Predictability of Return in Pakistan Stock Market through the Application of the Threshold Quantile Autoregressive Models

Authors

1 Department of Management Science, National University of Modern Languages, Islamabad, Pakistan; Noon Business School, University of Sargodha, Pakistan

2 Department of Management Science, National University of Modern Languages, Islamabad, Pakistan

3 School of social sciences and Humanity, National University of Science and Technology, Islamabad, Pakistan

Abstract

Stock market behavior is a contentious matter among researchers in the field of finance. In literature, various conventional and behavioral explanations exist for real-life stock market behavior. This study considered and incorporated all three schools of thought on the matter and applied a nonlinear model namely a threshold quantile autoregressive model as a contribution to exploring the behavior of the Pakistan stock market from 2000 to 2018. The findings of the study indicate that autocorrelation exists in the KSE 100 index and has a significant impact on both higher and lower regimes. The results also point out that investors overreact and underreact in different states of the stock market. During the examination of the impact of stock characteristics and behavioral factors on the existence of stock market autocorrelation. It is concluded based on empirical evidence that these factors cause a significant impact on autocorrelation in the index. The study is of the view that behavioral biases are among the prime reasons for the violation of efficient market behavior and need further exploration.

Keywords

References

Amihud, Y., & Mendelson, H. (1987). Trading Mechanisms and Stock Returns: An Empirical Investigation. The Journal of Finance, 42(3), 533–553.
Amini, S., Gebka, B., Hudson, R., & Keasey, K. (2013). A Review of the International Literature on the Short Term Predictability of Stock Prices Conditional on Large Prior Price Changes: Microstructure, Behavioral and Risk Related Explanations. International Review of Financial Analysis, 26(1), 1–17.
Anderson, R. M., Eom, K. S., Hahn, S. B., & Park, J. H. (2013). Autocorrelation and Partial Price Sdjustment. Journal of Empirical Finance, 24, 78–93.
Bannigidadmath, D., & Narayan, P. K. (2016). Stock Return Predictability and Determinants of Predictability and Profits. Emerging Markets Review, 26, 153–173.
Barber, B. M., & Odean, T. (2008). All that Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors. Review of Financial Studies, 21(2), 785–818.
Baur, D. G., Dimpfl, T., & Jung, R. C. (2012). Stock Return Autocorrelations Revisited: A Quantile Regression Approach. Journal of Empirical Finance, 19(2), 254–265.
Bondt, W. F., & Thaler, R. (1985). Does the Stock Market Overreact? The Journal of Finance, 40(3), 793–805.
Boudoukh, J., Richardson, M. P., & Whitelaw, R. F. (1994). A Tale of Three Schools: Insights on Autocorrelations of Short-horizon Stock Returns. Review of Financial Studies, 7(3), 539–573.
Campbell, J. Y., Lo, A. W. C., & MacKinlay, A. C. (1997). The Econometrics of Financial Markets. New Jersey: Princeton University Press.
Chabi-Yo, F. (2019). What Is the Conditional Autocorrelation on the Stock Market? SSRN Scholarly Paper ID, Social Science Research Network, Retrieved from https://doi.org/10.2139/ssrn.3490938
Chakraborty, M. (2006). Market Efficiency for the Pakistan Stock Market: Evidence from the Karachi Stock Exchange. South Asia Economic Journal, 7(1), 67–81.
Chan, F., Durand, R. B., Khuu, J., & Smales, L. A. (2017). The Validity of Investor Sentiment Proxies. International Review of Finance, 17(3), 473–477.
Chang, K. L. (2009). Do Macroeconomic Variables Have Regime-Dependent Effects on Stock Return Dynamics? Evidence from the Markov Regime Switching Model. Economic Modelling, 26(6), 1283–1299.
Cohen, K. J., Maier, S. F., & Schwartz, R. A. (1986). The Microstructure of Securities Markets. Retrieved from International Monetary Fund.
Conrad, J., & Kaul, G. (1988). Time-variation in Expected Returns. Journal of Business, 61(4), 409–425.
Daniel, K., Hirshleifer, D., & Subrahmanyam, A. (1998). Investor Psychology and Security Market Under-and Overreactions. The Journal of Finance, 53(6), 1839–1885.
De Vilder, R., & Visser, M. P. (2007). Proxies for Daily Volatility. Retrieved from https://hal.archives-ouvertes.fr/halshs-00588307/
DeBondt, W. F. M., & Thaler, R. (1995). Financial Decision Making in Markets and Firm Finance. Series of Handbooks in Operational Research and Management Science, Retrieved from https://www.nber.org/system/files/working_papers/w4777/w4777.pdf
Fama, E. F. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work. The Journal of Finance, 25(2), 383–417.
Fama, E. F., & French, K. R. (1988). Permanent and Temporary Components of Stock Prices. Journal of Political Economy, 96(2), 246–273.
Fleming, M. J. (2001). Measuring Treasury Market Liquidity. Retrieved from https://papers.ssrn.com/sol3/papers.cfm?abstract_id=276289
Galvao Jr, A. F., Montes-Rojas, G., & Olmo, J. (2011). Threshold Quantile Autoregressive Models. Journal of Time Series Analysis, 32(3), 253–267.
Gębka, B., & Wohar, M. E. (2013). The Determinants of Quantile Autocorrelations: Evidence from the UK. International Review of Financial Analysis, 29, 51–61.
Harvey, C. R. (1995). Predictable Risk and Returns in Emerging Markets. Review of Financial Studies, 8(3), 773–816.Harvey, C. R., & Siddique, A. (1999). Autoregressive Conditional Skewness. Journal of Financial and Quantitative Analysis, 34(04), 465–487.
He, C., Silvennoinen, A., & Teräsvirta, T. (2008). Parameterizing Unconditional Skewness in Models for Financial Time Series. Journal of Financial Econometrics, 6(2), 208–230.
Ho, T. S., & Stoll, H. R. (1983). The Dynamics of Dealer Markets under Competition. The Journal of Finance, 38(4), 1053–1074.
Hudson, P. R. (2010). Stock Return Predictability despite Low Autocorrelation. Retrieved from Http://Eprints.Ncl.Ac.Uk
Kahneman, D., & Riepe, M. W. (1998). Aspects of Investor Psychology. The Journal of Portfolio Management, 24(4), 52–65.
Kahneman, D., & Tversky, A. (1979). Prospect Theory: An Analysis of Decision under Risk. Econometrica, 47(2), 263–291.
Keim, D. B., & Stambaugh, R. F. (1986). Predicting Returns in the Stock and Bond Markets. Journal of Financial Economics, 17(2), 357–390.
Khan, F. A., & Ahmad, N. (2017). Determinants of Dividend Payout: An Empirical Study of Pharmaceutical Companies of Pakistan Stock Exchange (PSX), Retrieved from http://ibimapublishing.com/articles/JFSR/2017/538821/538214.pdf
Khilji, N. M., & Nabi, I. (1993). The Behaviour of Stock Returns in an Emerging Market: A Case Study of Pakistan [with Comments]. The Pakistan Development Review, 32(4), 593–604.
Kim, J. H., Shamsuddin, A., & Lim, K. P. (2011). Stock Return Predictability and the Adaptive Markets Hypothesis: Evidence from Century-long US Data. Journal of Empirical Finance, 18(5), 868–879.
Kinnunen, J. (2013). Dynamic Return Predictability in the Russian Stock Market. Emerging Markets Review, 15, 107–121.
Koenker, R., & Bassett Jr, G. (1978). Regression Quantiles. Econometrica, 46(1), 33–50.
Koenker, R., & Xiao, Z. (2006). Quantile Autoregression. Journal of the American Statistical Association, 101(475), 980–990.
Kudryavtsev, A., Cohen, G., & Hon-Snir, S. (2013). “Rational’or’Intuitive”: Are Behavioral Biases Correlated Across Stock Market Investors? Contemporary Economics, 7(2), 31–53.
Lehmann, B. N. (1990). Fads, Martingales, and Market Efficiency. The Quarterly Journal of Economics, 105(1), 1–28.
Lewellen, J. (2002). Momentum and Autocorrelation in Stock Returns. Review of Financial Studies, 15(2), 533–564.
Lo, A. W., & MacKinlay, A. C. (1990). When are Contrarian Profits Due to Stock Market Overreaction? Review of Financial Studies, 3(2), 175–205.
MacKinlay, A. C. (1997). Event Studies in Economics and Finance. Journal of Economic Literature, 35(1), 13–39.
Mazviona, B. W. (2015). Measuring Investor Sentiment on the Zimbabwe Stock Exchange. Asian Journal of Economic Modelling, 3(2), 21–32.
McKenzie, M. D., & Kim, S.-J. (2007). Evidence of an Asymmetry in the Relationship between Volatility and Autocorrelation. International Review of Financial Analysis, 16(1), 22–40.
McMillan, D. G. (2004). Nonlinear Predictability of Short-run Deviations in UK Stock Market Returns. Economics Letters, 84(2), 149–154.
Mech, T. S. (1993). Portfolio Return Autocorrelation. Journal of Financial Economics, 34(3), 307–344.
Narayan, P. K., & Bannigidadmath, D. (2015). Are Indian Stock Returns Predictable? Journal of Banking & Finance, 58, 506–531.
O’Hara, M., & Oldfield, G. S. (1986). The Microeconomics of Market Making. Journal of Financial and Quantitative Analysis, 21(4), 361–376.
Poterba, J. M., & Summers, L. H. (1988). Mean Reversion in Stock Prices: Evidence and Implications. Journal of Financial Economics, 22(1), 27–59.
Rasheed, M. H., Gul, F., Akhtar, M. W., & Tariq, S. (2020). Dynamics of Overconfidence among Stock Market Investors in Pakistan. International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies, 11(4), 1-11.
Rasheed, M. H., Rafique, A., Zahid, T., & Akhtar, M. W. (2018). Factors Influencing Investor’s Decision Making in Pakistan: Moderating the Role of Locus of Control. Review of Behavioral Finance, 10(1), 70–87.
Rasheed, M. H., & Tariq, S. (2017). Overconfidence among Investors in Pakistan: Moderating Role of Locus of Control; Business and Management Perspective in the Asian Context. 2nd International Lahore Business School Conference, Retrieved from https://lahore.comsats.edu.pk/abrc2009/Proceedings/proceedings.htm
Säfvenblad, P. (2000). Trading Volume and Autocorrelation: Empirical Evidence from the Stockholm Stock Exchange. Journal of Banking & Finance, 24(8), 1275–1287.
Scholes, M., & Williams, J. (1977). Estimating Betas from Nonsynchronous Data. Journal of Financial Economics, 5(3), 309–327.
Shen, C.-H., & Wang, L.-R. (1998). Daily Serial Correlation, Trading Volume and Price Limits: Evidence from the Taiwan Stock Market. Pacific-Basin Finance Journal, 6(3), 251–273.
Tang, Z., Ran, M., & Chen, W. (2019). The Influence of Trading Volume, Market Trend, and Monetary Policy on Characteristics of the Chinese Stock Exchange. International Conference on Industrial Engineering and Systems Management (IESM), Retrieved from https://doi.org/10.1109/IESM45758.2019.8948180
Tong, H., & Lim, K. S. (1980). Threshold Autoregression, Limit Cycles and Cyclical Data. Journal of the Royal Statistical Society. Series B (Methodological), 42(3), 245–292.
Tversky, A., & Kahneman, D. (1974). Judgment under Uncertainty: Heuristics and Biases. Science, 185(1), 1124–1131.
Vassalou, M. (2003). News Related to Future GDP Growth as a Risk Factor in Equity Returns. Journal of Financial Economics, 68(1), 47–73.
Veronesi, P. (1999). Stock Market Overreactions to Bad News in Good Times: A Rational Expectations Equilibrium Model. Review of Financial Studies, 12(5), 975–1007.
Waweru, N. M., Munyoki, E., & Uliana, E. (2008). The Effects of Behavioral Factors in Investment Decision-making: A Survey of Institutional Investors Operating at the Nairobi Stock Exchange. International Journal of Business and Emerging Markets, 1(1), 24–41.
Westerlund, J., Narayan, P. K., & Zheng, X. (2015). Testing for Stock Return Predictability in a Large Chinese Panel. Emerging Markets Review, 24, 81–100.
Xue, W.-J., & Zhang, L.-W. (2017). Stock Return Autocorrelations and Predictability in the Chinese Stock Market—Evidence from Threshold Quantile Autoregressive Models. Economic Modelling, 60, 391–401.
Iranian Economic Review
Volume 25, Issue 4
December 2021
Pages 815-828

Files

Share

How to cite

Statistics