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Modeling and predicting the CBOE market volatility index

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Cited by:

  1. Falik Shear & Badar Nadeem Ashraf & Mohsin Sadaqat, 2020. "Are Investors’ Attention and Uncertainty Aversion the Risk Factors for Stock Markets? International Evidence from the COVID-19 Crisis," Risks, MDPI, vol. 9(1), pages 1-15, December.
  2. Kim Christensen & Mathias Siggaard & Bezirgen Veliyev, 2021. "A machine learning approach to volatility forecasting," CREATES Research Papers 2021-03, Department of Economics and Business Economics, Aarhus University.
  3. Chang, C-L. & Hsieh, T-L. & McAleer, M.J., 2016. "How are VIX and Stock Index ETF Related?," Econometric Institute Research Papers EI2016-07, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  4. Liu, Qing & Wang, Shouyang & Sui, Cong, 2023. "Risk appetite and option prices: Evidence from the Chinese SSE50 options market," International Review of Financial Analysis, Elsevier, vol. 86(C).
  5. Caporale, Guglielmo Maria & Gil-Alana, Luis & Plastun, Alex, 2018. "Is market fear persistent? A long-memory analysis," Finance Research Letters, Elsevier, vol. 27(C), pages 140-147.
  6. Balcilar, Mehmet & Hammoudeh, Shawkat & Toparli, Elif Akay, 2018. "On the risk spillover across the oil market, stock market, and the oil related CDS sectors: A volatility impulse response approach," Energy Economics, Elsevier, vol. 74(C), pages 813-827.
  7. Filip Žikeš & Jozef Baruník, 2016. "Semi-parametric Conditional Quantile Models for Financial Returns and Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 14(1), pages 185-226.
  8. Choe, Geon Ho & Choi, So Eun & Jang, Hyun Jin, 2020. "Assessment of time-varying systemic risk in credit default swap indices: Simultaneity and contagiousness," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
  9. Florian Ielpo & Benoît Sévi, 2014. "Forecasting the density of oil futures," Working Papers 2014-601, Department of Research, Ipag Business School.
  10. Vortelinos, Dimitrios I., 2017. "Forecasting realized volatility: HAR against Principal Components Combining, neural networks and GARCH," Research in International Business and Finance, Elsevier, vol. 39(PB), pages 824-839.
  11. Chia-Lin Chang & Tai-Lin Hsieh & Michael McAleer, 2016. "Connecting VIX and Stock Index ETF," Tinbergen Institute Discussion Papers 16-010/III, Tinbergen Institute, revised 23 Jan 2017.
  12. Barletta, Andrea & Santucci de Magistris, Paolo & Violante, Francesco, 2019. "A non-structural investigation of VIX risk neutral density," Journal of Banking & Finance, Elsevier, vol. 99(C), pages 1-20.
  13. Salman Bahoo & Marco Cucculelli & Xhoana Goga & Jasmine Mondolo, 2024. "Artificial intelligence in Finance: a comprehensive review through bibliometric and content analysis," SN Business & Economics, Springer, vol. 4(2), pages 1-46, February.
  14. Fassas, Athanasios P. & Siriopoulos, Costas, 2021. "Implied volatility indices – A review," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 303-329.
  15. João Henrique G. Mazzeu & Gloria González-Rivera & Esther Ruiz & Helena Veiga, 2020. "A bootstrap approach for generalized Autocontour testing Implications for VIX forecast densities," Econometric Reviews, Taylor & Francis Journals, vol. 39(10), pages 971-990, November.
  16. Bartram, Söhnke & Branke, Jürgen & Motahari, Mehrshad, 2020. "Artificial Intelligence in Asset Management," CEPR Discussion Papers 14525, C.E.P.R. Discussion Papers.
  17. Guglielmo Maria Caporale & Luis Gil-Alana & Tommaso Trani, 2018. "Brexit and Uncertainty in Financial Markets," IJFS, MDPI, vol. 6(1), pages 1-9, February.
  18. Liu, Qiang & Guo, Shuxin & Qiao, Gaoxiu, 2015. "VIX forecasting and variance risk premium: A new GARCH approach," The North American Journal of Economics and Finance, Elsevier, vol. 34(C), pages 314-322.
  19. Degiannakis, Stavros & Filis, George & Hassani, Hossein, 2015. "Forecasting implied volatility indices worldwide: A new approach," MPRA Paper 72084, University Library of Munich, Germany.
  20. Andrea Bucci, 2020. "Realized Volatility Forecasting with Neural Networks," Journal of Financial Econometrics, Oxford University Press, vol. 18(3), pages 502-531.
  21. Chune Young Chung & Doojin Ryu & Kainan Wang & Blerina Bela Zykaj, 2018. "Optionable Stocks and Mutual Fund Performance," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(3), pages 390-412, March.
  22. Ballestra, Luca Vincenzo & Guizzardi, Andrea & Palladini, Fabio, 2019. "Forecasting and trading on the VIX futures market: A neural network approach based on open to close returns and coincident indicators," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1250-1262.
  23. Stefano Grassi & Nima Nonejad & Paolo Santucci De Magistris, 2017. "Forecasting With the Standardized Self‐Perturbed Kalman Filter," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(2), pages 318-341, March.
  24. Arindam Banerjee, 2019. "Forecasting of India VIX as a Measure of Sentiment," International Journal of Economics and Financial Issues, Econjournals, vol. 9(3), pages 268-276.
  25. Chen, Bin-xia & Sun, Yan-lin, 2022. "The impact of VIX on China’s financial market: A new perspective based on high-dimensional and time-varying methods," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
  26. Pierre J. Venter & Eben Maré, 2020. "GARCH Generated Volatility Indices of Bitcoin and CRIX," JRFM, MDPI, vol. 13(6), pages 1-15, June.
  27. Troster, Victor & Bouri, Elie & Roubaud, David, 2019. "A quantile regression analysis of flights-to-safety with implied volatilities," Resources Policy, Elsevier, vol. 62(C), pages 482-495.
  28. Buncic, Daniel & Gisler, Katja I.M., 2016. "Global equity market volatility spillovers: A broader role for the United States," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1317-1339.
  29. Wang, Zhenkun & Bouri, Elie & Ferreira, Paulo & Shahzad, Syed Jawad Hussain & Ferrer, Román, 2022. "A grey-based correlation with multi-scale analysis: S&P 500 VIX and individual VIXs of large US company stocks," Finance Research Letters, Elsevier, vol. 48(C).
  30. Andrea Bucci, 2020. "Cholesky–ANN models for predicting multivariate realized volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 865-876, September.
  31. Dicle, Mehmet F. & Levendis, John, 2020. "Historic risk and implied volatility," Global Finance Journal, Elsevier, vol. 45(C).
  32. Massimiliano Caporin & Eduardo Rossi & Paolo Santucci de Magistris, 2011. "Conditional jumps in volatility and their economic determinants," "Marco Fanno" Working Papers 0138, Dipartimento di Scienze Economiche "Marco Fanno".
  33. Jin, Jiayu & Han, Liyan & Xu, Yang, 2022. "Does the SDR stabilize investing in commodities?," International Review of Economics & Finance, Elsevier, vol. 81(C), pages 160-172.
  34. Chun, Dohyun & Cho, Hoon & Ryu, Doojin, 2023. "Discovering the drivers of stock market volatility in a data-rich world," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
  35. Massimiliano Caporin & Eduardo Rossi & Paolo Santucci de Magistris, 2016. "Volatility Jumps and Their Economic Determinants," Journal of Financial Econometrics, Oxford University Press, vol. 14(1), pages 29-80.
  36. Dimos S. Kambouroudis & David G. McMillan & Katerina Tsakou, 2021. "Forecasting realized volatility: The role of implied volatility, leverage effect, overnight returns, and volatility of realized volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(10), pages 1618-1639, October.
  37. Charalampos Stasinakis & Georgios Sermpinis & Konstantinos Theofilatos & Andreas Karathanasopoulos, 2016. "Forecasting US Unemployment with Radial Basis Neural Networks, Kalman Filters and Support Vector Regressions," Computational Economics, Springer;Society for Computational Economics, vol. 47(4), pages 569-587, April.
  38. Chia-Lin Chang & Tai-Lin Hsieh & Michael McAleer, 2018. "Connecting VIX and Stock Index ETF with VAR and Diagonal BEKK," JRFM, MDPI, vol. 11(4), pages 1-25, September.
  39. Han Lin Shang & Yang Yang & Fearghal Kearney, 2019. "Intraday forecasts of a volatility index: functional time series methods with dynamic updating," Annals of Operations Research, Springer, vol. 282(1), pages 331-354, November.
  40. Akhilesh Prasad & Priti Bakhshi, 2022. "Forecasting the Direction of Daily Changes in the India VIX Index Using Machine Learning," JRFM, MDPI, vol. 15(12), pages 1-26, November.
  41. David E Allen & Vince Hooper, 2018. "Generalized Correlation Measures of Causality and Forecasts of the VIX Using Non-Linear Models," Sustainability, MDPI, vol. 10(8), pages 1-15, August.
  42. Gonçalves Mazzeu, Joao Henrique & González-Rivera, Gloria & Ruiz Ortega, Esther & Veiga, Helena, 2016. "A Bootstrap Approach for Generalized Autocontour Testing," DES - Working Papers. Statistics and Econometrics. WS 23457, Universidad Carlos III de Madrid. Departamento de Estadística.
  43. Fei, Tianlun & Liu, Xiaoquan, 2021. "Herding and market volatility," International Review of Financial Analysis, Elsevier, vol. 78(C).
  44. Taylor, Nick, 2019. "Forecasting returns in the VIX futures market," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1193-1210.
  45. Yuru Sun & Worapree Maneesoonthorn & Ruben Loaiza-Maya & Gael M. Martin, 2023. "Optimal probabilistic forecasts for risk management," Papers 2303.01651, arXiv.org.
  46. Fulvio Corsi & Roberto Renò, 2012. "Discrete-Time Volatility Forecasting With Persistent Leverage Effect and the Link With Continuous-Time Volatility Modeling," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(3), pages 368-380, January.
  47. 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.
  48. Bekaert, Geert & Hoerova, Marie, 2014. "The VIX, the variance premium and stock market volatility," Journal of Econometrics, Elsevier, vol. 183(2), pages 181-192.
  49. Song, Wonho & Ryu, Doojin & Webb, Robert I., 2016. "Overseas market shocks and VKOSPI dynamics: A Markov-switching approach," Finance Research Letters, Elsevier, vol. 16(C), pages 275-282.
  50. Tissaoui, Kais, 2019. "Forecasting implied volatility risk indexes: International evidence using Hammerstein-ARX approach," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 232-249.
  51. 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.
  52. Hammoudeh, Shawkat & Liu, Tengdong & Chang, Chia-Lin & McAleer, Michael, 2013. "Risk spillovers in oil-related CDS, stock and credit markets," Energy Economics, Elsevier, vol. 36(C), pages 526-535.
  53. Richard T. Baillie & Dooyeon Cho & Seunghwa Rho, 2023. "Approximating long-memory processes with low-order autoregressions: Implications for modeling realized volatility," Empirical Economics, Springer, vol. 64(6), pages 2911-2937, June.
  54. Ji, Qiang & Fan, Ying, 2016. "Modelling the joint dynamics of oil prices and investor fear gauge," Research in International Business and Finance, Elsevier, vol. 37(C), pages 242-251.
  55. Konstantinidi, Eirini & Skiadopoulos, George & Tzagkaraki, Emilia, 2008. "Can the evolution of implied volatility be forecasted? Evidence from European and US implied volatility indices," Journal of Banking & Finance, Elsevier, vol. 32(11), pages 2401-2411, November.
  56. Cheng, Mingmian & Swanson, Norman R. & Yang, Xiye, 2021. "Forecasting volatility using double shrinkage methods," Journal of Empirical Finance, Elsevier, vol. 62(C), pages 46-61.
  57. Carlos Henrique Dias Cordeiro de Castro & Fernando Antonio Lucena Aiube, 2023. "Forecasting inflation time series using score‐driven dynamic models and combination methods: The case of Brazil," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 369-401, March.
  58. Xiao, Jihong & Wang, Yudong, 2022. "Good oil volatility, bad oil volatility, and stock return predictability," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 953-966.
  59. Qadan, Mahmoud & Jacob, Maram, 2022. "The value premium and investors' appetite for risk," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 194-219.
  60. Shengli Chen & Zili Zhang, 2019. "Forecasting Implied Volatility Smile Surface via Deep Learning and Attention Mechanism," Papers 1912.11059, arXiv.org.
  61. Anupam Dutta & Debojyoti Das, 2022. "Forecasting realized volatility: New evidence from time‐varying jumps in VIX," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(12), pages 2165-2189, December.
  62. Degiannakis, Stavros & Filis, George, 2017. "Forecasting oil price realized volatility using information channels from other asset classes," Journal of International Money and Finance, Elsevier, vol. 76(C), pages 28-49.
  63. Krauss, Christopher & Do, Xuan Anh & Huck, Nicolas, 2017. "Deep neural networks, gradient-boosted trees, random forests: Statistical arbitrage on the S&P 500," European Journal of Operational Research, Elsevier, vol. 259(2), pages 689-702.
  64. 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.
  65. Caporale, Guglielmo Maria & Gil-Alana, Luis A. & Tripathy, Trilochan, 2020. "Volatility persistence in the Russian stock market," Finance Research Letters, Elsevier, vol. 32(C).
  66. Holger Fink & Yulia Klimova & Claudia Czado & Jakob Stober, 2016. "Regime switching vine copula models for global equity and volatility indices," Papers 1604.05598, arXiv.org.
  67. Psaradellis, Ioannis & Sermpinis, Georgios, 2016. "Modelling and trading the U.S. implied volatility indices. Evidence from the VIX, VXN and VXD indices," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1268-1283.
  68. Geng, Jiang-Bo & Chen, Fu-Rui & Ji, Qiang & Liu, Bing-Yue, 2021. "Network connectedness between natural gas markets, uncertainty and stock markets," Energy Economics, Elsevier, vol. 95(C).
  69. Huck, Nicolas, 2019. "Large data sets and machine learning: Applications to statistical arbitrage," European Journal of Operational Research, Elsevier, vol. 278(1), pages 330-342.
  70. Lehrer, Steven & Xie, Tian & Zhang, Xinyu, 2021. "Social media sentiment, model uncertainty, and volatility forecasting," Economic Modelling, Elsevier, vol. 102(C).
  71. Ioannis Dokas & Georgios Oikonomou & Minas Panagiotidis & Eleftherios Spyromitros, 2023. "Macroeconomic and Uncertainty Shocks’ Effects on Energy Prices: A Comprehensive Literature Review," Energies, MDPI, vol. 16(3), pages 1-35, February.
  72. Campos, I. & Cortazar, G. & Reyes, T., 2017. "Modeling and predicting oil VIX: Internet search volume versus traditional mariables," Energy Economics, Elsevier, vol. 66(C), pages 194-204.
  73. Lujia Bai & Weichi Wu, 2021. "Detecting long-range dependence for time-varying linear models," Papers 2110.08089, arXiv.org, revised Mar 2023.
  74. Jeng-Bau Lin & Wei Tsai, 2019. "The Relations of Oil Price Change with Fear Gauges in Global Political and Economic Environment," Energies, MDPI, vol. 12(15), pages 1-17, August.
  75. Guglielmo Maria Caporale & Luis A. Gil-Alana & Trilochan Tripathy, 2018. "Persistence in the Russian Stock Market Volatility Indices," CESifo Working Paper Series 7243, CESifo.
  76. Tuncer Yılmaz & Bülent Yıldız, 2022. "Yatırımcıların Risk İştahı Endeksi İle Korku Endeksleri Arasındaki İlişki: Türkiye’de ARDL İle Ampirik Bir Uygulama," Journal of Research in Economics, Politics & Finance, Ersan ERSOY, vol. 7(3), pages 646-676.
  77. Reiter-Gavish, Liron & Qadan, Mahmoud & Yagil, Joseph, 2021. "Financial advice: Who Exactly Follows It?," Research in Economics, Elsevier, vol. 75(3), pages 244-258.
  78. Chen & Jo-Hui & Hussain & Sabbor & Chen & Fu-Ying, 2023. "The Relationship between VIX and Technical Indicator: The Analysis of Shared-Frailty Model," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 13(3), pages 1-5.
  79. Degiannakis, Stavros & Filis, George, 2016. "Forecasting oil price realized volatility: A new approach," MPRA Paper 69105, University Library of Munich, Germany.
  80. Degiannakis, Stavros & Filis, George & Hassani, Hossein, 2018. "Forecasting global stock market implied volatility indices," Journal of Empirical Finance, Elsevier, vol. 46(C), pages 111-129.
  81. Yang, Ke & Tian, Fengping & Chen, Langnan & Li, Steven, 2017. "Realized volatility forecast of agricultural futures using the HAR models with bagging and combination approaches," International Review of Economics & Finance, Elsevier, vol. 49(C), pages 276-291.
  82. 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.
  83. Han, Heejoon & Kutan, Ali M. & Ryu, Doojin, 2015. "Effects of the US stock market return and volatility on the VKOSPI," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 9, pages 1-34.
  84. Filip Žikeš & Jozef Baruník, 2015. "Semi-parametric Conditional Quantile Models for Financial Returns and Realized Volatility," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 14(1), pages 185-226.
  85. Han, Heejoon & Kutan, Ali M. & Ryu, Doojin, 2015. "Modeling and predicting the market volatility index: The case of VKOSPI," Economics Discussion Papers 2015-7, Kiel Institute for the World Economy (IfW Kiel).
  86. 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).
  87. Giovanni Bonaccolto & Massimiliano Caporin, 2016. "The Determinants of Equity Risk and Their Forecasting Implications: A Quantile Regression Perspective," JRFM, MDPI, vol. 9(3), pages 1-25, July.
  88. Bruno Deschamps & Tianlun Fei & Ying Jiang & Xiaoquan Liu, 2022. "Procyclical volatility in Chinese stock markets," Review of Quantitative Finance and Accounting, Springer, vol. 58(3), pages 1117-1144, April.
  89. Wang, Ping & Han, Wei & Huang, Chengcheng & Duong, Duy, 2022. "Forecasting realised volatility from search volume and overnight sentiment: Evidence from China," Research in International Business and Finance, Elsevier, vol. 62(C).
  90. Eric Hillebrand & Marcelo Medeiros, 2010. "The Benefits of Bagging for Forecast Models of Realized Volatility," Econometric Reviews, Taylor & Francis Journals, vol. 29(5-6), pages 571-593.
  91. Ji, Qiang & Liu, Bing-Yue & Nehler, Henrik & Uddin, Gazi Salah, 2018. "Uncertainties and extreme risk spillover in the energy markets: A time-varying copula-based CoVaR approach," Energy Economics, Elsevier, vol. 76(C), pages 115-126.
  92. Bahram Adrangi & Arjun Chatrath & Joseph Macri & Kambiz Raffiee, 2019. "Dynamic Responses of Major Equity Markets to the US Fear Index," JRFM, MDPI, vol. 12(4), pages 1-23, September.
  93. Pham, Linh & Do, Hung Xuan, 2022. "Green bonds and implied volatilities: Dynamic causality, spillovers, and implications for portfolio management," Energy Economics, Elsevier, vol. 112(C).
  94. Jung Park, Yuen & Kutan, Ali M. & Ryu, Doojin, 2019. "The impacts of overseas market shocks on the CDS-option basis," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 622-636.
  95. Degiannakis, Stavros & Filis, George, 2022. "Oil price volatility forecasts: What do investors need to know?," Journal of International Money and Finance, Elsevier, vol. 123(C).
  96. Wang, Xunxiao & Wu, Chongfeng & Xu, Weidong, 2015. "Volatility forecasting: The role of lunch-break returns, overnight returns, trading volume and leverage effects," International Journal of Forecasting, Elsevier, vol. 31(3), pages 609-619.
  97. Erhard Reschenhofer & Manveer Kaur Mangat & Christian Zwatz & Sándor Guzmics, 2020. "Evaluation of current research on stock return predictability," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 334-351, March.
  98. Liu, Min & Lee, Chien-Chiang, 2021. "Capturing the dynamics of the China crude oil futures: Markov switching, co-movement, and volatility forecasting," Energy Economics, Elsevier, vol. 103(C).
  99. Ouandlous, Arav & Barkoulas, John T. & Alhaj-Yaseen, Yaseen, 2018. "Persistence and discontinuity in the VIX dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 113(C), pages 333-344.
  100. Sharma, Aarzoo, 2022. "A comparative analysis of the financialization of commodities during COVID-19 and the global financial crisis using a quantile regression approach," Resources Policy, Elsevier, vol. 78(C).
  101. Holger Fink & Yulia Klimova & Claudia Czado & Jakob Stöber, 2017. "Regime Switching Vine Copula Models for Global Equity and Volatility Indices," Econometrics, MDPI, vol. 5(1), pages 1-38, January.
  102. Leandro Maciel & Fernando Gomide & Rosangela Ballini, 2016. "Evolving Fuzzy-GARCH Approach for Financial Volatility Modeling and Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 48(3), pages 379-398, October.
  103. Uddin, Moshfique & Chowdhury, Anup & Anderson, Keith & Chaudhuri, Kausik, 2021. "The effect of COVID – 19 pandemic on global stock market volatility: Can economic strength help to manage the uncertainty?," Journal of Business Research, Elsevier, vol. 128(C), pages 31-44.
  104. Qadan, Mahmoud & Aharon, David Y., 2019. "How much happiness can we find in the U.S. fear Index?," Finance Research Letters, Elsevier, vol. 30(C), pages 246-258.
  105. Philip Stahl, 2022. "Asymptotic extrapolation of model-free implied variance: exploring structural underestimation in the VIX Index," Review of Derivatives Research, Springer, vol. 25(3), pages 315-339, October.
  106. Iuri H. Ferreira & Marcelo C. Medeiros, 2021. "Modeling and Forecasting Intraday Market Returns: a Machine Learning Approach," Papers 2112.15108, arXiv.org.
  107. Danyan Wen & Mengxi He & Yaojie Zhang & Yudong Wang, 2022. "Forecasting realized volatility of Chinese stock market: A simple but efficient truncated approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 230-251, March.
  108. Smales, L.A., 2016. "Risk-on/Risk-off: Financial market response to investor fear," Finance Research Letters, Elsevier, vol. 17(C), pages 125-134.
  109. Papadamou, Stephanos & Fassas, Athanasios & Kenourgios, Dimitris & Dimitriou, Dimitrios, 2020. "Direct and Indirect Effects of COVID-19 Pandemic on Implied Stock Market Volatility: Evidence from Panel Data Analysis," MPRA Paper 100020, University Library of Munich, Germany.
  110. Curi, Claudia & Murgia, Lucia Milena, 2023. "Forecast Targeting and Financial Stability: Evidence from the European Central Bank and Bank of England," Finance Research Letters, Elsevier, vol. 51(C).
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