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Forecasting intraday volatility in the US equity market. Multiplicative component GARCH

Citations

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Cited by:

  1. Leschinski, Christian, 2017. "On the memory of products of long range dependent time series," Economics Letters, Elsevier, vol. 153(C), pages 72-76.
  2. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107630024, January.
  3. Jian, Zhihong & Wu, Shuai & Zhu, Zhican, 2018. "Asymmetric extreme risk spillovers between the Chinese stock market and index futures market: An MV-CAViaR based intraday CoVaR approach," Emerging Markets Review, Elsevier, vol. 37(C), pages 98-113.
  4. Eduardo Rossi & Dean Fantazzini, 2015. "Long Memory and Periodicity in Intraday Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 13(4), pages 922-961.
  5. Nino Antulov-Fantulin & Tian Guo & Fabrizio Lillo, 2021. "Temporal mixture ensemble models for probabilistic forecasting of intraday cryptocurrency volume," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 905-940, December.
  6. Chao Zhang & Yihuang Zhang & Mihai Cucuringu & Zhongmin Qian, 2022. "Volatility forecasting with machine learning and intraday commonality," Papers 2202.08962, arXiv.org, revised Feb 2023.
  7. Xiufeng Yan, 2021. "Autoregressive conditional duration modelling of high frequency data," Papers 2111.02300, arXiv.org.
  8. Eyup Kadioðluu & Guray Kuçukkocaoglu & Saim Kilic, 2015. "Closing price manipulation in Borsa Istanbul and the impact of call auction sessions," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 15(3), pages 213-221, September.
  9. Ito, Ryoko, 2013. "Modeling Dynamic Diurnal Patterns in High-Frequency Financial Data," Cambridge Working Papers in Economics 1315, Faculty of Economics, University of Cambridge.
  10. Heinlein, Reinhold & Legrenzi, Gabriella D. & Mahadeo, Scott M.R., 2021. "Crude oil and stock markets in the COVID-19 crisis: Evidence from oil exporters and importers," The Quarterly Review of Economics and Finance, Elsevier, vol. 82(C), pages 223-229.
  11. Cipollini, Fabrizio & Gallo, Giampiero M., 2019. "Modeling Euro STOXX 50 volatility with common and market-specific components," Econometrics and Statistics, Elsevier, vol. 11(C), pages 22-42.
  12. Christopher Krauss & Klaus Herrmann, 2017. "On the Power and Size Properties of Cointegration Tests in the Light of High-Frequency Stylized Facts," JRFM, MDPI, vol. 10(1), pages 1-24, February.
  13. Behrendt, Simon & Schmidt, Alexander, 2018. "The Twitter myth revisited: Intraday investor sentiment, Twitter activity and individual-level stock return volatility," Journal of Banking & Finance, Elsevier, vol. 96(C), pages 355-367.
  14. Kolokolov, Aleksey & Livieri, Giulia & Pirino, Davide, 2020. "Statistical inferences for price staleness," Journal of Econometrics, Elsevier, vol. 218(1), pages 32-81.
  15. Papaioannou, George P. & Dikaiakos, Christos & Dagoumas, Athanasios S. & Dramountanis, Anargyros & Papaioannou, Panagiotis G., 2018. "Detecting the impact of fundamentals and regulatory reforms on the Greek wholesale electricity market using a SARMAX/GARCH model," Energy, Elsevier, vol. 142(C), pages 1083-1103.
  16. Sobhesh Kumar Agarwalla & Ajay Pandey, 2013. "Expiration‐Day Effects and the Impact of Short Trading Breaks on Intraday Volatility: Evidence from the Indian Market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 33(11), pages 1046-1070, November.
  17. Xiufeng Yan, 2021. "Multiplicative Component GARCH Model of Intraday Volatility," Papers 2111.02376, arXiv.org.
  18. Dunis, Christian & Kellard, Neil M. & Snaith, Stuart, 2013. "Forecasting EUR–USD implied volatility: The case of intraday data," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 4943-4957.
  19. Jonathan R. Stroud & Michael S. Johannes, 2014. "Bayesian Modeling and Forecasting of 24-Hour High-Frequency Volatility," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(508), pages 1368-1384, December.
  20. Kim Christensen & Ulrich Hounyo & Mark Podolskij, 2017. "Is the diurnal pattern sufficient to explain the intraday variation in volatility? A nonparametric assessment," CREATES Research Papers 2017-30, Department of Economics and Business Economics, Aarhus University.
  21. Krauss, Christopher & Herrmann, Klaus & Teis, Stefan, 2015. "On the power and size properties of cointegration tests in the light of high-frequency stylized facts," FAU Discussion Papers in Economics 11/2015, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
  22. Vatter, Thibault & Chavez-Demoulin, Valérie, 2015. "Generalized additive models for conditional dependence structures," Journal of Multivariate Analysis, Elsevier, vol. 141(C), pages 147-167.
  23. Efimova, Olga & Serletis, Apostolos, 2014. "Energy markets volatility modelling using GARCH," Energy Economics, Elsevier, vol. 43(C), pages 264-273.
  24. Jian, Zhihong & Li, Xupei & Zhu, Zhican, 2022. "Extreme risk transmission channels between the stock index futures and spot markets: Evidence from China," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
  25. Dirk G Baur & Thomas Dimpfl, 2012. "State-dependent Momentum in International Stock Markets," Working Paper Series 169, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
  26. Liu, Dehong & Liang, Yucong & Zhang, Lili & Lung, Peter & Ullah, Rizwan, 2021. "Implied volatility forecast and option trading strategy," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 943-954.
  27. Chun, Dohyun & Cho, Hoon & Ryu, Doojin, 2020. "Economic indicators and stock market volatility in an emerging economy," Economic Systems, Elsevier, vol. 44(2).
  28. Eric Ghysels & Julien Idier & Simone Manganelli & Olivier Vergote, 2017. "A High-Frequency assessment of the ECB Securities Markets Programme," Journal of the European Economic Association, European Economic Association, vol. 15(1), pages 218-243.
  29. Agarwalla, Sobhesh Kumar & Pandey, Ajay, 2012. "Whether Cross-Listing, Stock-specific and Market-wide Calendar Events impact Intraday Volatility Dynamics? Evidence from the Indian Stock Market using High-frequency Data," IIMA Working Papers WP2012-11-03, Indian Institute of Management Ahmedabad, Research and Publication Department.
  30. Adam Clements & Joanne Fuller & Vasilios Papalexiou, 2015. "Public news flow in intraday component models for trading activity and volatility," NCER Working Paper Series 106, National Centre for Econometric Research.
  31. Peter Malec, 2016. "A Semiparametric Intraday GARCH Model," Cambridge Working Papers in Economics 1633, Faculty of Economics, University of Cambridge.
  32. Ha, Youngmin & Zhang, Hai, 2020. "Algorithmic trading for online portfolio selection under limited market liquidity," European Journal of Operational Research, Elsevier, vol. 286(3), pages 1033-1051.
  33. Tobias Eckernkemper & Bastian Gribisch, 2021. "Intraday conditional value at risk: A periodic mixed‐frequency generalized autoregressive score approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 883-910, August.
  34. Naimoli, Antonio & Storti, Giuseppe, 2019. "Heterogeneous component multiplicative error models for forecasting trading volumes," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1332-1355.
  35. Hong Li & Shamim Ahmed & Thanaset Chevapatrakul, 2016. "Volatility spillovers across European stock markets around the Brexit referendum," Discussion Papers 2016/06, University of Nottingham, Centre for Finance, Credit and Macroeconomics (CFCM).
  36. Paulo Sergio Ceretta & Alexandre Silva da Costa & Marcelo Brutti Righi & Fernanda Maria Müller, 2013. "A 10 min tick volatility analysis between the Ibovespa and the S&P500," Economics Bulletin, AccessEcon, vol. 33(3), pages 2169-2176.
  37. Zhang, Hanyu & Dufour, Alfonso, 2019. "Modeling intraday volatility of European bond markets: A data filtering application," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 131-146.
  38. Irena Barjav{s}i'c & Nino Antulov-Fantulin, 2020. "Time-varying volatility in Bitcoin market and information flow at minute-level frequency," Papers 2004.00550, arXiv.org, revised Jan 2021.
  39. Wesselhöfft, Niels & Härdle, Wolfgang Karl, 2019. "Estimating low sampling frequency risk measure by high-frequency data," IRTG 1792 Discussion Papers 2019-003, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
  40. Farid, Saqib & Kayani, Ghulam Mujtaba & Naeem, Muhammad Abubakr & Shahzad, Syed Jawad Hussain, 2021. "Intraday volatility transmission among precious metals, energy and stocks during the COVID-19 pandemic," Resources Policy, Elsevier, vol. 72(C).
  41. Herrmann, Klaus & Teis, Stefan & Yu, Weijun, 2014. "Components of intraday volatility and their prediction at different sampling frequencies with application to DAX and BUND futures," FAU Discussion Papers in Economics 15/2014, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
  42. Thibault Vatter & Hau-Tieng Wu & Valérie Chavez-Demoulin & Bin Yu, 2015. "Non-Parametric Estimation of Intraday Spot Volatility: Disentangling Instantaneous Trend and Seasonality," Econometrics, MDPI, vol. 3(4), pages 1-24, December.
  43. Nino Antulov-Fantulin & Tian Guo & Fabrizio Lillo, 2020. "Temporal mixture ensemble models for intraday volume forecasting in cryptocurrency exchange markets," Papers 2005.09356, arXiv.org, revised Dec 2020.
  44. Themistoclis Pantos & Stathis Polyzos & Aggelos Armenatzoglou & Ilias Kampouris, 2019. "Volatility Spillovers in Electricity Markets: Evidence from the United States," International Journal of Energy Economics and Policy, Econjournals, vol. 9(4), pages 131-143.
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