Does Volatility Cause Herding in Malaysian Stock Market? Evidence from Quantile Regression Analysis

Abstract

This study examines the existence, tendency and determinants of herding in the Malaysian stock market under market stress from 2016 to 2020. This study adopts ordinary least square and quantile regression models to estimate herding. Three types of measurements are used to capture volatility, which are realized volatility, Parkinson volatility and Garman and Klass volatility. The result shows that herding exists in the Malaysian stock market. Investors are observed to herd stronger in the bearish (down) market condition compared to bullish (up) market condition, especially in the upper quantile (τ > 50%). Realized volatility is found to be significant in every quantile except for the median quantile (τ = 50%) and Garman and Klass’s volatility is significant in the upper quantiles of 0.75 and 0.90. This study assists analysts and investors to formulate better investment strategies. Regulators and policymakers shall also control and regulate the herding behaviour of investors, which can deviate the stocks from their fundamentals. The existence of herding also violates the assumptions of EMH in assuming that investors are rational.

What Is the Effect of Oil and Gas Markets (Spot/Futures) on Herding in BRICS? Recent Evidence (2007–2022)

“…Since they are representatives of emerging markets, the selection of BRICS countries can serve the purpose of gaining a relatively comprehensive understanding of the behaviour patterns of emerging markets under the influence of world energy markets. Nevertheless, much of the published research concerning this issue focuses on the developed markets or Gulf Cooperation Council (GCC) countries, such as the cases of the United States (BenMabrouk and Litimi 2018;Brunetti et al 2013;Youssef and Mokni 2020), GCC markets (Balcilar et al 2014(Balcilar et al , 2017Ulussever and Demirer 2017), and Saudi Arabia (Gabbori et al 2020), or on just one or two markets of the BRICS group, such as the cases of Brazil and Russia (Cakan et al 2019a) and Chinese Stock Exchanges (Loang 2023). Most importantly, currently, there seems to exist a variety of published literature shedding light on the influence of global energy on the local stock market, which can be divided into two categories: (1) the effect of fluctuation in various energy indicators (energy price, return, volatility, speculative activities in either spot or futures market) on the performance of the equity market (Ross et al 2021;Bernanke 2016;Alamgir and Amin 2021;Antonakakis and Filis 2013;Gatfaoui 2016) ; (2) the relationship between the energy market and investment behaviour (herding or trading preferences) (Cliffe 2022;Cattlin 2021;BenMabrouk and Litimi 2018;Cakan et al 2019a;Ghorbel et al 2014).…”

“…During an investigation into herding in Saudi Arabia, Gabbori et al (2020) observed that herding in Saudi Arabia tends to be independent of oil volatility, but not of OPEC meetings-the stock market in Saudi Arabia is reported to herd on and around the days of OPEC meetings. With regard to BRICS, Youssef and Mokni's (2023) work was complemented by Loang's (2023) study, which agreed that the crude oil market causes herding in China (only in the Shanghai Stock Exchange) due to its high degree of globalisation and development. Cakan et al (2019b) confirmed that a high-volatility regime can be regarded as the only driver of investors' herding in the real estate investment market in South Africa.…”