Asian Stock Markets Analysis: The New Evidence from Time-Varying Coefficient Autoregressive Model

• 발행기관: 한국유통과학회
• 저자명: Napon HONGSAKULVASU Asama LIAMMUKDA
• 간행물 정보: 『The Journal of Asian Finance, Economics and Business(JAFEB)』Vol. 7 No.9, 95~104쪽, 전체 10쪽
• 주제분류: 경제경영 > 경제학
• 파일형태: PDF
• 발행일자: 2020.09.30

영문 초록

In financial economics studies, the autoregressive model has been a workhorse for a long time. However, the model has a fixed value on every parameter and requires the stationarity assumptions. Time-varying coefficient autoregressive model that we use in this paper offers some desirable benefits over the traditional model such as the parameters are allowed to be varied over-time and can be applies to nonstationary financial data. This paper provides the Monte Carlo simulation studies which show that the model can capture the dynamic movement of parameters very well, even though, there are some sudden changes or jumps. For the daily data from January 1, 2015 to February 12, 2020, our paper provides the empirical studies that Thailand, Taiwan and Tokyo Stock market Index can be explained very well by the time-varying coefficient autoregressive model with lag order one while South Korea’s stock index can be explained by the model with lag order three. We show that the model can unveil the non-linear shape of the estimated mean. We employ GJR-GARCH in the condition variance equation and found the evidences that the negative shocks have more impact on market’s volatility than the positive shock in the case of South Korea and Tokyo.

목차

1. Introduction

2. Research Methodology

3. The Monte Carlo Simulation Study

4. Empirical Study

5. Conclusions

References

키워드

Non-Stationary Time-Varying Coefficient Autoregressive Model Asian Stock Markets GJR-GARCH