Modelling stock returns volatility on Tokyo Stock Exchange Limited

Abstract

This study empirically investigates the volatility pattern of the Tokyo stock exchange based on time series data which consists of monthly closing prices of the Nekkei Index for the seventeen years from 2000 to 2017. The present study has employed various autoregressive conditional heteroscedasticity (ARCH) family models such as generalized autoregressive conditional heteroscedasticity (GARCH), exponential GARCH (EGARCH), and threshold ARCH (TARCH) to appraise assorted nature of volatility patterns in the Tokyo stock market. Our findings suggest that the stock index fluctuated over the period. The negative skewness exhibits that return is negatively skewed. The negative skewness provides that the returns distributions of the market have a higher probability of providing a negative return. Jarque-Bera test examines the normality of return. It outlines that return is not normally distributed in the Tokyo stock exchange. Based on the unit root test, it has been observed that the index variable is stationary at the level. Moreover, the ARCH effect, GARCH effect, EGARCH, and PARCH effect are based on volatility models.