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Trading frequency and volatility clustering

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  • Xue, Yi
  • Gençay, Ramazan

Abstract

Volatility clustering, with autocorrelations of the hyperbolic decay rate, is unquestionably one of the most important stylized facts of financial time series. This paper presents a market microstructure model that is able to generate volatility clustering with hyperbolically decaying autocorrelations via traders with multiple trading frequencies, using Bayesian information updates in an incomplete market. The model illustrates that signal extraction, which is induced by multiple trading frequencies, can increase the persistence of the volatility of returns. Furthermore, we show that the volatility of the underlying time series of returns varies greatly with the number of traders in the market.

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  • Xue, Yi & Gençay, Ramazan, 2012. "Trading frequency and volatility clustering," Journal of Banking & Finance, Elsevier, vol. 36(3), pages 760-773.
    • Handle: RePEc:eee:jbfina:v:36:y:2012:i:3:p:760-773
    DOI: 10.1016/j.jbankfin.2011.09.008
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    1. Brock, William A & LeBaron, Blake D, 1996. "A Dynamic Structural Model for Stock Return Volatility and Trading Volume," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 94-110, February.
    2. Timmermann, Allan, 2001. "Structural Breaks, Incomplete Information, and Stock Prices," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(3), pages 299-314, July.
    3. Haan, Wouter J. den & Spear, Scott A., 1998. "Volatility clustering in real interest rates Theory and evidence," Journal of Monetary Economics, Elsevier, vol. 41(3), pages 431-453, May.
    4. Harrison Hong & José Scheinkman & Wei Xiong, 2006. "Asset Float and Speculative Bubbles," Journal of Finance, American Finance Association, vol. 61(3), pages 1073-1117, June.
    5. Gemmill, Gordon, 1996. "Transparency and Liquidity: A Study of Block Trades on the London Stock Exchange under Different Publication Rules," Journal of Finance, American Finance Association, vol. 51(5), pages 1765-1790, December.
    6. Brock, William A. & Hommes, Cars H. & Wagener, Florian O. O., 2005. "Evolutionary dynamics in markets with many trader types," Journal of Mathematical Economics, Elsevier, vol. 41(1-2), pages 7-42, February.
    7. Liu, Ming, 2000. "Modeling long memory in stock market volatility," Journal of Econometrics, Elsevier, vol. 99(1), pages 139-171, November.
    8. Bollerslev, Tim & Ole Mikkelsen, Hans, 1999. "Long-term equity anticipation securities and stock market volatility dynamics," Journal of Econometrics, Elsevier, vol. 92(1), pages 75-99, September.
    9. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    10. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.
    11. Thierry Chauveau & Alexander Subbotin, 2010. "Price Dynamics in Market with Heterogeneous Investment Horizons and Boundedly Rational Traders," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00497427, HAL.
    12. Cabrales, Antonio & Hoshi, Takeo, 1996. "Heterogeneous beliefs, wealth accumulation, and asset price dynamics," Journal of Economic Dynamics and Control, Elsevier, vol. 20(6-7), pages 1073-1100.
    13. Alexander Subbotin & Thierry Chauveau, 2010. "Price Dynamics in a Market with Heterogeneous Investment Horizons and Boundedly Rational Traders," Documents de travail du Centre d'Economie de la Sorbonne 10048, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    14. Granger, Clive W.J. & Machina, Mark J., 2006. "Structural attribution of observed volatility clustering," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 15-29.
    15. Hommes, Cars H., 2006. "Heterogeneous Agent Models in Economics and Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 23, pages 1109-1186, Elsevier.
    16. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    17. de Fontnouvelle, Patrick, 2000. "Information Dynamics In Financial Markets," Macroeconomic Dynamics, Cambridge University Press, vol. 4(2), pages 139-169, June.
    18. Bollerslev, Tim & Ole Mikkelsen, Hans, 1996. "Modeling and pricing long memory in stock market volatility," Journal of Econometrics, Elsevier, vol. 73(1), pages 151-184, July.
    19. Jensen, Gerald R. & Moorman, Theodore, 2010. "Inter-temporal variation in the illiquidity premium," Journal of Financial Economics, Elsevier, vol. 98(2), pages 338-358, November.
    20. Robert F. Engle, 2000. "The Econometrics of Ultra-High Frequency Data," Econometrica, Econometric Society, vol. 68(1), pages 1-22, January.
    21. Chung, Kee H. & Li, Mingsheng & McInish, Thomas H., 2005. "Information-based trading, price impact of trades, and trade autocorrelation," Journal of Banking & Finance, Elsevier, vol. 29(7), pages 1645-1669, July.
    22. Benoit Mandelbrot, 2015. "The Variation of Certain Speculative Prices," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 3, pages 39-78, World Scientific Publishing Co. Pte. Ltd..
    23. Gençay, Ramazan & Dacorogna, Michel & Muller, Ulrich A. & Pictet, Olivier & Olsen, Richard, 2001. "An Introduction to High-Frequency Finance," Elsevier Monographs, Elsevier, edition 1, number 9780122796715.
    24. Thierry Chauveau & Alexander Subbotin, 2010. "Price Dynamics in Market with Heterogeneous Investment Horizons and Boundedly Rational Traders," Post-Print halshs-00497427, HAL.
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    Cited by:

    1. Aitken, Michael & Cumming, Douglas & Zhan, Feng, 2015. "High frequency trading and end-of-day price dislocation," Journal of Banking & Finance, Elsevier, vol. 59(C), pages 330-349.
    2. Batten, Jonathan A. & Kinateder, Harald & Wagner, Niklas, 2014. "Multifractality and value-at-risk forecasting of exchange rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 401(C), pages 71-81.
    3. Alessio Brini & Giacomo Toscano, 2024. "SpotV2Net: Multivariate Intraday Spot Volatility Forecasting via Vol-of-Vol-Informed Graph Attention Networks," Papers 2401.06249, arXiv.org, revised Aug 2024.
    4. Lorraine Muguto & Paul-Francois Muzindutsi, 2022. "A Comparative Analysis of the Nature of Stock Return Volatility in BRICS and G7 Markets," JRFM, MDPI, vol. 15(2), pages 1-27, February.
    5. Xue, Yi & Gençay, Ramazan, 2012. "Hierarchical information and the rate of information diffusion," Journal of Economic Dynamics and Control, Elsevier, vol. 36(9), pages 1372-1401.
    6. Nikitopoulos, Christina Sklibosios & Thomas, Alice Carole & Wang, Jianxin, 2023. "The economic impact of daily volatility persistence on energy markets," Journal of Commodity Markets, Elsevier, vol. 30(C).
    7. Borgards, Oliver & Czudaj, Robert L., 2021. "Features of overreactions in the cryptocurrency market," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 31-48.
    8. Wang, Jianxin, 2022. "Market distraction and near-zero daily volatility persistence," International Review of Financial Analysis, Elsevier, vol. 80(C).
    9. Chen, Pei-Fen & Zeng, Jhih-Hong, 2014. "Asymmetric effects of households’ financial participation on banking diversification," Journal of Financial Stability, Elsevier, vol. 13(C), pages 18-29.
    10. Zhao, Xiaojun & Zhang, Na & Zhang, Yali & Xu, Chao & Shang, Pengjian, 2024. "Equity markets volatility clustering: A multiscale analysis of intraday and overnight returns," Journal of Empirical Finance, Elsevier, vol. 77(C).
    11. Christopher M Wray & Steven R Bishop, 2016. "A Financial Market Model Incorporating Herd Behaviour," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-28, March.
    12. Cao, Guangxi & Zhang, Minjia & Li, Qingchen, 2017. "Volatility-constrained multifractal detrended cross-correlation analysis: Cross-correlation among Mainland China, US, and Hong Kong stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 472(C), pages 67-76.

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    More about this item

    Keywords

    Trading frequency; Volatility clustering; Signal extraction; Hyperbolic decay;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • D43 - Microeconomics - - Market Structure, Pricing, and Design - - - Oligopoly and Other Forms of Market Imperfection
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design

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