Speed of Mean Reversion: An Empirical Analysis of Kse, Lse and Ise Indices

Abstract

Abstract. The purpose of this study is to determine the presence of mean reversion in the stock markets indices of Pakistan, moreover, to measure, and compare the speed of mean reversion of the stock markets indices across Pakistan. In order to carry out the research study, the daily data of three stock indices of Pakistan such as: KSE-100, LSE-25 and ISE-10 are collected from 2003 to 2014. After the application of tests such as ARCH and GARCH, it was found that returns series of KSE-100, LSE-25 and ISE-10 indices exhibit mean reversion, indicating that the returns revert back to their historical value after reaching an extreme value. Further, the mean reversion rate shows that KSE-100 index has the slowest mean reversion, however, the ISE-10 index has the fastest mean reversion among the three indices. Therefore, the results of the study concluded that KSE-100 index, due to the slowest mean reversion rate has higher volatility over a longer period of time. On the contrary, since, ISE-10 index has exhibited the fastest mean reversion with the lowest volatility as compared to others. But due to fast mean reversion rate, it will help investors to gain profits over a shorter period of time. Thus, it can be recommended that the investor willing to bear the risk of time and looking for long-term investment should invest in KSE-100 index. However, investors looking for higher profits in a shorter period can invest in the ISE-10 index but with higher risk-returns trade-off.

Asymmetric Mean Reversion in Low Liquid Markets: Evidence from BRVM

“…If the series show no unit root, then we can use a stationary times series class model like covariance-stationary ARMA. This test is also an insight into the mean reversion property Palwasha et al (2018). If the return has no unit root, then the returns may exhibit a mean reverting property.…”

“…This model allows to capture the leverage effects. Other alternatives are the standard GARCH (sGARCH) model (Palwasha et al 2018). However, the advantage of using the EGARCH model is that it specifies the logarithm of conditional volatility and avoids the need for any parametric constraints, so any positivity restrictions on parameters to ensure non-negativity of h t is not needed.…”

“…The majority of research conducted on this hypothesis focuses on developed stock markets in the United States and Europe (Ahmed et al 2018;Palwasha et al 2018;Poterba and Summers 1988;Spierdijk et al 2012). Very few studies address the market efficiency in the context of African stock markets (Anoruo and Gil-Alana 2011;Kuttu 2018;Mlambo and Biekpe 2007).…”

“…Despite the interest in the EMH, many investors believe that one can make a profit from the times series of prices by focusing properly on some patterns in securities. One possible explanation behind that position is the theory of mean reversion (Palwasha et al 2018). Mean reversion is the assumption that a stock's price will tend to move to the average price over time.…”

“…Evidence for mean reverting stock prices has mainly been tested for several advanced and emerging stock markets (Ahmed et al 2018;Fama 1965;Palwasha et al 2018). Palwasha et al (2018) find that the mean reversion theory is valid on the Pakistan stock market using daily data of three stock indices: KSE-100, LSE-25 and ISE-10. Further, the mean reversion rate shows that the indices do not have the same mean reversion speed.…”