Empirical Analysis of Stock Returns and Volatility: Evidence From Asian Stock Markets

Abstract

The objective of this research isto measure and examine volatilities among important stock markets of Asia and to ascertain a causal relation between volatility and stock returns. For this purpose six markets KSE100 (Karachi, Pakistan), BSE Sensex (Mumbai, India), NIKKEI 225 (Tokyo, Japan), Hang Seng (Hong Kong), Shanghai Stock Exchange (SSE) (Shanghai, China) and KOSPI (Seoul, South Korea) were considered. Stock market indices comprise of daily data from the period January 2002 to December 2009. The graphical representation of time series shows the preliminary examination of stock behaviors. The analysis shows the high correlation and heteroskedastic trend (volatility) among the stock markets in selected time period. After preliminary analysis the formal descriptive method of mean, standard deviation and coefficient of variation have been applied for measuring and ranking purposes. The results show that KOSPI has the highest average annual return of 12.67% and followed by BSE with 11.61%, whereas, KSE 100 has the least annual average returns of 9.31%. The highest volatility coefficient of 3.097 has been observed in Hang Seng (Hong Kong) followed by 2.87 in Nikkei (Tokyo). However, the KSE 100 observed the lowest volatility coefficient of 2.078. Bartlett’s test is applied for the inferential analysis to investigate whether the equality of volatility is the same in each market return. Finally, GARCH (1, 1) model is applied which concludes a significant ARCH (1) and GARCH (1) effects and confirms all markets’ returns are statistically significant since p < 0.01 and their Long Run Average Variances (LRAV) range from 1.52% to 2.54% for KSE100 Index and Shanghai Stock Exchange respectively.

Mean reversion in international markets: evidence from G.A.R.C.H. and half-life volatility models

“…is less than one. The previous literature has also found the same conclusion (Ahmad et al, 2016;Chi et al, 2016;Hart et al, 2015;Mishra, 2017;Tripathy, 2017;Wang et al, 2015). The results of the study also demonstrate that there is a direct relation between stock returns and volatilities of the emerging and developed stock markets.…”

“…Similarly, Kuttu (2017) suggested that the existence of mean reversion process explains the different behaviours of the stock market. Ribeiro et al (2017), Ahmad et al (2016), and Kim, Morley, and Nelson (2001) also studied the behaviours of stocks and volatility, and they have also concluded the direct relationship between stock returns and the volatility. Arefin and Ahkam (2017), Chen et al (2012), and Balsara, Chen, and Zheng (2007) concluded that the investors should use the constrained trading strategy to get maximum profit because of the mean reversion process.…”

Highlighting the Dynamics of the Game-Changer: Empirical Evidence from Stock Markets of the Key Players

“…The descriptive analysis was done by taking log returns as done by previous studies e.g. Saleem (2007) and Ahmad, Ahmed, Vveinhardt and Streimikiene (2016). The descriptive analysis shows that among the two indices PSX-100 has the highest mean return of 0.099%, followed by post-CPEC announcement mean return of PSX-100 of 0.018%.…”

Exploring the Gibson law in CEE countries using a time series approach

“…Another aspect to consider when studying the paradox is the interconnection between fi nancial markets (Vychytilová, 2015). Volatilities among important stock markets could also infl uence the relationship between bond yields and prices (Ahmad et al, 2016). Microeconomic aspects are an important trigger for the paradox (Škare & Mošnja-Škare, 2014).…”