Forecasting Volatility of Stocks Return: A Smooth Transition Combining Forecasts

• 영문명: Forecasting Volatility of Stocks Return: A Smooth Transition Combining Forecasts
• 발행기관: 한국유통과학회
• 저자명: Jen Sim HO Wei Chong CHOO Wei Theng LAU Choy Leng YEE Yuruixian ZHANG Cheong Kin WAN
• 간행물 정보: 『The Journal of Asian Finance, Economics and Business(JAFEB)』Vol. 9 No.10, 1~13쪽, 전체 13쪽
• 주제분류: 경제경영 > 경제학
• 파일형태: PDF
• 발행일자: 2022.12.31

영문 초록

This paper empirically explores the predicting ability of the newly proposed smooth transition (ST) time-varying combining forecast methods. The proposed method allows the “weight” of combining forecasts to change gradually over time through its unique feature of transition variables. Stock market returns from 7 countries were applied to Ad Hoc models, the well-known Generalized Autoregressive Conditional Heteroskedasticity (GARCH) family models, and the Smooth Transition Exponential Smoothing (STES) models. Of the individual models, GJRGARCH and STES-E&AE emerged as the best models and thereby were chosen for constructing the combined forecast models where a total of nine ST combining methods were developed. The robustness of the ST combining forecasts is also validated by the Diebold-Mariano (DM) test. The post-sample forecasting performance shows that ST combining forecast methods outperformed all the individual models and fixed weight combining models. This study contributes in two ways: 1) the ST combining methods statistically outperformed all the individual forecast methods and the existing traditional combining methods using simple averaging and Bates & Granger method. 2) trading volume as a transition variable in ST methods was superior to other individual models as well as the ST models with single sign or size of past shocks as transition variables.

목차

1. Introduction

2. Literature Review

3. Volatility Forecasting Methods

4. Results and Discussion

5. Conclusion

References

키워드

Stocks Volatility Forecasts Combining Forecasts Smooth Transition