This study utilized GARCH-type models to model the relationship between stock returns and its volatility in addition to investigating the asymmetric volatility of both emerging and developed markets. The effect of including trading volume in the conditional variance of GARCH-type models on volatility asymmetry and volatility persistence is probed. The results reveal that stock returns and its volatility are positively related. Moreover, developed markets are described by high volatility clustering and volatility persistence as compared to emerging markets. Addition of trading volume on conditional variance equation has an effect on both asymmetric volatility and volatility persistence. Finally, it is revealed that holding asset returns from emerging market is risky than that of developed markets.

stock returns, volatility asymmetry, volatility persistence, GARCH-type models.

Received: July 3, 2022; Revised: August 9, 2022; Accepted: September 10, 2022; Published: September 23, 2022

How to cite this article: Sebastian Kaweto Kalovwe, Joseph Ivivi Mwaniki and Richard Onyino Simwa, On stock market asymmetric volatility and trading volume, Far East Journal of Theoretical Statistics 66 (2022), 89-104. http://dx.doi.org/10.17654/0972086322014

This Open Access Article is Licensed under Creative Commons Attribution 4.0 International License

References:

[1] Roni Bhowmik and Shouyang Wang, Stock market volatility and return analysis: a systematic literature review, Entropy 22(5) (2020), 522.
https://doi.org/10.3390/e22050522.
[2] Karunanithy Banumathy and Ramachandran Azhagaiah, Modelling stock market volatility: evidence from India, Managing Global Transitions: International Research Journal 13(2) (2015).
[3] Hojatallah Goudarzi and C. S. Ramanarayanan, Modeling asymmetric volatility in the Indian stock market, International Journal of Business and Management 6(3) (2011), 221. doi:10.5539/ijbm.v6n3p221.
[4] Guojun Wu, The determinants of asymmetric volatility, The Review of Financial Studies 14(3) (2001), 837-859.
[5] Kerry David Patterson, An Introduction to Applied Econometrics: a Time Series Approach, Macmillan, 2000.
[6] Chris Brooks, RATS Handbook to Accompany Introductory Econometrics for Finance, Cambridge Books, 2008.
[7] Kenneth F. Kroner and Victor K. Ng, Modeling asymmetric comovements of asset returns, The Review of Financial Studies 11(4) (1998), 817-844.
[8] Philip Kearns and Adrian R. Pagan, Australian stock market volatility: economic record: 1875-1987, The Economic Society of Australia 69(2) (1993), 163-178.
[9] Suman Gulia, Testing of relationship between trading volume, return and volatility, Amity Global Business Review 11 (2016), 96-103.
[10] Edwin Moyo, Antony Gichuhi Waititu and Antony Ngunyi, Modelling the effects of trading volume on stock return volatility using conditional heteroskedastic models, Journal of Finance and Economics 6(5) (2018), 193-200.
[11] Pramod Kumar Naik, Rangan Gupta and Puja Padhi, The relationship between stock market volatility and trading volume: evidence from South Africa, The Journal of Developing Areas 52(1) (2018), 99-114.
[12] Tim Bollerslev, Generalized autoregressive conditional heteroskedasticity, Journal of Econometrics 31(3) (1986), 307-327.