks on Bitcoin Returns," Economics Letters, Elsevier, vol. 221(C).
    20. Goodell, John W. & Alon, Ilan & Chiaramonte, Laura & Dreassi, Alberto & Paltrinieri, Andrea & Piserà, Stefano, 2023. "Risk substitution in cryptocurrencies: Evidence from BRICS announcements," Emerging Markets Review, Elsevier, vol. 54(C).
    21. Kao, Yu-Sheng & Day, Min-Yuh & Chou, Ke-Hsin, 2024. "A comparison of bitcoin futures return and return volatility based on news sentiment contemporaneously or lead-lag," The North American Journal of Economics and Finance, Elsevier, vol. 72(C).
    22. Nguyen, Thach V.H. & Nguyen, Thai Vu Hong & Nguyen, Thanh Cong & Pham, Thu Thi Anh & Nguyen, Quan M.P., 2022. "Stablecoins versus traditional cryptocurrencies in response to interbank rates," Finance Research Letters, Elsevier, vol. 47(PB).
    23. Li, Zheng & Zhou, Bo & Hensher, David A., 2022. "Forecasting automobile gasoline demand in Australia using machine learning-based regression," Energy, Elsevier, vol. 239(PD).
    24. Zhang, Pengcheng & Xu, Kunpeng & Qi, Jiayin, 2023. "The impact of regulation on cryptocurrency market volatility in the context of the COVID-19 pandemic — evidence from China," Economic Analysis and Policy, Elsevier, vol. 80(C), pages 222-246.
    25. Griffith, Todd & Clancey-Shang, Danjue, 2023. "Cryptocurrency regulation and market quality," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 84(C).
    26. Halousková, Martina & Stašek, Daniel & Horváth, Matúš, 2022. "The role of investor attention in global asset price variation during the invasion of Ukraine," Finance Research Letters, Elsevier, vol. 50(C).
    27. Zhang, Chuanhai & Zhang, Zhengjun & Xu, Mengyu & Peng, Zhe, 2023. "Good and bad self-excitation: Asymmetric self-exciting jumps in Bitcoin returns," Economic Modelling, Elsevier, vol. 119(C).
    28. 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.
    29. Pattnaik, Debidutta & Hassan, M. Kabir & Dsouza, Arun & Tiwari, Aviral & Devji, Shridev, 2023. "Ex-post facto analysis of cryptocurrency literature over a decade using bibliometric technique," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    30. Mercik, Aleksander & Słoński, Tomasz & Karaś, Marta, 2024. "Understanding crypto-asset exposure: An investigation of its impact on performance and stock sensitivity among listed companies," International Review of Financial Analysis, Elsevier, vol. 92(C).
    31. Arun Narayanasamy & Humnath Panta & Rohit Agarwal, 2023. "Relations among Bitcoin Futures, Bitcoin Spot, Investor Attention, and Sentiment," JRFM, MDPI, vol. 16(11), pages 1-24, November.
    32. Lyócsa, Štefan & Plíhal, Tomáš, 2022. "Russia’s ruble during the onset of the Russian invasion of Ukraine in early 2022: The role of implied volatility and attention," Finance Research Letters, Elsevier, vol. 48(C).
    33. Ftiti, Zied & Ben Ameur, Hachmi & Louhichi, Waël, 2021. "Does non-fundamental news related to COVID-19 matter for stock returns? Evidence from Shanghai stock market," Economic Modelling, Elsevier, vol. 99(C).
    34. Ao Shu & Feiyang Cheng & Jianlei Han & Zini Liang & Zheyao Pan, 2023. "Arbitrage across different Bitcoin exchange venues: Perspectives from investor base and market related events," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(5), pages 5183-5210, December.
    35. Lyócsa, Štefan & Halousková, Martina & Haugom, Erik, 2023. "The US banking crisis in 2023: Intraday attention and price variation of banks at risk," Finance Research Letters, Elsevier, vol. 57(C).
    36. Yaojie Zhang & Yudong Wang & Feng Ma & Yu Wei, 2022. "To jump or not to jump: momentum of jumps in crude oil price volatility prediction," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-31, December.
    37. Panayotis G. Papaioannou & George P. Papaioannou & George Evangelidis & George Gavalakis, 2024. "Detecting Structural breakpoints in natural gas and electricity wholesale prices via Bayesian ensemble approach, in the era of energy prices turmoil of 2022 period: the cases of ten European markets," Papers 2410.07224, arXiv.org.
    38. Ahmed, Walid M.A., 2024. "Attention to climate change and eco-friendly financial-asset prices: A quantile ARDL approach," Energy Economics, Elsevier, vol. 136(C).
    39. Scharnowski, Stefan, 2022. "Central bank speeches and digital currency competition," Finance Research Letters, Elsevier, vol. 49(C).
    40. Dias, Ishanka K. & Fernando, J.M. Ruwani & Fernando, P. Narada D., 2022. "Does investor sentiment predict bitcoin return and volatility? A quantile regression approach," International Review of Financial Analysis, Elsevier, vol. 84(C).
    41. Ivanovski, Kris & Hailemariam, Abebe, 2023. "Forecasting the stock-cryptocurrency relationship: Evidence from a dynamic GAS model," International Review of Economics & Finance, Elsevier, vol. 86(C), pages 97-111.
    42. Kumar Kulbhaskar, Anamika & Subramaniam, Sowmya, 2023. "Breaking news headlines: Impact on trading activity in the cryptocurrency market," Economic Modelling, Elsevier, vol. 126(C).
    43. Ştefan Cristian Gherghina & Liliana Nicoleta Simionescu, 2023. "Exploring the asymmetric effect of COVID-19 pandemic news on the cryptocurrency market: evidence from nonlinear autoregressive distributed lag approach and frequency domain causality," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-58, December.

  21. Lyócsa, Štefan & Baumöhl, Eduard & Výrost, Tomáš & Molnár, Peter, 2020. "Fear of the coronavirus and the stock markets," Finance Research Letters, Elsevier, vol. 36(C).
    See citations under working paper version above.
  22. 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.
    See citations under working paper version above.
  23. Linh Phuong Catherine Do & Štefan Lyócsa & Peter Molnár, 2019. "Impact of wind and solar production on electricity prices: Quantile regression approach," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 70(10), pages 1752-1768, October.

    Cited by:

    1. Ajanaku, Bolarinwa A. & Collins, Alan R., 2024. "“Comparing merit order effects of wind penetration across wholesale electricity markets”," Renewable Energy, Elsevier, vol. 226(C).
    2. Do, Linh Phuong Catherine & Lyócsa, Štefan & Molnár, Peter, 2021. "Residual electricity demand: An empirical investigation," Applied Energy, Elsevier, vol. 283(C).
    3. John Dorrell & Keunjae Lee, 2021. "The Price of Wind: An Empirical Analysis of the Relationship between Wind Energy and Electricity Price across the Residential, Commercial, and Industrial Sectors," Energies, MDPI, vol. 14(12), pages 1-21, June.
    4. Sirin, Selahattin Murat & Yilmaz, Berna N., 2020. "Variable renewable energy technologies in the Turkish electricity market: Quantile regression analysis of the merit-order effect," Energy Policy, Elsevier, vol. 144(C).
    5. Erik Haugom & Peter Molnár & Magne Tysdahl, 2020. "Determinants of the Forward Premium in the Nord Pool Electricity Market," Energies, MDPI, vol. 13(5), pages 1-18, March.
    6. Gökgöz, Fazıl & Yücel, Öykü, 2024. "Merit-order of dispatchable and variable renewable energy sources in Turkey's day-ahead electricity market," Utilities Policy, Elsevier, vol. 88(C).

  24. Horpestad, Jone B. & Lyócsa, Štefan & Molnár, Peter & Olsen, Torbjørn B., 2019. "Asymmetric volatility in equity markets around the world," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 540-554.

    Cited by:

    1. Maki, Daiki & Ota, Yasushi, 2021. "Impacts of asymmetry on forecasting realized volatility in Japanese stock markets," Economic Modelling, Elsevier, vol. 101(C).
    2. Lyócsa, Štefan & Plíhal, Tomáš & Výrost, Tomáš, 2021. "FX market volatility modelling: Can we use low-frequency data?," Finance Research Letters, Elsevier, vol. 40(C).
    3. Duan, Huayou & Zhao, Chenchen & Wang, Lu & Liu, Guangqiang, 2024. "The relationship between renewable energy attention and volatility: A HAR model with markov time-varying transition probability," Research in International Business and Finance, Elsevier, vol. 71(C).
    4. Maurice Omane‐Adjepong & Imhotep Paul Alagidede, 2021. "Modelling Asymmetry and Leverage in Cryptocurrencies and Emerging Financial Markets," Economic Papers, The Economic Society of Australia, vol. 40(2), pages 152-166, June.
    5. Fałdziński, Marcin & Fiszeder, Piotr & Molnár, Peter, 2024. "Improving volatility forecasts: Evidence from range-based models," The North American Journal of Economics and Finance, Elsevier, vol. 69(PB).
    6. Jiawen Luo & Oguzhan Cepni & Riza Demirer & Rangan Gupta, 2022. "Forecasting Multivariate Volatilities with Exogenous Predictors: An Application to Industry Diversification Strategies," Working Papers 202258, University of Pretoria, Department of Economics.
    7. Borjigin, Sumuya & Gao, Ting & Sun, Yafei & An, Biao, 2020. "For evil news rides fast, while good news baits later?—A network based analysis in Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 551(C).
    8. Mensi, Walid & Sensoy, Ahmet & Aslan, Aylin & Kang, Sang Hoon, 2019. "High-frequency asymmetric volatility connectedness between Bitcoin and major precious metals markets," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    9. Lyócsa, Štefan & Todorova, Neda & Výrost, Tomáš, 2021. "Predicting risk in energy markets: Low-frequency data still matter," Applied Energy, Elsevier, vol. 282(PA).
    10. Maki, Daiki, 2024. "Forecasting downside and upside realized volatility: The role of asymmetric information," The Journal of Economic Asymmetries, Elsevier, vol. 29(C).
    11. Xiao, Jihong & Wen, Fenghua & Zhao, Yupei & Wang, Xiong, 2021. "The role of US implied volatility index in forecasting Chinese stock market volatility: Evidence from HAR models," International Review of Economics & Finance, Elsevier, vol. 74(C), pages 311-333.
    12. Lyócsa, Štefan & Todorova, Neda, 2024. "Forecasting of clean energy market volatility: The role of oil and the technology sector," Energy Economics, Elsevier, vol. 132(C).
    13. Lyócsa, Štefan & Molnár, Peter & Výrost, Tomáš, 2021. "Stock market volatility forecasting: Do we need high-frequency data?," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1092-1110.
    14. Xie, Qiwei & Liu, Ranran & Qian, Tao & Li, Jingyu, 2021. "Linkages between the international crude oil market and the Chinese stock market: A BEKK-GARCH-AFD approach," Energy Economics, Elsevier, vol. 102(C).
    15. Papathanasiou, Spyros & Koutsokostas, Drosos & Pergeris, Georgios, 2022. "Novel alternative assets within a transmission mechanism of volatility spillovers: The role of SPACs," Finance Research Letters, Elsevier, vol. 47(PA).
    16. Mensi, Walid & Nekhili, Ramzi & Vo, Xuan Vinh & Suleman, Tahir & Kang, Sang Hoon, 2021. "Asymmetric volatility connectedness among U.S. stock sectors," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    17. Daiki Maki & Yasushi Ota, 2020. "The impacts of asymmetry on modeling and forecasting realized volatility in Japanese stock markets," Papers 2006.00158, arXiv.org.
    18. Plíhal, Tomáš & Lyócsa, Štefan, 2021. "Modeling realized volatility of the EUR/USD exchange rate: Does implied volatility really matter?," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 811-829.

  25. Lyócsa, Štefan & Výrost, Tomáš & Baumöhl, Eduard, 2019. "Return spillovers around the globe: A network approach," Economic Modelling, Elsevier, vol. 77(C), pages 133-146.
    See citations under working paper version above.
  26. Lyócsa, Štefan & Molnár, Peter & Plíhal, Tomáš, 2019. "Central bank announcements and realized volatility of stock markets in G7 countries," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 58(C), pages 117-135.

    Cited by:

    1. Lyócsa, Štefan & Todorova, Neda, 2024. "Forecasting of clean energy market volatility: The role of oil and the technology sector," Energy Economics, Elsevier, vol. 132(C).

  27. 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.
    See citations under working paper version above.
  28. Roman Horváth & Štefan Lyócsa & Eduard Baumöhl, 2018. "Stock market contagion in Central and Eastern Europe: unexpected volatility and extreme co-exceedance," The European Journal of Finance, Taylor & Francis Journals, vol. 24(5), pages 391-412, March.
    See citations under working paper version above.
  29. Štefan Lyócsa & Tomáš Výrost, 2018. "To bet or not to bet: a reality check for tennis betting market efficiency," Applied Economics, Taylor & Francis Journals, vol. 50(20), pages 2251-2272, April.

    Cited by:

    1. He, Xue-Zhong & Treich, Nicolas, 2017. "Prediction market prices under risk aversion and heterogeneous beliefs," Journal of Mathematical Economics, Elsevier, vol. 70(C), pages 105-114.
    2. Ramirez, Philip & Reade, J. James & Singleton, Carl, 2023. "Betting on a buzz: Mispricing and inefficiency in online sportsbooks," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1413-1423.

  30. Štefan Lyócsa & Roman Horváth, 2018. "Stock Market Contagion: a New Approach," Open Economies Review, Springer, vol. 29(3), pages 547-577, July.

    Cited by:

    1. Erniel B. Barrios & Paolo Victor T. Redondo, 2021. "Nonparametric Test for Volatility in Clustered Multiple Time Series," Papers 2104.14412, arXiv.org, revised May 2024.
    2. Gil-Alana, Luis A. & Infante, Juan & Martín-Valmayor, Miguel Angel, 2023. "Persistence and long run co-movements across stock market prices," The Quarterly Review of Economics and Finance, Elsevier, vol. 89(C), pages 347-357.
    3. Hendriks, Johannes Jurgens & Bonga-Bonga, Lumengo, 2020. "Sectoral dependence and contagion in the BRICS grouping: an application of the R-Vine copulas," MPRA Paper 102473, University Library of Munich, Germany.

  31. Lyócsa, Štefan & Výrost, Tomáš, 2018. "Scale-free distribution of firm-size distribution in emerging economies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 501-505.

    Cited by:

    1. Musa, Hussam & Krištofík, Peter & Medzihorský, Juraj & Klieštik, Tomáš, 2024. "The development of firm size distribution – Evidence from four Central European countries," International Review of Economics & Finance, Elsevier, vol. 91(C), pages 98-110.
    2. Faustino Prieto & José María Sarabia & Enrique Calderín-Ojeda, 2021. "The nonlinear distribution of employment across municipalities," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 16(2), pages 287-307, April.
    3. Michal Brzozowski, 2019. "Access to Credit and Growth of Firms," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 69(3), pages 253-274, June.

  32. 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.

    Cited by:

    1. Hasanov, Akram Shavkatovich & Burkhanov, Aktam Usmanovich & Usmonov, Bunyod & Khajimuratov, Nizomjon Shukurullaevich & Khurramova, Madina Mansur qizi, 2024. "The role of sudden variance shifts in predicting volatility in bioenergy crop markets under structural breaks," Energy, Elsevier, vol. 293(C).
    2. Wu, Bi-Bo, 2021. "The dynamics of oil on China’s commodity sectors: What can we learn from a quantile perspective?," Journal of Commodity Markets, Elsevier, vol. 23(C).
    3. 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).
    4. Liang, Chao & Xia, Zhenglan & Lai, Xiaodong & Wang, Lu, 2022. "Natural gas volatility prediction: Fresh evidence from extreme weather and extended GARCH-MIDAS-ES model," Energy Economics, Elsevier, vol. 116(C).
    5. Horpestad, Jone B. & Lyócsa, Štefan & Molnár, Peter & Olsen, Torbjørn B., 2019. "Asymmetric volatility in equity markets around the world," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 540-554.
    6. Rangan Gupta & Christian Pierdzioch, 2021. "Climate Risks and the Realized Volatility Oil and Gas Prices: Results of an Out-of-Sample Forecasting Experiment," Energies, MDPI, vol. 14(23), pages 1-18, December.
    7. Alizadeh, Amir H. & Huang, Chih-Yueh & Marsh, Ian W., 2021. "Modelling the volatility of TOCOM energy futures: A regime switching realised volatility approach," Energy Economics, Elsevier, vol. 93(C).
    8. Lyócsa, Štefan & Molnár, Peter & Plíhal, Tomáš & Širaňová, Mária, 2020. "Impact of macroeconomic news, regulation and hacking exchange markets on the volatility of bitcoin," Journal of Economic Dynamics and Control, Elsevier, vol. 119(C).
    9. Liu, Yuanyuan & Niu, Zibo & Suleman, Muhammad Tahir & Yin, Libo & Zhang, Hongwei, 2022. "Forecasting the volatility of crude oil futures: The role of oil investor attention and its regime switching characteristics under a high-frequency framework," Energy, Elsevier, vol. 238(PA).
    10. Haukvik, Nicole & Cheraghali, Hamid & Molnár, Peter, 2024. "The role of investors’ fear in crude oil volatility forecasting," Research in International Business and Finance, Elsevier, vol. 70(PB).
    11. Amaro, Raphael & Pinho, Carlos & Madaleno, Mara, 2022. "Forecasting the Value-at-Risk of energy commodities: A comparison of models and alternative distribution functions," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 65, pages 77-101.
    12. Lyócsa, Štefan & Todorova, Neda, 2020. "Trading and non-trading period realized market volatility: Does it matter for forecasting the volatility of US stocks?," International Journal of Forecasting, Elsevier, vol. 36(2), pages 628-645.
    13. Luo, Jiawen & Ji, Qiang & Klein, Tony & Todorova, Neda & Zhang, Dayong, 2020. "On realized volatility of crude oil futures markets: Forecasting with exogenous predictors under structural breaks," Energy Economics, Elsevier, vol. 89(C).
    14. Lyócsa, Štefan & Todorova, Neda & Výrost, Tomáš, 2021. "Predicting risk in energy markets: Low-frequency data still matter," Applied Energy, Elsevier, vol. 282(PA).
    15. Delis, Panagiotis & Degiannakis, Stavros & Giannopoulos, Kostantinos, 2021. "What should be taken into consideration when forecasting oil implied volatility index?," MPRA Paper 110831, University Library of Munich, Germany.
    16. Yaxian Lu & Longguang Yang & Lihong Liu, 2019. "Volatility Spillovers between Crude Oil and Agricultural Commodity Markets since the Financial Crisis," Sustainability, MDPI, vol. 11(2), pages 1-12, January.
    17. Lyócsa, Štefan & Todorova, Neda, 2021. "What drives volatility of the U.S. oil and gas firms?," Energy Economics, Elsevier, vol. 100(C).
    18. Zargar, Faisal Nazir & Kumar, Dilip, 2020. "Heterogeneous market hypothesis approach for modeling unbiased extreme value volatility estimator in presence of leverage effect: An individual stock level study with economic significance analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 77(C), pages 271-285.
    19. Gil, Cohen, 2022. "Intraday Trading of Precious Metals Futures Using Algorithmic Systems," Chaos, Solitons & Fractals, Elsevier, vol. 154(C).
    20. Lyócsa, Štefan & Molnár, Peter & Výrost, Tomáš, 2021. "Stock market volatility forecasting: Do we need high-frequency data?," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1092-1110.

  33. Lyócsa, Štefan & Molnár, Peter & Todorova, Neda, 2017. "Volatility forecasting of non-ferrous metal futures: Covariances, covariates or combinations?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 51(C), pages 228-247.

    Cited by:

    1. Hasanov, Akram Shavkatovich & Burkhanov, Aktam Usmanovich & Usmonov, Bunyod & Khajimuratov, Nizomjon Shukurullaevich & Khurramova, Madina Mansur qizi, 2024. "The role of sudden variance shifts in predicting volatility in bioenergy crop markets under structural breaks," Energy, Elsevier, vol. 293(C).
    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. Luo, Jiawen & Klein, Tony & Ji, Qiang & Hou, Chenghan, 2022. "Forecasting realized volatility of agricultural commodity futures with infinite Hidden Markov HAR models," International Journal of Forecasting, Elsevier, vol. 38(1), pages 51-73.
    4. Horpestad, Jone B. & Lyócsa, Štefan & Molnár, Peter & Olsen, Torbjørn B., 2019. "Asymmetric volatility in equity markets around the world," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 540-554.
    5. 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.
    6. Mark F. J. Steel, 2020. "Model Averaging and Its Use in Economics," Journal of Economic Literature, American Economic Association, vol. 58(3), pages 644-719, September.
    7. Han, Xuyuan & Liu, Zhenya & Wang, Shixuan, 2022. "An R-vine copula analysis of non-ferrous metal futures with application in Value-at-Risk forecasting," Journal of Commodity Markets, Elsevier, vol. 25(C).
    8. Liu, Yanqiong & Guo, Yaoqi & Wei, Qing, 2024. "Time-varying and multi-scale analysis of copper price influencing factors based on LASSO and EMD methods," Journal of Commodity Markets, Elsevier, vol. 34(C).
    9. Luo, Jiawen & Klein, Tony & Ji, Qiang & Hou, Chenghan, 2019. "Forecasting Realized Volatility of Agricultural Commodity Futures with Infinite Hidden Markov HAR Models," QBS Working Paper Series 2019/10, Queen's University Belfast, Queen's Business School.
    10. Donghua Wang & Yang Xin & Xiaohui Chang & Xingze Su, 2021. "Realized volatility forecasting and volatility spillovers: Evidence from Chinese non‐ferrous metals futures," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2713-2731, April.
    11. Lyócsa, Štefan & Todorova, Neda & Výrost, Tomáš, 2021. "Predicting risk in energy markets: Low-frequency data still matter," Applied Energy, Elsevier, vol. 282(PA).
    12. Díaz, Juan D. & Hansen, Erwin & Cabrera, Gabriel, 2021. "Economic drivers of commodity volatility: The case of copper," Resources Policy, Elsevier, vol. 73(C).
    13. Díaz, Juan D. & Hansen, Erwin & Cabrera, Gabriel, 2020. "A random walk through the trees: Forecasting copper prices using decision learning methods," Resources Policy, Elsevier, vol. 69(C).
    14. Yaxian Lu & Longguang Yang & Lihong Liu, 2019. "Volatility Spillovers between Crude Oil and Agricultural Commodity Markets since the Financial Crisis," Sustainability, MDPI, vol. 11(2), pages 1-12, January.
    15. Lyócsa, Štefan & Todorova, Neda, 2021. "What drives volatility of the U.S. oil and gas firms?," Energy Economics, Elsevier, vol. 100(C).
    16. 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).
    17. Todorova, Neda & Clements, Adam E., 2018. "The volatility-volume relationship in the LME futures market for industrial metals," Resources Policy, Elsevier, vol. 58(C), pages 111-124.
    18. Rubaszek, Michał & Karolak, Zuzanna & Kwas, Marek, 2020. "Mean-reversion, non-linearities and the dynamics of industrial metal prices. A forecasting perspective," Resources Policy, Elsevier, vol. 65(C).
    19. Lyócsa, Štefan & Molnár, Peter & Výrost, Tomáš, 2021. "Stock market volatility forecasting: Do we need high-frequency data?," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1092-1110.
    20. Plíhal, Tomáš & Lyócsa, Štefan, 2021. "Modeling realized volatility of the EUR/USD exchange rate: Does implied volatility really matter?," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 811-829.

  34. Baumöhl, Eduard & Lyócsa, Štefan, 2017. "Directional predictability from stock market sector indices to gold: A cross-quantilogram analysis," Finance Research Letters, Elsevier, vol. 23(C), pages 152-164.
    See citations under working paper version above.
  35. Lyócsa, Štefan & Molnár, Peter, 2017. "The effect of non-trading days on volatility forecasts in equity markets," Finance Research Letters, Elsevier, vol. 23(C), pages 39-49.

    Cited by:

    1. Lyócsa, Štefan & Molnár, Peter & Todorova, Neda, 2017. "Volatility forecasting of non-ferrous metal futures: Covariances, covariates or combinations?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 51(C), pages 228-247.
    2. Horpestad, Jone B. & Lyócsa, Štefan & Molnár, Peter & Olsen, Torbjørn B., 2019. "Asymmetric volatility in equity markets around the world," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 540-554.
    3. Lyócsa, Štefan & Todorova, Neda, 2020. "Trading and non-trading period realized market volatility: Does it matter for forecasting the volatility of US stocks?," International Journal of Forecasting, Elsevier, vol. 36(2), pages 628-645.
    4. Díaz-Mendoza, Ana-Carmen & Pardo, Angel, 2020. "Holidays, weekends and range-based volatility," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    5. Jayawardena, Nirodha I. & Todorova, Neda & Li, Bin & Su, Jen-Je, 2020. "Volatility forecasting using related markets’ information for the Tokyo stock exchange," Economic Modelling, Elsevier, vol. 90(C), pages 143-158.
    6. Zargar, Faisal Nazir & Kumar, Dilip, 2020. "Heterogeneous market hypothesis approach for modeling unbiased extreme value volatility estimator in presence of leverage effect: An individual stock level study with economic significance analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 77(C), pages 271-285.

  36. Štefan Lyócsa & Igor Fedorko, 2016. "What drives intermediation costs? A case of tennis betting market," Applied Economics, Taylor & Francis Journals, vol. 48(22), pages 2037-2053, May.

    Cited by:

    1. Whelan, Karl, 2022. "Risk Aversion and Favorite-Longshot Bias in a Competitive Fixed-Odds Betting Market," CEPR Discussion Papers 17518, C.E.P.R. Discussion Papers.
    2. Carlos Gomez-Gonzalez & Julio del Corral, 2018. "The betting market over time: overround and surebets in European football," Economics and Business Letters, Oviedo University Press, vol. 7(4), pages 129-136.

  37. Štefan Lyócsa & Peter Molnár, 2016. "Volatility forecasting of strategically linked commodity ETFs: gold-silver," Quantitative Finance, Taylor & Francis Journals, vol. 16(12), pages 1809-1822, December.

    Cited by:

    1. Lyócsa, Štefan & Molnár, Peter & Todorova, Neda, 2017. "Volatility forecasting of non-ferrous metal futures: Covariances, covariates or combinations?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 51(C), pages 228-247.
    2. Bergsli, Lykke Øverland & Lind, Andrea Falk & Molnár, Peter & Polasik, Michał, 2022. "Forecasting volatility of Bitcoin," Research in International Business and Finance, Elsevier, vol. 59(C).
    3. Riza Demirer & Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2022. "Risk aversion and the predictability of crude oil market volatility: A forecasting experiment with random forests," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 73(8), pages 1755-1767, August.
    4. Luo, Jiawen & Klein, Tony & Ji, Qiang & Hou, Chenghan, 2022. "Forecasting realized volatility of agricultural commodity futures with infinite Hidden Markov HAR models," International Journal of Forecasting, Elsevier, vol. 38(1), pages 51-73.
    5. Horpestad, Jone B. & Lyócsa, Štefan & Molnár, Peter & Olsen, Torbjørn B., 2019. "Asymmetric volatility in equity markets around the world," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 540-554.
    6. Lyócsa, Štefan & Molnár, Peter, 2018. "Exploiting dependence: Day-ahead volatility forecasting for crude oil and natural gas exchange-traded funds," Energy, Elsevier, vol. 155(C), pages 462-473.
    7. Aalborg, Halvor Aarhus & Molnár, Peter & de Vries, Jon Erik, 2019. "What can explain the price, volatility and trading volume of Bitcoin?," Finance Research Letters, Elsevier, vol. 29(C), pages 255-265.
    8. Lyócsa, Štefan & Molnár, Peter, 2017. "The effect of non-trading days on volatility forecasts in equity markets," Finance Research Letters, Elsevier, vol. 23(C), pages 39-49.
    9. Demirer, Riza & Gkillas, Konstantinos & Gupta, Rangan & Pierdzioch, Christian, 2019. "Time-varying risk aversion and realized gold volatility," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    10. Bissoondoyal-Bheenick, Emawtee & Brooks, Robert & Do, Hung Xuan & Smyth, Russell, 2020. "Exploiting the heteroskedasticity in measurement error to improve volatility predictions in oil and biofuel feedstock markets," Energy Economics, Elsevier, vol. 86(C).
    11. Ye, Chuxin & Lv, Jiamin & Xue, Yinsong & Luo, Xingguo, 2023. "Intraday volatility predictability in china gold futures market: The case of last half-hour realized volatility forecasting," Finance Research Letters, Elsevier, vol. 58(PA).
    12. Plíhal, Tomáš & Lyócsa, Štefan, 2021. "Modeling realized volatility of the EUR/USD exchange rate: Does implied volatility really matter?," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 811-829.

  38. 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.

    Cited by:

    1. Lyócsa, Štefan & Molnár, Peter & Todorova, Neda, 2017. "Volatility forecasting of non-ferrous metal futures: Covariances, covariates or combinations?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 51(C), pages 228-247.
    2. 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.
    3. Aalborg, Halvor Aarhus & Molnár, Peter & de Vries, Jon Erik, 2019. "What can explain the price, volatility and trading volume of Bitcoin?," Finance Research Letters, Elsevier, vol. 29(C), pages 255-265.
    4. Lyócsa, Štefan & Molnár, Peter, 2017. "The effect of non-trading days on volatility forecasts in equity markets," Finance Research Letters, Elsevier, vol. 23(C), pages 39-49.
    5. Lyócsa, Štefan & Todorova, Neda & Výrost, Tomáš, 2021. "Predicting risk in energy markets: Low-frequency data still matter," Applied Energy, Elsevier, vol. 282(PA).
    6. Victor Shevchuk & Roman Kopych, 2021. "Exchange Rate Volatility, Currency Misalignment, and Risk of Recession in the Central and Eastern European Countries," Risks, MDPI, vol. 9(5), pages 1-19, May.
    7. 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.

  39. Lyócsa, Štefan & Baumöhl, Eduard, 2015. "Similarity of emerging market returns under changing market conditions: Markets in the ASEAN-4, Latin America, Middle East, and BRICs," Economic Systems, Elsevier, vol. 39(2), pages 253-268.

    Cited by:

    1. Niţoi, Mihai & Pochea, Maria Miruna, 2016. "Testing financial markets convergence in Central and Eastern Europe: A non-linear single factor model," Economic Systems, Elsevier, vol. 40(2), pages 323-334.

  40. Výrost, Tomáš & Lyócsa, Štefan & Baumöhl, Eduard, 2015. "Granger causality stock market networks: Temporal proximity and preferential attachment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 427(C), pages 262-276.
    See citations under working paper version above.
  41. Baumöhl, Eduard & Lyócsa, Štefan, 2014. "Volatility and dynamic conditional correlations of worldwide emerging and frontier markets," Economic Modelling, Elsevier, vol. 38(C), pages 175-183.

    Cited by:

    1. Lyócsa, Štefan & Výrost, Tomáš & Baumöhl, Eduard, 2019. "Return spillovers around the globe: A network approach," Economic Modelling, Elsevier, vol. 77(C), pages 133-146.
    2. Yang, Lu & Cai, Xiao Jing & Li, Mengling & Hamori, Shigeyuki, 2015. "Modeling dependence structures among international stock markets: Evidence from hierarchical Archimedean copulas," Economic Modelling, Elsevier, vol. 51(C), pages 308-314.
    3. Maghyereh, Aktham I. & Awartani, Basel & Hilu, Khalil Al, 2015. "Dynamic transmissions between the U.S. and equity markets in the MENA countries: New evidence from pre- and post-global financial crisis," The Quarterly Review of Economics and Finance, Elsevier, vol. 56(C), pages 123-138.
    4. Škrinjarić Tihana, 2015. "Measuring Dynamics of Risk and Performance of Sector Indices on Zagreb Stock Exchange," Croatian Review of Economic, Business and Social Statistics, Sciendo, vol. 1(1-2), pages 27-41, December.
    5. Niţoi, Mihai & Pochea, Maria Miruna, 2020. "Time-varying dependence in European equity markets: A contagion and investor sentiment driven analysis," Economic Modelling, Elsevier, vol. 86(C), pages 133-147.
    6. Štefan Lyócsa & Roman Horváth, 2018. "Stock Market Contagion: a New Approach," Open Economies Review, Springer, vol. 29(3), pages 547-577, July.
    7. Mensah, Jones Odei & Alagidede, Paul, 2017. "How are Africa's emerging stock markets related to advanced markets? Evidence from copulas," Economic Modelling, Elsevier, vol. 60(C), pages 1-10.
    8. Shreevastava Aman & Raza Shahil & Bharat Kumar Meher & Ramona Birau & Anand Abhishek & Mircea Laurentiu Simion & Nadia Tudora Cirjan, 2024. "Exploring Advanced GARCH Models for Analyzing Asymmetric Volatility Dynamics for the Emerging Stock Market in Hungary: An Empirical Case Study," Economics and Applied Informatics, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, issue 2, pages 41-52.
    9. Mimouni, Karim & Charfeddine, Lanouar & Al-Azzam, Moh'd, 2016. "Do oil producing countries offer international diversification benefits? Evidence from GCC countries," Economic Modelling, Elsevier, vol. 57(C), pages 263-280.
    10. Deev, Oleg & Lyócsa, Štefan & Výrost, Tomáš, 2022. "The looming crisis in the Chinese stock market? Left-tail exposure analysis of Chinese stocks to Evergrande," Finance Research Letters, Elsevier, vol. 49(C).
    11. Eduard Baumöhl & Štefan Lyócsa, 2014. "Risk-Return Convergence in CEE Stock Markets: Structural Breaks and Market Volatility," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 64(5), pages 352-373, November.
    12. Ahmed, Walid M.A., 2020. "Corruption and equity market performance: International comparative evidence," Pacific-Basin Finance Journal, Elsevier, vol. 60(C).
    13. McIver, Ron P. & Kang, Sang Hoon, 2020. "Financial crises and the dynamics of the spillovers between the U.S. and BRICS stock markets," Research in International Business and Finance, Elsevier, vol. 54(C).
    14. Sriananthakumar, Sivagowry & Narayan, Seema, 2015. "Are prolonged conflict and tension deterrents for stock market integration? The case of Sri Lanka," International Review of Economics & Finance, Elsevier, vol. 39(C), pages 504-520.
    15. Wil Martens & Prem Yapa & Maryam Safari, 2021. "Earnings Management in Frontier Market: Do Institutional Settings Matter?," Economies, MDPI, vol. 9(1), pages 1-19, February.
    16. Lyócsa, Štefan & Baumöhl, Eduard, 2015. "Similarity of emerging market returns under changing market conditions: Markets in the ASEAN-4, Latin America, Middle East, and BRICs," Economic Systems, Elsevier, vol. 39(2), pages 253-268.
    17. Mokni, Khaled & Mansouri, Faysal, 2017. "Conditional dependence between international stock markets: A long memory GARCH-copula model approach," Journal of Multinational Financial Management, Elsevier, vol. 42, pages 116-131.
    18. Newaz, Mohammad Khaleq & Park, Jin Suk, 2019. "The impact of trade intensity and Market characteristics on asymmetric volatility, spillovers and asymmetric spillovers: Evidence from the response of international stock markets to US shocks," The Quarterly Review of Economics and Finance, Elsevier, vol. 71(C), pages 79-94.
    19. Neha Seth & Laxmidhar Panda, 2020. "Time-varying Correlation Between Indian Equity Market and Selected Asian and US Stock Markets," Global Business Review, International Management Institute, vol. 21(6), pages 1354-1375, December.

  42. Lyócsa, Štefan, 2014. "Growth-returns nexus: Evidence from three Central and Eastern European countries," Economic Modelling, Elsevier, vol. 42(C), pages 343-355.

    Cited by:

    1. Lyócsa, Štefan & Výrost, Tomáš & Plíhal, Tomáš, 2021. "A tale of tails : New evidence on the growth-return nexus," Finance Research Letters, Elsevier, vol. 38(C).
    2. Aviral K. Tiwari & Claudiu T. Albulescu & Rangan Gupta, 2016. "Time-frequency relationship between US output with commodity and asset prices," Applied Economics, Taylor & Francis Journals, vol. 48(3), pages 227-242, January.
    3. Muhammad Shafiullah & Usman Khalid & Sajid M. Chaudhry, 2022. "Do stock markets play a role in determining COVID‐19 economic stimulus? A cross‐country analysis," The World Economy, Wiley Blackwell, vol. 45(2), pages 386-408, February.
    4. Białkowski, Jędrzej & Dang, Huong Dieu & Wei, Xiaopeng, 2022. "High policy uncertainty and low implied market volatility: An academic puzzle?," Journal of Financial Economics, Elsevier, vol. 143(3), pages 1185-1208.
    5. Peter Molnár, 2016. "High-low range in GARCH models of stock return volatility," Applied Economics, Taylor & Francis Journals, vol. 48(51), pages 4977-4991, November.

  43. Eduard Baumöhl & Štefan Lyócsa, 2014. "Risk-Return Convergence in CEE Stock Markets: Structural Breaks and Market Volatility," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 64(5), pages 352-373, November.

    Cited by:

    1. Niţoi, Mihai & Pochea, Maria Miruna, 2016. "Testing financial markets convergence in Central and Eastern Europe: A non-linear single factor model," Economic Systems, Elsevier, vol. 40(2), pages 323-334.

  44. Dana PANCUROVA & Stefan LYOCSA, 2013. "Determinants of Commercial Banks’ Efficiency: Evidence from 11 CEE Countries," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(2), pages 152-179, May.

    Cited by:

    1. Tiantian Zhang & Zhenrong Liu, 2024. "Navigating Integration Through Rising Complexity: Convergence Dynamics in the ASEAN Banking Markets," Open Economies Review, Springer, vol. 35(4), pages 801-826, September.
    2. Viera Mendelová, 2021. "Decomposition of cost efficiency with adjustable prices: an application of data envelopment analysis," Operational Research, Springer, vol. 21(4), pages 2739-2770, December.
    3. Eva Horvatova, 2018. "Technical Efficiency of Banks in Central and Eastern Europe," IJFS, MDPI, vol. 6(3), pages 1-25, July.
    4. Konara, Palitha & Tan, Yong & Johnes, Jill, 2019. "FDI and heterogeneity in bank efficiency: Evidence from emerging markets," Research in International Business and Finance, Elsevier, vol. 49(C), pages 100-113.
    5. Mihai Nitoi & Cristi Spulbar, 2016. "The Relationship between Bank Efficiency and Risk and Productivity Patterns in the Romanian Banking System," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 39-53, March.
    6. C. Spulbăr & M. Niţoi, 2014. "Determinants of bank cost efficiency in transition economies: evidence for Latin America, Central and Eastern Europe and South-East Asia," Applied Economics, Taylor & Francis Journals, vol. 46(16), pages 1940-1952, June.
    7. Eva Horvatova, 2020. "Twenty Years of Mortgage Banking in Slovakia," IJFS, MDPI, vol. 8(3), pages 1-30, September.

  45. Vyrost, Tomas & Baumöhl, Eduard & Lyocsa, Stefan, 2013. "What Drives the Stock Market Integration in the CEE-3?," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 61(1), pages 67-81.

    Cited by:

    1. 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.

  46. Lyócsa, Štefan & Výrost, Tomáš & Baumöhl, Eduard, 2012. "Stock market networks: The dynamic conditional correlation approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(16), pages 4147-4158.

    Cited by:

    1. Lyócsa, Štefan & Výrost, Tomáš & Baumöhl, Eduard, 2019. "Return spillovers around the globe: A network approach," Economic Modelling, Elsevier, vol. 77(C), pages 133-146.
    2. 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.
    3. Zhang, Weiping & Zhuang, Xintian, 2019. "The stability of Chinese stock network and its mechanism," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 748-761.
    4. Zhou, Yang & Xie, Chi & Wang, Gang-Jin & Zhu, You & Uddin, Gazi Salah, 2023. "Analysing and forecasting co-movement between innovative and traditional financial assets based on complex network and machine learning," Research in International Business and Finance, Elsevier, vol. 64(C).
    5. Su, Qingqing & Tu, Lilan & Wang, Xianjia & Rong, Hang, 2022. "Construction and robustness of directed-weighted financial stock networks via meso-scales," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 605(C).
    6. Výrost, Tomáš, 2012. "Country effects in CEE3 stock market networks: a preliminary study," MPRA Paper 43481, University Library of Munich, Germany.
    7. Sensoy, Ahmet & Tabak, Benjamin M., 2014. "Dynamic spanning trees in stock market networks: The case of Asia-Pacific," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 414(C), pages 387-402.
    8. Kundu, Srikanta & Sarkar, Nityananda, 2016. "Return and volatility interdependences in up and down markets across developed and emerging countries," Research in International Business and Finance, Elsevier, vol. 36(C), pages 297-311.
    9. Brida, Juan Gabriel & Matesanz, David & Seijas, Maria Nela, 2016. "Network analysis of returns and volume trading in stock markets: The Euro Stoxx case," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 751-764.
    10. Gautier Marti & Frank Nielsen & Miko{l}aj Bi'nkowski & Philippe Donnat, 2017. "A review of two decades of correlations, hierarchies, networks and clustering in financial markets," Papers 1703.00485, arXiv.org, revised Nov 2020.
    11. Deev, Oleg & Lyócsa, Štefan, 2020. "Connectedness of financial institutions in Europe: A network approach across quantiles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 550(C).
    12. Yang, Xu-Hua & Lou, Shun-Li & Chen, Guang & Chen, Sheng-Yong & Huang, Wei, 2013. "Scale-free networks via attaching to random neighbors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(17), pages 3531-3536.
    13. Výrost, Tomáš & Lyócsa, Štefan & Baumöhl, Eduard, 2015. "Granger causality stock market networks: Temporal proximity and preferential attachment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 427(C), pages 262-276.
    14. Wang, Gang-Jin & Wan, Li & Feng, Yusen & Xie, Chi & Uddin, Gazi Salah & Zhu, You, 2023. "Interconnected multilayer networks: Quantifying connectedness among global stock and foreign exchange markets," International Review of Financial Analysis, Elsevier, vol. 86(C).
    15. Brida, Juan Gabriel & Gómez, David Matesanz & Seijas, Maria Nela, 2017. "Debt and growth: A non-parametric approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 883-894.
    16. Papana, Angeliki & Kyrtsou, Catherine & Kugiumtzis, Dimitris & Diks, Cees, 2017. "Financial networks based on Granger causality: A case study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 65-73.
    17. Huang, Wei-Qiang & Zhuang, Xin-Tian & Yao, Shuang & Uryasev, Stan, 2016. "A financial network perspective of financial institutions’ systemic risk contributions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 183-196.
    18. Gogas, Periklis & Papadimitriou, Theophilos & Matthaiou, Maria-Artemis, 2016. "Bank supervision using the Threshold-Minimum Dominating Set," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 23-35.

  47. Zarembova, Andrea & Lyocsa, Stefan & Baumöhl, Eduard, 2012. "The Real Convergence of CEE Countries: A Study of Real GDP per capita," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 60(6), pages 642-656.

    Cited by:

    1. Viorica Chirila & Ciprian Chirila, 2021. "Analysis of GDP per Capita Convergence Speed in the Member States of the European Union," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(2), pages 101-108, December.

  48. E. Baumohl & S. Lyocsa & T. Vyrost, 2011. "Shift contagion with endogenously detected volatility breaks: the case of CEE stock markets," Applied Economics Letters, Taylor & Francis Journals, vol. 18(12), pages 1103-1109.

    Cited by:

    1. Baumöhl, Eduard, 2013. "Stock market integration between the CEE-4 and the G7 markets: Asymmetric DCC and smooth transition approach," MPRA Paper 43834, University Library of Munich, Germany.
    2. Vyrost, Tomas & Baumöhl, Eduard & Lyocsa, Stefan, 2013. "What Drives the Stock Market Integration in the CEE-3?," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 61(1), pages 67-81.
    3. Eduard Baumöhl & Štefan Lyócsa, 2014. "Risk-Return Convergence in CEE Stock Markets: Structural Breaks and Market Volatility," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 64(5), pages 352-373, November.
    4. Baumohl, Eduard & Lyocsa, Stefan, 2013. "Volatility and dynamic conditional correlations of European emerging stock markets," MPRA Paper 49898, University Library of Munich, Germany.
    5. Eduard Baum??hl & ??tefan Ly??csa, 2014. "How smooth is the stock market integration of CEE-3?," William Davidson Institute Working Papers Series wp1079, William Davidson Institute at the University of Michigan.
    6. Eduard Baumöhl & Štefan Lyócsa & Tomáš Výrost, 2011. "Volatility Regimes in Macroeconomic Time Series: The Case of the Visegrad Group," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 61(6), pages 530-544, December.
    7. Eduard Baumöhl, 2014. "Determinanty integrácie akciových trhov krajín V4 [Determinants of CEE-4 Stock Market Integration]," Politická ekonomie, Prague University of Economics and Business, vol. 2014(3), pages 347-365.
    8. Baumöhl, Eduard & Lyócsa, Štefan, 2014. "Volatility and dynamic conditional correlations of worldwide emerging and frontier markets," Economic Modelling, Elsevier, vol. 38(C), pages 175-183.

  49. Eduard Baumöhl & Štefan Lyócsa & Tomáš Výrost, 2011. "Volatility Regimes in Macroeconomic Time Series: The Case of the Visegrad Group," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 61(6), pages 530-544, December.

    Cited by:

    1. Zarembova, Andrea & Lyocsa, Stefan & Baumöhl, Eduard, 2012. "The Real Convergence of CEE Countries: A Study of Real GDP per capita," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 60(6), pages 642-656.

  50. Stefan Lyocsa & Eduard Baumohl & Tomas Vyrost, 2011. "The Stock Markets and Real Economic Activity," Eastern European Economics, Taylor & Francis Journals, vol. 49(4), pages 6-23, July.

    Cited by:

    1. Baumöhl, Eduard, 2013. "Stock market integration between the CEE-4 and the G7 markets: Asymmetric DCC and smooth transition approach," MPRA Paper 43834, University Library of Munich, Germany.
    2. Lyócsa, Štefan & Výrost, Tomáš & Baumöhl, Eduard, 2011. "Unit-root and stationarity testing with empirical application on industrial production of CEE-4 countries," MPRA Paper 29648, University Library of Munich, Germany.
    3. Małgorzata Iwanicz-Drozdowska & Paola Bongini & Paweł Smaga & Bartosz Witkowski, 2019. "The role of banks in CESEE countries: exploring non-standard determinants of economic growth," Post-Communist Economies, Taylor & Francis Journals, vol. 31(3), pages 349-382, May.
    4. Lyócsa, Štefan, 2014. "Growth-returns nexus: Evidence from three Central and Eastern European countries," Economic Modelling, Elsevier, vol. 42(C), pages 343-355.
    5. Ülkü, Numan & Kuruppuarachchi, Duminda & Kuzmicheva, Olga, 2017. "Stock market's response to real output shocks in Eastern European frontier markets: A VARwAL model," Emerging Markets Review, Elsevier, vol. 33(C), pages 140-154.

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