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Keven Bluteau

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. David Ardia & Keven Bluteau & Thien Duy Tran, 2022. "How easy is it for investment managers to deploy their talent in green and brown stocks?," Papers 2201.05709, arXiv.org, revised Apr 2023.

    Cited by:

    1. Ardia, David & Bluteau, Keven & Lortie-Cloutier, Gabriel & Duy Tran, Thien, 2023. "Factor exposure heterogeneity in green and brown stocks," Finance Research Letters, Elsevier, vol. 55(PA).

  2. David Ardia & Keven Bluteau & Kris Boudt, 2021. "Media abnormal tone, earnings announcements, and the stock market," Papers 2110.10800, arXiv.org.

    Cited by:

    1. Perico Ortiz, Daniel & Schnaubelt, Matthias & Seifert, Oleg, 2023. "A topic modeling perspective on investor uncertainty," FAU Discussion Papers in Economics 04/2023, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.

  3. David Ardia & Keven Bluteau & Kris Boudt & Koen Inghelbrecht, 2020. "Climate change concerns and the performance of green versus brown stocks," Working Paper Research 395, National Bank of Belgium.

    Cited by:

    1. Bua, Giovanna & Kapp, Daniel & Ramella, Federico & Rognone, Lavinia, 2022. "Transition versus physical climate risk pricing in European financial markets: a text-based approach," Working Paper Series 2677, European Central Bank.
    2. Meinerding, Christoph & Schüler, Yves S. & Zhang, Philipp, 2023. "Shocks to transition risk," Discussion Papers 04/2023, Deutsche Bundesbank.
    3. Rabeh Khalfaoui & Salma Mefteh-Wali & Jean-Laurent Viviani & Sami Ben Jabeur & Mohammad Zoynul Abedin & Brian Lucey, 2022. "How do climate risk and clean energy spillovers, and uncertainty affect U.S. stock markets?," Post-Print hal-03797937, HAL.
    4. Apel, Matthias & Betzer, André & Scherer, Bernd, 2023. "Real-time transition risk," Finance Research Letters, Elsevier, vol. 53(C).
    5. Inessa BENCHORA & Aurélien LEROY & Louis RAFFESTIN, 2023. "Is Monetary Policy Transmission Green?," Bordeaux Economics Working Papers 2023-08, Bordeaux School of Economics (BSE).
    6. Tiziano De Angelis & Peter Tankov & Olivier David Zerbib, 2022. "Climate Impact Investing," Carlo Alberto Notebooks 676 JEL Classification: G, Collegio Carlo Alberto.
    7. Venturini, Alessio, 2022. "Climate change, risk factors and stock returns: A review of the literature," International Review of Financial Analysis, Elsevier, vol. 79(C).
    8. Milot Hasaj & Bernd Scherer, 2021. "Covid-19 and smart beta," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 35(4), pages 515-532, December.
    9. Ardia, David & Bluteau, Keven & Tran, Thien Duy, 2022. "How easy is it for investment managers to deploy their talent in green and brown stocks?," Finance Research Letters, Elsevier, vol. 48(C).
    10. Iulia Lupu & Adina Criste, 2022. "Tendencies In Green Finance," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 3, pages 57-63, June.
    11. Pástor, Luboš & Stambaugh, Robert F. & Taylor, Lucian, 2022. "Dissecting Green Returns," CEPR Discussion Papers 16260, C.E.P.R. Discussion Papers.
    12. Du, Qianqian & Su, Wanxuan & Liang, Dawei & Wang, Luying, 2023. "How does green preference impact sustainability-based investment strategy? Evidence from the Chinese stock market," Economic Modelling, Elsevier, vol. 124(C).
    13. Joost Bats & Giovanna Bua & Daniel Kapp, 2023. "Physical and transition risk premiums in euro area corporate bond markets," Working Papers 761, DNB.
    14. Zhang, Si Ying, 2022. "Are investors sensitive to climate-related transition and physical risks? Evidence from global stock markets," Research in International Business and Finance, Elsevier, vol. 62(C).
    15. Bats, Joost Victor & Bua, Giovanna & Kapp, Daniel, 2024. "Physical and transition risk premiums in euro area corporate bond markets," Working Paper Series 2899, European Central Bank.
    16. Olivier David Zerbib, 2022. "A Sustainable Capital Asset Pricing Model (S-CAPM): Evidence from Environmental Integration and Sin Stock Exclusion [Asset pricing with liquidity risk]," Review of Finance, European Finance Association, vol. 26(6), pages 1345-1388.
    17. Borghesi, S. & Castellini, M. & Comincioli, N. & Donadelli, M. & Gufler, I. & Vergalli, S., 2022. "European green policy announcements and sectoral stock returns," Energy Policy, Elsevier, vol. 166(C).
    18. Ho, Kelvin & Wong, Andrew, 2023. "Effect of climate-related risk on the costs of bank loans: Evidence from syndicated loan markets in emerging economies," Emerging Markets Review, Elsevier, vol. 55(C).

Articles

  1. Ardia, David & Bluteau, Keven & Boudt, Kris, 2022. "Media abnormal tone, earnings announcements, and the stock market," Journal of Financial Markets, Elsevier, vol. 61(C).
    See citations under working paper version above.
  2. Ardia, David & Bluteau, Keven & Tran, Thien Duy, 2022. "How easy is it for investment managers to deploy their talent in green and brown stocks?," Finance Research Letters, Elsevier, vol. 48(C).
    See citations under working paper version above.
  3. Andres Algaba & David Ardia & Keven Bluteau & Samuel Borms & Kris Boudt, 2020. "Econometrics Meets Sentiment: An Overview Of Methodology And Applications," Journal of Economic Surveys, Wiley Blackwell, vol. 34(3), pages 512-547, July.

    Cited by:

    1. Ardia, David & Bluteau, Keven & Boudt, Kris, 2022. "Media abnormal tone, earnings announcements, and the stock market," Journal of Financial Markets, Elsevier, vol. 61(C).
    2. Gerardin Mathilde, & Ranvier Martial., 2021. "Enrichment of the Banque de France’s monthly business survey: lessons from textual analysis of business leaders’ comments," Working papers 821, Banque de France.
    3. Hoang, Daniel & Wiegratz, Kevin, 2022. "Machine learning methods in finance: Recent applications and prospects," Working Paper Series in Economics 158, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    4. Bo Yan & Mengru Liang & Yinxin Zhao, 2024. "Market sentiment and price dynamics in weak markets: A comprehensive empirical analysis of the soybean meal option market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(5), pages 744-766, May.
    5. de Medeiros, Rennan Kertlly & da Silva Bejarano Aragón, Edilean Kleber & Besarria, Cássio da Nóbrega, 2023. "Effects of oil market sentiment on macroeconomic variables," Resources Policy, Elsevier, vol. 83(C).
    6. Peter A.G. van Bergeijk, 2021. "Pandemic Economics," Books, Edward Elgar Publishing, number 20401.
    7. Danilo Vassallo & Giacomo Bormetti & Fabrizio Lillo, 2019. "A tale of two sentiment scales: Disentangling short-run and long-run components in multivariate sentiment dynamics," Papers 1910.01407, arXiv.org, revised Sep 2020.
    8. Robert Lehmann, 2020. "The Forecasting Power of the ifo Business Survey," CESifo Working Paper Series 8291, CESifo.
    9. VAN DER WIELEN Wouter & BARRIOS Salvador, 2020. "Fear and Employment During the COVID Pandemic: Evidence from Search Behaviour in the EU," JRC Working Papers on Taxation & Structural Reforms 2020-08, Joint Research Centre.
    10. Hubert, Paul & Labondance, Fabien, 2021. "The signaling effects of central bank tone," European Economic Review, Elsevier, vol. 133(C).
    11. Karol Szafranek & Michał Rubaszek & Gazi Salah Uddin, 2023. "The role of uncertainty and sentiment for intraday volatility connectedness between oil and financial markets," KAE Working Papers 2023-095, Warsaw School of Economics, Collegium of Economic Analysis.
    12. Kishor, N. Kundan & Pratap, Bhanu, 2023. "The Role of Inflation Targeting in Anchoring Long-Run Inflation Expectations: Evidence from India," MPRA Paper 118951, University Library of Munich, Germany.
    13. Ahelegbey, Daniel Felix & Cerchiello, Paola & Scaramozzino, Roberta, 2022. "Network based evidence of the financial impact of Covid-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 81(C).
    14. Mikhail Stolbov & Maria Shchepeleva, 2023. "Sentiment-based indicators of real estate market stress and systemic risk: international evidence," Annals of Finance, Springer, vol. 19(3), pages 355-382, September.
    15. Simionescu, Mihaela, 2022. "Econometrics of sentiments- sentometrics and machine learning: The improvement of inflation predictions in Romania using sentiment analysis," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    16. Christopher Adamo & Jeffrey Carpenter, 2023. "Sentiment and the belief in fake news during the 2020 presidential primaries," Oxford Open Economics, Oxford University Press, vol. 2, pages 512-547.
    17. Mazzotta, Stefano, 2022. "Immigration narrative sentiment from TV news and the stock market," Journal of Behavioral and Experimental Finance, Elsevier, vol. 34(C).
    18. Gianni La Cava, 2021. "Smells Like Animal Spirits: The Effect of Corporate Sentiment on Investment," RBA Research Discussion Papers rdp2021-11, Reserve Bank of Australia.
    19. Aakriti Mathur & Rajeswari Sengupta & Bhanu Pratap, 2022. "Saved by the bell? Equity market responses to surprise Covid-19 lockdowns and central bank interventions," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2022-001, Indira Gandhi Institute of Development Research, Mumbai, India.
    20. Stolbov, Mikhail & Shchepeleva, Maria & Karminsky, Alexander, 2022. "When central bank research meets Google search: A sentiment index of global financial stress," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    21. Ballandonne, Matthieu & Cersosimo, Igor, 2022. "Towards a “Text as Data” Approach in the History of Economics: An Application to Adam Smith’s Classics," OSF Preprints mg3zb, Center for Open Science.
    22. Andres Algaba & Samuel Borms & Kris Boudt & Brecht Verbeken, 2021. "Daily news sentiment and monthly surveys: A mixed–frequency dynamic factor model for nowcasting consumer confidence," Working Paper Research 396, National Bank of Belgium.
    23. Dorinth van Dijk & Jasper de Winter, 2023. "Nowcasting GDP using tone-adjusted time varying news topics: Evidence from the financial press," Working Papers 766, DNB.
    24. Baranowski, Paweł & Doryń, Wirginia & Łyziak, Tomasz & Stanisławska, Ewa, 2021. "Words and deeds in managing expectations: Empirical evidence from an inflation targeting economy," Economic Modelling, Elsevier, vol. 95(C), pages 49-67.
    25. Jae H. Kim, 2022. "Moving to a world beyond p-value," Review of Managerial Science, Springer, vol. 16(8), pages 2467-2493, November.
    26. Yu, Zhen & Liu, Wei & Yang, Fuyu, 2023. "A central bankers’ sentiment index of global financial cycle," Finance Research Letters, Elsevier, vol. 57(C).
    27. Mikhaylov, Dmitry, 2023. "Macroeconomic Forecasting with the Use of News Data," Working Papers w20220250, Russian Presidential Academy of National Economy and Public Administration.
    28. Elena Shulyak, 2022. "Macroeconomic Forecasting Using Data from Social Media," Russian Journal of Money and Finance, Bank of Russia, vol. 81(4), pages 86-112, December.
    29. Łukasz Baszczak, 2023. "Ekonomia narracji – początki nowego nurtu," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 1, pages 66-81.
    30. Aktham Maghyereh & Hussein Abdoh, 2022. "Can news-based economic sentiment predict bubbles in precious metal markets?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-29, December.
    31. Christoph Kronenberg, 2021. "A New Measure of 19th Century US Suicides," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 157(2), pages 803-815, September.
    32. Antón Sarabia Arturo & Bazdresch Santiago & Lelo-de-Larrea Alejandra, 2023. "The Influence of Central Bank's Projections and Economic Narrative on Professional Forecasters' Expectations: Evidence from Mexico," Working Papers 2023-21, Banco de México.
    33. Fabozzi, Francesco A. & Nazemi, Abdolreza, 2023. "News-based sentiment and the value premium," Journal of International Money and Finance, Elsevier, vol. 136(C).
    34. khan Feroz, Noushad & Hassan, Gazi & Cameron, Michael P., 2022. "To what extent do network effects moderate the relationship between social media propagated news and investors’ perceptions?," Research in Economics, Elsevier, vol. 76(3), pages 170-188.
    35. Aromi, J. Daniel & Clements, Adam, 2021. "Facial expressions and the business cycle," Economic Modelling, Elsevier, vol. 102(C).

  4. Ardia, David & Bluteau, Keven & Rüede, Maxime, 2019. "Regime changes in Bitcoin GARCH volatility dynamics," Finance Research Letters, Elsevier, vol. 29(C), pages 266-271.

    Cited by:

    1. Fantazzini, Dean, 2022. "Crypto Coins and Credit Risk: Modelling and Forecasting their Probability of Death," MPRA Paper 113744, University Library of Munich, Germany.
    2. Kawakami, Tabito, 2023. "Quantile prediction for Bitcoin returns using financial assets’ realized measures," Finance Research Letters, Elsevier, vol. 55(PA).
    3. Panagiotidis, Theodore & Papapanagiotou, Georgios & Stengos, Thanasis, 2022. "On the volatility of cryptocurrencies," Research in International Business and Finance, Elsevier, vol. 62(C).
    4. OlaOluwa S. Yaya & Ahamuefula E. Ogbonna & Robert Mudida & Nuruddeen Abu, 2021. "Market efficiency and volatility persistence of cryptocurrency during pre‐ and post‐crash periods of Bitcoin: Evidence based on fractional integration," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 1318-1335, January.
    5. Jingxuan Liu & Ping Qiao & Jian Ding & Luke Hankinson & Elodie H. Harriman & Edward M. Schiller & Ieva Ramanauskaite & Haowei Zhang, 2020. "Will the Aviation Industry Have a Bright Future after the COVID-19 Outbreak? Evidence from Chinese Airport Shipping Sector," JRFM, MDPI, vol. 13(11), pages 1-14, November.
    6. Elie Bouri & Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2021. "Forecasting Realized Volatility of Bitcoin: The Role of the Trade War," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 29-53, January.
    7. Carlos Trucíos & James W. Taylor, 2023. "A comparison of methods for forecasting value at risk and expected shortfall of cryptocurrencies," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 989-1007, July.
    8. Mawuli Segnon & Stelios Bekiros, 2020. "Forecasting volatility in bitcoin market," Annals of Finance, Springer, vol. 16(3), pages 435-462, September.
    9. Pınar Kaya Soylu & Mustafa Okur & Özgür Çatıkkaş & Z. Ayca Altintig, 2020. "Long Memory in the Volatility of Selected Cryptocurrencies: Bitcoin, Ethereum and Ripple," JRFM, MDPI, vol. 13(6), pages 1-21, May.
    10. Ángeles Cebrián-Hernández & Enrique Jiménez-Rodríguez, 2021. "Modeling of the Bitcoin Volatility through Key Financial Environment Variables: An Application of Conditional Correlation MGARCH Models," Mathematics, MDPI, vol. 9(3), pages 1-16, January.
    11. Kuo-Shing Chen & Yu-Chuan Huang, 2021. "Detecting Jump Risk and Jump-Diffusion Model for Bitcoin Options Pricing and Hedging," Mathematics, MDPI, vol. 9(20), pages 1-24, October.
    12. Chappell, Daniel, 2018. "Regime heteroskedasticity in Bitcoin: A comparison of Markov switching models," MPRA Paper 90682, University Library of Munich, Germany.
    13. Caporale, Guglielmo Maria & Zekokh, Timur, 2019. "Modelling volatility of cryptocurrencies using Markov-Switching GARCH models," Research in International Business and Finance, Elsevier, vol. 48(C), pages 143-155.
    14. Constandina Koki & Stefanos Leonardos & Georgios Piliouras, 2020. "Do Cryptocurrency Prices Camouflage Latent Economic Effects? A Bayesian Hidden Markov Approach," Future Internet, MDPI, vol. 12(3), pages 1-19, March.
    15. Lai T. Hoang & Dirk G. Baur, 2020. "Forecasting bitcoin volatility: Evidence from the options market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(10), pages 1584-1602, October.
    16. Skander Slim & Ibrahim Tabche & Yosra Koubaa & Mohamed Osman & Andreas Karathanasopoulos, 2023. "Forecasting realized volatility of Bitcoin: The informative role of price duration," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(7), pages 1909-1929, November.
    17. Fung, Kennard & Jeong, Jiin & Pereira, Javier, 2022. "More to cryptos than bitcoin: A GARCH modelling of heterogeneous cryptocurrencies," Finance Research Letters, Elsevier, vol. 47(PA).
    18. Ke, Rui & Yang, Luyao & Tan, Changchun, 2022. "Forecasting tail risk for Bitcoin: A dynamic peak over threshold approach," Finance Research Letters, Elsevier, vol. 49(C).
    19. Ataurima Arellano, Miguel & Rodríguez, Gabriel, 2020. "Empirical modeling of high-income and emerging stock and Forex market return volatility using Markov-switching GARCH models," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    20. Borri, Nicola, 2019. "Conditional tail-risk in cryptocurrency markets," Journal of Empirical Finance, Elsevier, vol. 50(C), pages 1-19.
    21. Nidhal Mgadmi & Azza Béjaoui & Wajdi Moussa, 2023. "Disentangling the Nonlinearity Effect in Cryptocurrency Markets During the Covid-19 Pandemic: Evidence from a Regime-Switching Approach," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 30(3), pages 457-473, September.
    22. Amaro, Raphael & Pinho, Carlos, 2022. "Energy commodities: A study on model selection for estimating Value-at-Risk," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 68, pages 5-27.
    23. Urom, Christian & Onwuka, Kevin O. & Uma, Kalu E. & Yuni, Denis N., 2020. "Regime dependent effects and cyclical volatility spillover between crude oil price movements and stock returns," International Economics, Elsevier, vol. 161(C), pages 10-29.
    24. Jiang, Kunliang & Zeng, Linhui & Song, Jiashan & Liu, Yimeng, 2022. "Forecasting Value-at-Risk of cryptocurrencies using the time-varying mixture-accelerating generalized autoregressive score model," Research in International Business and Finance, Elsevier, vol. 61(C).
    25. Jens Klose, 2022. "Comparing cryptocurrencies and gold - a system-GARCH-approach," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 12(4), pages 653-679, December.
    26. Yaojie Zhang & Mengxi He & Danyan Wen & Yudong Wang, 2022. "Forecasting Bitcoin volatility: A new insight from the threshold regression model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 633-652, April.
    27. Fan Fang & Carmine Ventre & Michail Basios & Leslie Kanthan & David Martinez-Rego & Fan Wu & Lingbo Li, 2022. "Cryptocurrency trading: a comprehensive survey," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-59, December.
    28. Aharon, David Y. & Butt, Hassan Anjum & Jaffri, Ali & Nichols, Brian, 2023. "Asymmetric volatility in the cryptocurrency market: New evidence from models with structural breaks," International Review of Financial Analysis, Elsevier, vol. 87(C).
    29. Ding, Shusheng & Cui, Tianxiang & Wu, Xiangling & Du, Min, 2022. "Supply chain management based on volatility clustering: The effect of CBDC volatility," Research in International Business and Finance, Elsevier, vol. 62(C).
    30. Ramzi Nekhili & Jahangir Sultan, 2020. "Jump Driven Risk Model Performance in Cryptocurrency Market," IJFS, MDPI, vol. 8(2), pages 1-18, April.
    31. Yin, Libo & Nie, Jing & Han, Liyan, 2021. "Understanding cryptocurrency volatility: The role of oil market shocks," International Review of Economics & Finance, Elsevier, vol. 72(C), pages 233-253.
    32. Abdulkadir Kaya & İkram Yusuf Yarbaşı, 2021. "Forecasting of Volatility in Stock Exchange Markets by MS-GARCH Approach: An Application of Borsa Istanbul," Journal of Research in Economics, Politics & Finance, Ersan ERSOY, vol. 6(1), pages 16-35.
    33. Park, Beum-Jo, 2022. "The COVID-19 pandemic, volatility, and trading behavior in the bitcoin futures market," Research in International Business and Finance, Elsevier, vol. 59(C).
    34. Nikolaos A. Kyriazis, 2021. "A Survey on Volatility Fluctuations in the Decentralized Cryptocurrency Financial Assets," JRFM, MDPI, vol. 14(7), pages 1-46, June.
    35. Zhang, Dingxuan & Sun, Yuying & Duan, Hongbo & Hong, Yongmiao & Wang, Shouyang, 2023. "Speculation or currency? Multi-scale analysis of cryptocurrencies—The case of Bitcoin," International Review of Financial Analysis, Elsevier, vol. 88(C).
    36. Leandro Maciel, 2021. "Cryptocurrencies value‐at‐risk and expected shortfall: Do regime‐switching volatility models improve forecasting?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4840-4855, July.
    37. Ilhami KARAHANOGLU, 2020. "The VaR comparison of the fresh investment toolBITCOIN with other conventional investment tools, gold, stock exchange (BIST100) and foreign currencies (EUR/USD VS TRL)," Eastern Journal of European Studies, Centre for European Studies, Alexandru Ioan Cuza University, vol. 11, pages 160-181, December.
    38. Corbet, Shaen & Lucey, Brian & Urquhart, Andrew & Yarovaya, Larisa, 2019. "Cryptocurrencies as a financial asset: A systematic analysis," International Review of Financial Analysis, Elsevier, vol. 62(C), pages 182-199.
    39. Dimitrios Koutmos & James E. Payne, 2021. "Intertemporal asset pricing with bitcoin," Review of Quantitative Finance and Accounting, Springer, vol. 56(2), pages 619-645, February.
    40. Koki, Constandina & Leonardos, Stefanos & Piliouras, Georgios, 2022. "Exploring the predictability of cryptocurrencies via Bayesian hidden Markov models," Research in International Business and Finance, Elsevier, vol. 59(C).
    41. Trucíos, Carlos, 2019. "Forecasting Bitcoin risk measures: A robust approach," International Journal of Forecasting, Elsevier, vol. 35(3), pages 836-847.
    42. Dirk G. Baur & Thomas Dimpfl, 2021. "The volatility of Bitcoin and its role as a medium of exchange and a store of value," Empirical Economics, Springer, vol. 61(5), pages 2663-2683, November.
    43. Vahidin Jeleskovic & Mirko Meloni & Zahid Irshad Younas, 2020. "Cryptocurrencies: A Copula Based Approach for Asymmetric Risk Marginal Allocations," MAGKS Papers on Economics 202034, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    44. Klaudia Jarno & Hanna Kołodziejczyk, 2021. "Does the Design of Stablecoins Impact Their Volatility?," JRFM, MDPI, vol. 14(2), pages 1-14, January.
    45. Katsiampa, Paraskevi & Corbet, Shaen & Lucey, Brian, 2019. "Volatility spillover effects in leading cryptocurrencies: A BEKK-MGARCH analysis," Finance Research Letters, Elsevier, vol. 29(C), pages 68-74.
    46. Natalya Apopo & Andrew Phiri, 2019. "On the (in)efficiency of cryptocurrencies: Have they taken daily or weekly random walks?," Working Papers 1904, Department of Economics, Nelson Mandela University, revised Jun 2019.
    47. Jalan, Akanksha & Matkovskyy, Roman & Urquhart, Andrew & Yarovaya, Larisa, 2023. "The role of interpersonal trust in cryptocurrency adoption," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 83(C).
    48. Kejia Yan & Huqin Yan & Rakesh Gupta, 2022. "Are GARCH and DCC Values of 10 Cryptocurrencies Affected by COVID-19?," JRFM, MDPI, vol. 15(3), pages 1-25, March.
    49. Feng Ma & Chao Liang & Yuanhui Ma & M.I.M. Wahab, 2020. "Cryptocurrency volatility forecasting: A Markov regime‐switching MIDAS approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(8), pages 1277-1290, December.
    50. Amélie Charles & Olivier Darné, 2019. "Volatility estimation for cryptocurrencies: Further evidence with jumps and structural breaks," Economics Bulletin, AccessEcon, vol. 39(2), pages 954-968.
    51. Alessio Brini & Jimmie Lenz, 2024. "A Comparison of Cryptocurrency Volatility-benchmarking New and Mature Asset Classes," Papers 2404.04962, arXiv.org.
    52. Qian, Lihua & Wang, Jiqian & Ma, Feng & Li, Ziyang, 2022. "Bitcoin volatility predictability–The role of jumps and regimes," Finance Research Letters, Elsevier, vol. 47(PB).
    53. Cretarola, Alessandra & Figà-Talamanca, Gianna, 2020. "Bubble regime identification in an attention-based model for Bitcoin and Ethereum price dynamics," Economics Letters, Elsevier, vol. 191(C).
    54. Walther, Thomas & Klein, Tony & Bouri, Elie, 2018. "Exogenous Drivers of Bitcoin and Cryptocurrency Volatility – A Mixed Data Sampling Approach to Forecasting," QBS Working Paper Series 2018/02, Queen's University Belfast, Queen's Business School.
    55. Jiménez, Inés & Mora-Valencia, Andrés & Perote, Javier, 2022. "Semi-nonparametric risk assessment with cryptocurrencies," Research in International Business and Finance, Elsevier, vol. 59(C).
    56. Wu, Chuanzhen, 2021. "Window effect with Markov-switching GARCH model in cryptocurrency market," Chaos, Solitons & Fractals, Elsevier, vol. 146(C).
    57. Uzonwanne, Godfrey, 2021. "Volatility and return spillovers between stock markets and cryptocurrencies," The Quarterly Review of Economics and Finance, Elsevier, vol. 82(C), pages 30-36.
    58. Naeem, Muhammad Abubakr & Lucey, Brian M. & Karim, Sitara & Ghafoor, Abdul, 2022. "Do financial volatilities mitigate the risk of cryptocurrency indexes?," Finance Research Letters, Elsevier, vol. 50(C).
    59. Tan, Shay-Kee & Chan, Jennifer So-Kuen & Ng, Kok-Haur, 2020. "On the speculative nature of cryptocurrencies: A study on Garman and Klass volatility measure," Finance Research Letters, Elsevier, vol. 32(C).
    60. José Antonio Núñez-Mora & Roberto Joaquín Santillán-Salgado & Mario Iván Contreras-Valdez, 2022. "COVID Asymmetric Impact on the Risk Premium of Developed and Emerging Countries’ Stock Markets," Mathematics, MDPI, vol. 10(9), pages 1-36, April.
    61. Shuzhen Yang, 2021. "Compensatory model for quantile estimation and application to VaR," Papers 2112.07278, arXiv.org.
    62. Grobys, Klaus & Junttila, Juha & Kolari, James W. & Sapkota, Niranjan, 2021. "On the stability of stablecoins," Journal of Empirical Finance, Elsevier, vol. 64(C), pages 207-223.
    63. Qiu, Yue & Wang, Zongrun & Xie, Tian & Zhang, Xinyu, 2021. "Forecasting Bitcoin realized volatility by exploiting measurement error under model uncertainty," Journal of Empirical Finance, Elsevier, vol. 62(C), pages 179-201.
    64. Shi, Yanlin & Ho, Kin-Yip, 2021. "News sentiment and states of stock return volatility: Evidence from long memory and discrete choice models," Finance Research Letters, Elsevier, vol. 38(C).
    65. Saketh Aleti & Bruce Mizrach, 2021. "Bitcoin spot and futures market microstructure," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(2), pages 194-225, February.
    66. Stephanie Danielle Subramoney & Knowledge Chinhamu & Retius Chifurira, 2021. "Value at Risk estimation using GAS models with heavy tailed distributions for cryptocurrencies," International Journal of Finance & Banking Studies, Center for the Strategic Studies in Business and Finance, vol. 10(4), pages 40-54, October.
    67. Sun Meng & Yan Chen, 2023. "Market Volatility Spillover, Network Diffusion, and Financial Systemic Risk Management: Financial Modeling and Empirical Study," Mathematics, MDPI, vol. 11(6), pages 1-16, March.
    68. Figà-Talamanca, Gianna & Focardi, Sergio & Patacca, Marco, 2021. "Regime switches and commonalities of the cryptocurrencies asset class," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    69. Angerer, Martin & Hoffmann, Christian Hugo & Neitzert, Florian & Kraus, Sascha, 2021. "Objective and subjective risks of investing into cryptocurrencies," Finance Research Letters, Elsevier, vol. 40(C).
    70. Tan, Chia-Yen & Koh, You-Beng & Ng, Kok-Haur & Ng, Kooi-Huat, 2021. "Dynamic volatility modelling of Bitcoin using time-varying transition probability Markov-switching GARCH model," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    71. Gradojevic, Nikola & Tsiakas, Ilias, 2021. "Volatility cascades in cryptocurrency trading," Journal of Empirical Finance, Elsevier, vol. 62(C), pages 252-265.
    72. Pinar Deniz & Thanasis Stengos, 2020. "Cryptocurrency Returns before and after the Introduction of Bitcoin Futures," JRFM, MDPI, vol. 13(6), pages 1-21, June.
    73. Riccardo De Blasis & Alexander Webb, 2022. "Arbitrage, contract design, and market structure in Bitcoin futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(3), pages 492-524, March.
    74. Aurelio F. Bariviera & Ignasi Merediz-Sol`a, 2020. "Where do we stand in cryptocurrencies economic research? A survey based on hybrid analysis," Papers 2003.09723, arXiv.org.
    75. Müller, Fernanda Maria & Santos, Samuel Solgon & Gössling, Thalles Weber & Righi, Marcelo Brutti, 2022. "Comparison of risk forecasts for cryptocurrencies: A focus on Range Value at Risk," Finance Research Letters, Elsevier, vol. 48(C).
    76. Naeem, Muhammad & Tiwari, Aviral Kumar & Mubashra, Sana & Shahbaz, Muhammad, 2019. "Modeling volatility of precious metals markets by using regime-switching GARCH models," Resources Policy, Elsevier, vol. 64(C).
    77. Fantazzini, Dean, 2023. "Assessing the Credit Risk of Crypto-Assets Using Daily Range Volatility Models," MPRA Paper 117141, University Library of Munich, Germany.
    78. Jens Klose, 2021. "Cryptocurrencies and Gold - Similarities and Differences," MAGKS Papers on Economics 202128, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    79. Ma, Yechi & Ahmad, Ferhana & Liu, Miao & Wang, Zilong, 2020. "Portfolio optimization in the era of digital financialization using cryptocurrencies," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    80. Darko Vukovic & Moinak Maiti & Zoran Grubisic & Elena M. Grigorieva & Michael Frömmel, 2021. "COVID-19 Pandemic: Is the Crypto Market a Safe Haven? The Impact of the First Wave," Sustainability, MDPI, vol. 13(15), pages 1-17, July.
    81. Cristina Chinazzo & Vahidin Jeleskovic, 2024. "Forecasting Bitcoin Volatility: A Comparative Analysis of Volatility Approaches," Papers 2401.02049, arXiv.org.
    82. Grobys, Klaus & Junttila, Juha, 2021. "Speculation and lottery-like demand in cryptocurrency markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 71(C).
    83. Bedi, Prateek & Nashier, Tripti, 2020. "On the investment credentials of Bitcoin: A cross-currency perspective," Research in International Business and Finance, Elsevier, vol. 51(C).
    84. Bucci, Andrea & Palomba, Giulio & Rossi, Eduardo, 2023. "The role of uncertainty in forecasting volatility comovements across stock markets," Economic Modelling, Elsevier, vol. 125(C).
    85. Sabah, Nasim, 2020. "Cryptocurrency accepting venues, investor attention, and volatility," Finance Research Letters, Elsevier, vol. 36(C).
    86. Tetsuya Takaishi, 2021. "Time-varying properties of asymmetric volatility and multifractality in Bitcoin," Papers 2102.07425, arXiv.org.
    87. Bourghelle, David & Jawadi, Fredj & Rozin, Philippe, 2022. "Do collective emotions drive bitcoin volatility? A triple regime-switching vector approach," Journal of Economic Behavior & Organization, Elsevier, vol. 196(C), pages 294-306.
    88. Ahmed M. Khedr & Ifra Arif & Pravija Raj P V & Magdi El‐Bannany & Saadat M. Alhashmi & Meenu Sreedharan, 2021. "Cryptocurrency price prediction using traditional statistical and machine‐learning techniques: A survey," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 28(1), pages 3-34, January.
    89. Chaim, Pedro & Laurini, Márcio P., 2019. "Nonlinear dependence in cryptocurrency markets," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 32-47.
    90. Constandina Koki & Stefanos Leonardos & Georgios Piliouras, 2019. "A Peek into the Unobservable: Hidden States and Bayesian Inference for the Bitcoin and Ether Price Series," Papers 1909.10957, arXiv.org, revised Jul 2021.
    91. Liu, Yue & Sun, Huaping & Zhang, Jijian & Taghizadeh-Hesary, Farhad, 2020. "Detection of volatility regime-switching for crude oil price modeling and forecasting," Resources Policy, Elsevier, vol. 69(C).
    92. 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.
    93. Khanh Hoang & Cuong C. Nguyen & Kongchheng Poch & Thang X. Nguyen, 2020. "Does Bitcoin Hedge Commodity Uncertainty?," JRFM, MDPI, vol. 13(6), pages 1-14, June.
    94. Olofsson, Petter & Råholm, Anna & Uddin, Gazi Salah & Troster, Victor & Kang, Sang Hoon, 2021. "Ethical and unethical investments under extreme market conditions," International Review of Financial Analysis, Elsevier, vol. 78(C).
    95. Gao, Lingbo & Ye, Wuyi & Guo, Ranran, 2022. "Jointly forecasting the value-at-risk and expected shortfall of Bitcoin with a regime-switching CAViaR model," Finance Research Letters, Elsevier, vol. 48(C).
    96. Dora Almeida & Andreia Dionísio & Isabel Vieira & Paulo Ferreira, 2022. "Uncertainty and Risk in the Cryptocurrency Market," JRFM, MDPI, vol. 15(11), pages 1-17, November.
    97. Walther, Thomas & Klein, Tony & Bouri, Elie, 2019. "Exogenous drivers of Bitcoin and Cryptocurrency volatility – A mixed data sampling approach to forecasting," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 63(C).
    98. Jiqian Wang & Feng Ma & Elie Bouri & Yangli Guo, 2023. "Which factors drive Bitcoin volatility: Macroeconomic, technical, or both?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 970-988, July.
    99. Mawuli Segnon & Stelios Bekiros, 2019. "Forecasting Volatility in Cryptocurrency Markets," CQE Working Papers 7919, Center for Quantitative Economics (CQE), University of Muenster.
    100. Walid Chkili, 2021. "Modeling Bitcoin price volatility: long memory vs Markov switching," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 11(3), pages 433-448, September.
    101. Semeyutin, Artur & O’Neill, Robert, 2019. "A brief survey on the choice of parameters for: “Kernel density estimation for time series data”," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    102. Constandina Koki & Stefanos Leonardos & Georgios Piliouras, 2020. "Exploring the Predictability of Cryptocurrencies via Bayesian Hidden Markov Models," Papers 2011.03741, arXiv.org, revised Dec 2020.

  5. Ardia, David & Bluteau, Keven & Boudt, Kris, 2019. "Questioning the news about economic growth: Sparse forecasting using thousands of news-based sentiment values," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1370-1386.

    Cited by:

    1. Nyman, Rickard & Kapadia, Sujit & Tuckett, David & Gregory, David & Ormerod, Paul & Smith, Robert, 2018. "News and narratives in financial systems: exploiting big data for systemic risk assessment," Bank of England working papers 704, Bank of England.
    2. Paul Hubert & Fabien Labondance, 2019. "Central bank tone and the dispersion of views within monetary policy committees," Working Papers hal-03403256, HAL.
    3. Gerardin Mathilde, & Ranvier Martial., 2021. "Enrichment of the Banque de France’s monthly business survey: lessons from textual analysis of business leaders’ comments," Working papers 821, Banque de France.
    4. Deimante Teresiene & Greta Keliuotyte-Staniuleniene & Yiyi Liao & Rasa Kanapickiene & Ruihui Pu & Siyan Hu & Xiao-Guang Yue, 2021. "The Impact of the COVID-19 Pandemic on Consumer and Business Confidence Indicators," JRFM, MDPI, vol. 14(4), pages 1-23, April.
    5. Luca Barbaglia & Sergio Consoli & Sebastiano Manzan, 2024. "Forecasting GDP in Europe with textual data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(2), pages 338-355, March.
    6. Saiz, Lorena & Ashwin, Julian & Kalamara, Eleni, 2021. "Nowcasting euro area GDP with news sentiment: a tale of two crises," Working Paper Series 2616, European Central Bank.
    7. Marc Burri & Daniel Kaufmann, 2020. "A daily fever curve for the Swiss economy," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 156(1), pages 1-11, December.
    8. Ksenia Yakovleva, 2018. "Text Mining-based Economic Activity Estimation," Russian Journal of Money and Finance, Bank of Russia, vol. 77(4), pages 26-41, December.
    9. Ardia, David & Bluteau, Keven & Kassem, Alaa, 2021. "A century of Economic Policy Uncertainty through the French–Canadian lens," Economics Letters, Elsevier, vol. 205(C).
    10. Yuting Chen & Don Bredin & Valerio Potì & Roman Matkovskyy, 2022. "COVID risk narratives: a computational linguistic approach to the econometric identification of narrative risk during a pandemic," Digital Finance, Springer, vol. 4(1), pages 17-61, March.
    11. Diana Gabrielyan & Lenno Uusküla, 2022. "Inflation Expectations And Consumption With Machine Learning," University of Tartu - Faculty of Economics and Business Administration Working Paper Series 142, Faculty of Economics and Business Administration, University of Tartu (Estonia).
    12. Hubert, Paul & Labondance, Fabien, 2021. "The signaling effects of central bank tone," European Economic Review, Elsevier, vol. 133(C).
    13. Jon Ellingsen & Vegard H. Larsen & Leif Anders Thorsrud, 2020. "News media vs. FRED-MD for macroeconomic forecasting," Working Papers No 08/2020, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    14. Massimo Ferrari Minesso & Laura Lebastard & Helena Mezo, 2023. "Text-Based Recession Probabilities," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 71(2), pages 415-438, June.
    15. Andres Algaba & David Ardia & Keven Bluteau & Samuel Borms & Kris Boudt, 2020. "Econometrics Meets Sentiment: An Overview Of Methodology And Applications," Journal of Economic Surveys, Wiley Blackwell, vol. 34(3), pages 512-547, July.
    16. Valentina Aprigliano & Simone Emiliozzi & Gabriele Guaitoli & Andrea Luciani & Juri Marcucci & Libero Monteforte, 2021. "The power of text-based indicators in forecasting the Italian economic activity," Temi di discussione (Economic working papers) 1321, Bank of Italy, Economic Research and International Relations Area.
    17. Raffaele Mattera & Michelangelo Misuraca & Maria Spano & Germana Scepi, 2023. "Mixed frequency composite indicators for measuring public sentiment in the EU," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(3), pages 2357-2382, June.
    18. Simionescu, Mihaela, 2022. "Econometrics of sentiments- sentometrics and machine learning: The improvement of inflation predictions in Romania using sentiment analysis," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    19. Ricardo P. Masini & Marcelo C. Medeiros & Eduardo F. Mendes, 2023. "Machine learning advances for time series forecasting," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 76-111, February.
    20. Shrub, Yuliya & Rieger, Jonas & Müller, Henrik & Jentsch, Carsten, 2022. "Text data rule - don't they? A study on the (additional) information of Handelsblatt data for nowcasting German GDP in comparison to established economic indicators," Ruhr Economic Papers 964, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    21. Erik Andres-Escayola & Corinna Ghirelli & Luis Molina & Javier J. Pérez & Elena Vidal, 2022. "Using newspapers for textual indicators: which and how many?," Working Papers 2235, Banco de España.
    22. Zhang, Yulian & Hamori, Shigeyuki, 2021. "Do news sentiment and the economic uncertainty caused by public health events impact macroeconomic indicators? Evidence from a TVP-VAR decomposition approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 82(C), pages 145-162.
    23. Afanasyev, Dmitriy O. & Fedorova, Elena & Ledyaeva, Svetlana, 2021. "Strength of words: Donald Trump's tweets, sanctions and Russia's ruble," Journal of Economic Behavior & Organization, Elsevier, vol. 184(C), pages 253-277.
    24. Kalamara, Eleni & Turrell, Arthur & Redl, Chris & Kapetanios, George & Kapadia, Sujit, 2020. "Making text count: economic forecasting using newspaper text," Bank of England working papers 865, Bank of England.
    25. Dooruj Rambaccussing & Craig Menzies & Andrzej Kwiatkowski, 2022. "Look who’s Talking: Individual Committee members’ impact on inflation expectations," Dundee Discussion Papers in Economics 305, Economic Studies, University of Dundee.
    26. Stolbov, Mikhail & Shchepeleva, Maria & Karminsky, Alexander, 2022. "When central bank research meets Google search: A sentiment index of global financial stress," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    27. Dorinth van Dijk & Jasper de Winter, 2023. "Nowcasting GDP using tone-adjusted time varying news topics: Evidence from the financial press," Working Papers 766, DNB.
    28. Bai, Xiwen & Lam, Jasmine Siu Lee & Jakher, Astha, 2021. "Shipping sentiment and the dry bulk shipping freight market: New evidence from newspaper coverage," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 155(C).
    29. Mikhaylov, Dmitry, 2023. "Macroeconomic Forecasting with the Use of News Data," Working Papers w20220250, Russian Presidential Academy of National Economy and Public Administration.
    30. Elena Shulyak, 2022. "Macroeconomic Forecasting Using Data from Social Media," Russian Journal of Money and Finance, Bank of Russia, vol. 81(4), pages 86-112, December.
    31. Jon Ellingsen & Vegard H. Larsen & Leif Anders Thorsrud, 2022. "News media versus FRED‐MD for macroeconomic forecasting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(1), pages 63-81, January.
    32. Aromi, J. Daniel & Clements, Adam, 2021. "Facial expressions and the business cycle," Economic Modelling, Elsevier, vol. 102(C).
    33. Claveria, Oscar & Monte, Enric & Torra, Salvador, 2020. "Economic forecasting with evolved confidence indicators," Economic Modelling, Elsevier, vol. 93(C), pages 576-585.
    34. Oscar Claveria & Enric Monte & Salvador Torra, 2021. ""Nowcasting and forecasting GDP growth with machine-learning sentiment indicators"," IREA Working Papers 202103, University of Barcelona, Research Institute of Applied Economics, revised Feb 2021.
    35. Park, Eunhye & Park, Jinah & Hu, Mingming, 2021. "Tourism demand forecasting with online news data mining," Annals of Tourism Research, Elsevier, vol. 90(C).

  6. Ardia, David & Bluteau, Keven & Boudt, Kris & Catania, Leopoldo, 2018. "Forecasting risk with Markov-switching GARCH models:A large-scale performance study," International Journal of Forecasting, Elsevier, vol. 34(4), pages 733-747.

    Cited by:

    1. Achraf Ghorbel & Ahmed Jeribi, 2021. "Volatility spillovers and contagion between energy sector and financial assets during COVID-19 crisis period," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 11(3), pages 449-467, September.
    2. Panagiotidis, Theodore & Papapanagiotou, Georgios & Stengos, Thanasis, 2022. "On the volatility of cryptocurrencies," Research in International Business and Finance, Elsevier, vol. 62(C).
    3. Carlos Trucíos & James W. Taylor, 2023. "A comparison of methods for forecasting value at risk and expected shortfall of cryptocurrencies," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 989-1007, July.
    4. Vahidin Jeleskovic & Claudio Latini & Zahid I. Younas & Mamdouh A. S. Al-Faryan, 2023. "Optimization of portfolios with cryptocurrencies: Markowitz and GARCH-Copula model approach," Papers 2401.00507, arXiv.org.
    5. R. Rajesh, 2023. "Grey Markov Models for Predicting the Social Sustainability Performances of Firms," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 168(1), pages 297-351, August.
    6. Caporale, Guglielmo Maria & Kang, Woo-Young & Spagnolo, Fabio & Spagnolo, Nicola, 2020. "Non-linearities, cyber attacks and cryptocurrencies," Finance Research Letters, Elsevier, vol. 32(C).
    7. Yu, Xing & Li, Yanyan & Lu, Junli & Shen, Xilin, 2023. "Futures hedging in crude oil markets: A trade-off between risk and return," Resources Policy, Elsevier, vol. 80(C).
    8. Toshiyuki Yam awake & Joseph Sheely & Roberto Serrano & Jiro Hodoshima, 2022. "Comparative Performance of Cryptocurrencies through the Aumann and Serrano Economic Index of Riskiness," Working Papers 2022-007, Brown University, Department of Economics.
    9. Caporale, Guglielmo Maria & Zekokh, Timur, 2019. "Modelling volatility of cryptocurrencies using Markov-Switching GARCH models," Research in International Business and Finance, Elsevier, vol. 48(C), pages 143-155.
    10. Hasanov, Akram Shavkatovich & Shaiban, Mohammed Sharaf & Al-Freedi, Ajab, 2020. "Forecasting volatility in the petroleum futures markets: A re-examination and extension," Energy Economics, Elsevier, vol. 86(C).
    11. Ataurima Arellano, Miguel & Rodríguez, Gabriel, 2020. "Empirical modeling of high-income and emerging stock and Forex market return volatility using Markov-switching GARCH models," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    12. Halkos, George & Tzirivis, Apostolos, 2018. "Effective energy commodities’ risk management: Econometric modeling of price volatility," MPRA Paper 90781, University Library of Munich, Germany.
    13. 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.
    14. Amaro, Raphael & Pinho, Carlos, 2022. "Energy commodities: A study on model selection for estimating Value-at-Risk," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 68, pages 5-27.
    15. Ardia, David & Bluteau, Keven & Rüede, Maxime, 2019. "Regime changes in Bitcoin GARCH volatility dynamics," Finance Research Letters, Elsevier, vol. 29(C), pages 266-271.
    16. Urom, Christian & Onwuka, Kevin O. & Uma, Kalu E. & Yuni, Denis N., 2020. "Regime dependent effects and cyclical volatility spillover between crude oil price movements and stock returns," International Economics, Elsevier, vol. 161(C), pages 10-29.
    17. Abdulkadir Kaya & İkram Yusuf Yarbaşı, 2021. "Forecasting of Volatility in Stock Exchange Markets by MS-GARCH Approach: An Application of Borsa Istanbul," Journal of Research in Economics, Politics & Finance, Ersan ERSOY, vol. 6(1), pages 16-35.
    18. Arian, Hamid & Moghimi, Mehrdad & Tabatabaei, Ehsan & Zamani, Shiva, 2022. "Encoded Value-at-Risk: A machine learning approach for portfolio risk measurement," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 202(C), pages 500-525.
    19. Nikolaos A. Kyriazis, 2021. "A Survey on Volatility Fluctuations in the Decentralized Cryptocurrency Financial Assets," JRFM, MDPI, vol. 14(7), pages 1-46, June.
    20. Leandro Maciel, 2021. "Cryptocurrencies value‐at‐risk and expected shortfall: Do regime‐switching volatility models improve forecasting?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4840-4855, July.
    21. Scarcioffolo, Alexandre R. & Etienne, Xiaoli L., 2021. "Regime-switching energy price volatility: The role of economic policy uncertainty," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 336-356.
    22. Ibrahim, Omar, 2019. "Modelling Risk on the Egyptian Stock Market: Evidence from a Markov-Regime Switching GARCH Process," MPRA Paper 98091, University Library of Munich, Germany.
    23. Hotta, Luiz Koodi & Trucíos Maza, Carlos César & Pereira, Pedro L. Valls & Zevallos Herencia, Mauricio Henrique, 2024. "Forecasting VaR and ES through Markov-switching GARCH models: does the specication matter?," Textos para discussão 567, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    24. Guo, Xiaozhu & Huang, Yisu & Liang, Chao & Umar, Muhammad, 2022. "Forecasting volatility of EUA futures: New evidence," Energy Economics, Elsevier, vol. 110(C).
    25. Wu, Chuanzhen, 2021. "Window effect with Markov-switching GARCH model in cryptocurrency market," Chaos, Solitons & Fractals, Elsevier, vol. 146(C).
    26. Oscar V. De la Torre-Torres & Francisco Venegas-Martínez & Mᵃ Isabel Martínez-Torre-Enciso, 2021. "Enhancing Portfolio Performance and VIX Futures Trading Timing with Markov-Switching GARCH Models," Mathematics, MDPI, vol. 9(2), pages 1-22, January.
    27. Leopoldo Catania & Mads Sandholdt, 2019. "Bitcoin at High Frequency," JRFM, MDPI, vol. 12(1), pages 1-20, February.
    28. Lu-Tao Zhao & Li-Na Liu & Zi-Jie Wang & Ling-Yun He, 2019. "Forecasting Oil Price Volatility in the Era of Big Data: A Text Mining for VaR Approach," Sustainability, MDPI, vol. 11(14), pages 1-20, July.
    29. John Weirstrass Muteba Mwamba & Sutene Mwambetania Mwambi, 2021. "Assessing Market Risk in BRICS and Oil Markets: An Application of Markov Switching and Vine Copula," IJFS, MDPI, vol. 9(2), pages 1-22, May.
    30. Halkos, George & Tsirivis, Apostolos, 2019. "Using Value-at-Risk for effective energy portfolio risk management," MPRA Paper 91674, University Library of Munich, Germany.
    31. Katleho Makatjane & Ntebogang Moroke, 2021. "Predicting Extreme Daily Regime Shifts in Financial Time Series Exchange/Johannesburg Stock Exchange—All Share Index," IJFS, MDPI, vol. 9(2), pages 1-18, March.
    32. Oscar V. De la Torre-Torres & Evaristo Galeana-Figueroa & José Álvarez-García, 2019. "A Test of Using Markov-Switching GARCH Models in Oil and Natural Gas Trading," Energies, MDPI, vol. 13(1), pages 1-24, December.
    33. Naeem, Muhammad & Tiwari, Aviral Kumar & Mubashra, Sana & Shahbaz, Muhammad, 2019. "Modeling volatility of precious metals markets by using regime-switching GARCH models," Resources Policy, Elsevier, vol. 64(C).
    34. Abdollahi, Hooman, 2020. "A novel hybrid model for forecasting crude oil price based on time series decomposition," Applied Energy, Elsevier, vol. 267(C).
    35. Makridakis, Spyros & Spiliotis, Evangelos & Assimakopoulos, Vassilios, 2020. "The M4 Competition: 100,000 time series and 61 forecasting methods," International Journal of Forecasting, Elsevier, vol. 36(1), pages 54-74.
    36. Abdessamad Ouchen, 2022. "Is the ESG portfolio less turbulent than a market benchmark portfolio?," Risk Management, Palgrave Macmillan, vol. 24(1), pages 1-33, March.
    37. Rewat Khanthaporn, 2022. "Analysis of Nonlinear Comovement of Benchmark Thai Government Bond Yields," PIER Discussion Papers 183, Puey Ungphakorn Institute for Economic Research.
    38. Chon, Sora & Kim, Jaeho, 2021. "Does the Financial Leverage Effect Depend on Volatility Regimes?," Finance Research Letters, Elsevier, vol. 39(C).
    39. Olofsson, Petter & Råholm, Anna & Uddin, Gazi Salah & Troster, Victor & Kang, Sang Hoon, 2021. "Ethical and unethical investments under extreme market conditions," International Review of Financial Analysis, Elsevier, vol. 78(C).
    40. 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).

  7. Ardia David & Bluteau Keven & Hoogerheide Lennart F., 2018. "Methods for Computing Numerical Standard Errors: Review and Application to Value-at-Risk Estimation," Journal of Time Series Econometrics, De Gruyter, vol. 10(2), pages 1-9, July.

    Cited by:

    1. Federico Bassetti & Giulia Carallo & Roberto Casarin, 2022. "First-order integer-valued autoregressive processes with Generalized Katz innovations," Papers 2202.02029, arXiv.org.

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