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Asymmetric effect of trading volume on realized volatility

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  • Maki, Daiki

Abstract

This study examines the asymmetric effect of trading volume on realized volatility and introduces two new realized volatility models to examine this effect: one model uses asymmetric trading volume variables based on intraday returns, while the other uses asymmetric trading volume variables based on daily returns. These new variables are introduced into the heterogeneous autoregressive models with the leverage effect and realized semivariance. The in-sample estimation results show that the asymmetric trading volume variables are clearly significant. Furthermore, out-of-sample forecasting comparisons indicate that asymmetric trading volume variables increase the forecasting performance of realized volatility. These empirical analyses demonstrate that considering asymmetric trading volume in modeling and forecasting realized volatility is important. This study’s findings provide valuable information for understanding and controlling asset and market risks.

Suggested Citation

  • Maki, Daiki, 2024. "Asymmetric effect of trading volume on realized volatility," International Review of Economics & Finance, Elsevier, vol. 94(C).
    • Handle: RePEc:eee:reveco:v:94:y:2024:i:c:s1059056024003800
    DOI: 10.1016/j.iref.2024.103388
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    1. Eleanor Xu, Xiaoqing & Chen, Peter & Wu, Chunchi, 2006. "Time and dynamic volume-volatility relation," Journal of Banking & Finance, Elsevier, vol. 30(5), pages 1535-1558, May.
    2. Bouteska, Ahmed & Sharif, Taimur & Abedin, Mohammad Zoynul, 2023. "Volatility spillovers and other dynamics between cryptocurrencies and the energy and bond markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 92(C), pages 1-13.
    3. Yaojie Zhang & Yudong Wang & Feng Ma, 2021. "Forecasting US stock market volatility: How to use international volatility information," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 733-768, August.
    4. Wang, Yong & Liu, Shimiao & Abedin, Mohammad Zoynul & Lucey, Brian, 2024. "Volatility spillover and hedging strategies among Chinese carbon, energy, and electricity markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 91(C).
    5. Darrat, Ali F. & Zhong, Maosen & Cheng, Louis T.W., 2007. "Intraday volume and volatility relations with and without public news," Journal of Banking & Finance, Elsevier, vol. 31(9), pages 2711-2729, September.
    6. 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.
    7. Jones, Charles M & Kaul, Gautam & Lipson, Marc L, 1994. "Transactions, Volume, and Volatility," The Review of Financial Studies, Society for Financial Studies, vol. 7(4), pages 631-651.
    8. Peter R. Hansen & Asger Lunde & James M. Nason, 2011. "The Model Confidence Set," Econometrica, Econometric Society, vol. 79(2), pages 453-497, March.
    9. Darolles, Serge & Le Fol, Gaëlle & Mero, Gulten, 2017. "Mixture of distribution hypothesis: Analyzing daily liquidity frictions and information flows," Journal of Econometrics, Elsevier, vol. 201(2), pages 367-383.
    10. Chen, Shengming & Bouteska, Ahmed & Sharif, Taimur & Abedin, Mohammad Zoynul, 2023. "The Russia–Ukraine war and energy market volatility: A novel application of the volatility ratio in the context of natural gas," Resources Policy, Elsevier, vol. 85(PA).
    11. Fulvio Corsi, 2009. "A Simple Approximate Long-Memory Model of Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 7(2), pages 174-196, Spring.
    12. Kao, Erin H. & Fung, Hung-Gay, 2012. "Intraday trading activities and volatility in round-the-clock futures markets," International Review of Economics & Finance, Elsevier, vol. 21(1), pages 195-209.
    13. Xu, Xiaoqing Eleanor & Wu, Chunchi, 1999. "The intraday relation between return volatility, transactions, and volume," International Review of Economics & Finance, Elsevier, vol. 8(4), pages 375-397, November.
    14. Shahzad, Hassan & Duong, Huu Nhan & Kalev, Petko S. & Singh, Harminder, 2014. "Trading volume, realized volatility and jumps in the Australian stock market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 31(C), pages 414-430.
    15. Manabu Asai & Michael McAleer & Marcelo C. Medeiros, 2012. "Asymmetry and Long Memory in Volatility Modeling," Journal of Financial Econometrics, Oxford University Press, vol. 10(3), pages 495-512, June.
    16. Andersen, Torben G. & Bollerslev, Tim & Lange, Steve, 1999. "Forecasting financial market volatility: Sample frequency vis-a-vis forecast horizon," Journal of Empirical Finance, Elsevier, vol. 6(5), pages 457-477, December.
    17. Patton, Andrew J., 2011. "Volatility forecast comparison using imperfect volatility proxies," Journal of Econometrics, Elsevier, vol. 160(1), pages 246-256, January.
    18. Darrat, Ali F. & Rahman, Shafiqur & Zhong, Maosen, 2003. "Intraday trading volume and return volatility of the DJIA stocks: A note," Journal of Banking & Finance, Elsevier, vol. 27(10), pages 2035-2043, October.
    19. Clark, Peter K, 1973. "A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices," Econometrica, Econometric Society, vol. 41(1), pages 135-155, January.
    20. Kao, Yu-Sheng & Zhao, Kai & Chuang, Hwei-Lin & Ku, Yu-Cheng, 2024. "The asymmetric relationships between the Bitcoin futures’ return, volatility, and trading volume," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 524-542.
    21. Waël Louhichi, 2011. "What drives the volume-volatility relationship on Euronext Paris?," Post-Print halshs-00601370, HAL.
    22. Copeland, Thomas E, 1976. "A Model of Asset Trading under the Assumption of Sequential Information Arrival," Journal of Finance, American Finance Association, vol. 31(4), pages 1149-1168, September.
    23. Min Liu & Chien‐Chiang Lee & Wei‐Chong Choo, 2021. "An empirical study on the role of trading volume and data frequency in volatility forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 792-816, August.
    24. Yadav, Miklesh Prasad & Sharif, Taimur & Ashok, Shruti & Dhingra, Deepika & Abedin, Mohammad Zoynul, 2023. "Investigating volatility spillover of energy commodities in the context of the Chinese and European stock markets," Research in International Business and Finance, Elsevier, vol. 65(C).
    25. Andrew J. Patton & Kevin Sheppard, 2015. "Good Volatility, Bad Volatility: Signed Jumps and The Persistence of Volatility," The Review of Economics and Statistics, MIT Press, vol. 97(3), pages 683-697, July.
    26. Tauchen, George E & Pitts, Mark, 1983. "The Price Variability-Volume Relationship on Speculative Markets," Econometrica, Econometric Society, vol. 51(2), pages 485-505, March.
    27. Maki, Daiki & Ota, Yasushi, 2021. "Impacts of asymmetry on forecasting realized volatility in Japanese stock markets," Economic Modelling, Elsevier, vol. 101(C).
    28. Francesco Audrino & Yujia Hu, 2016. "Volatility Forecasting: Downside Risk, Jumps and Leverage Effect," Econometrics, MDPI, vol. 4(1), pages 1-24, February.
    29. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    30. Karpoff, Jonathan M., 1987. "The Relation between Price Changes and Trading Volume: A Survey," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 22(1), pages 109-126, March.
    31. Li, Dakai, 2024. "Forecasting stock market realized volatility: The role of investor attention to the price of petroleum products," International Review of Economics & Finance, Elsevier, vol. 90(C), pages 115-122.
    32. Jennings, Robert H & Starks, Laura T & Fellingham, John C, 1981. "An Equilibrium Model of Asset Trading with Sequential Information Arrival," Journal of Finance, American Finance Association, vol. 36(1), pages 143-161, March.
    33. Giot, Pierre & Laurent, Sébastien & Petitjean, Mikael, 2010. "Trading activity, realized volatility and jumps," Journal of Empirical Finance, Elsevier, vol. 17(1), pages 168-175, January.
    34. Bissoondoyal-Bheenick, Emawtee & Brooks, Robert & Do, Hung Xuan, 2019. "Asymmetric relationship between order imbalance and realized volatility: Evidence from the Australian market," International Review of Economics & Finance, Elsevier, vol. 62(C), pages 309-320.
    35. Marcel Prokopczuk & Lazaros Symeonidis & Chardin Wese Simen, 2016. "Do Jumps Matter for Volatility Forecasting? Evidence from Energy Markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(8), pages 758-792, August.
    36. Kao, Yu-Sheng & Chuang, Hwei-Lin & Ku, Yu-Cheng, 2020. "The empirical linkages among market returns, return volatility, and trading volume: Evidence from the S&P 500 VIX Futures," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    37. Xu, Yanyan & Liu, Jing & Ma, Feng & Chu, Jielei, 2024. "Liquidity and realized volatility prediction in Chinese stock market: A time-varying transitional dynamic perspective," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 543-560.
    38. Chao Liang & Yu Wei & Yaojie Zhang, 2020. "Is implied volatility more informative for forecasting realized volatility: An international perspective," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(8), pages 1253-1276, December.
    39. Louhichi, Waël, 2011. "What drives the volume-volatility relationship on Euronext Paris?," International Review of Financial Analysis, Elsevier, vol. 20(4), pages 200-206, August.
    40. Mohammad Mazibar Rahman & Chi Guotai & Anupam Das Gupta & Mahmud Hossain & Mohammad Zoynul Abedin, 2022. "Impact of early COVID-19 pandemic on the US and European stock markets and volatility forecasting," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 35(1), pages 3591-3608, December.
    41. Andersen, Torben G, 1996. "Return Volatility and Trading Volume: An Information Flow Interpretation of Stochastic Volatility," Journal of Finance, American Finance Association, vol. 51(1), pages 169-204, March.
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