Modeling and Forecasting Saudi Stock Market Volatility Using Wavelet Methods

• 발행기관: 한국유통과학회
• 저자명: Tariq S. ALSHAMMARI Mohd T. ISMAIL Sadam AL-WADI Mohammad H. SALEH Jamil J. JABER
• 간행물 정보: 『The Journal of Asian Finance, Economics and Business(JAFEB)』Vol. 7 No.11, 83~93쪽, 전체 11쪽
• 주제분류: 경제경영 > 경제학
• 파일형태: PDF
• 발행일자: 2020.11.30

영문 초록

This empirical research aims to modeling and improving the forecasting accuracy of the volatility pattern by employing the Saudi Arabia stock market (Tadawul)by studying daily closed price index data from October 2011 to December 2019 with a number of observations being 2048. In order to achieve significant results, this study employs many mathematical functions which are non-linear spectral model Maximum overlapping Discrete Wavelet Transform (MODWT) based on the best localized function (Bl14), autoregressive integrated moving average (ARIMA) model and generalized autoregressive conditional heteroskedasticity (GARCH) models. Therefore, the major findings of this study show that all the previous events during the mentioned period of time will be explained and a new forecasting model will be suggested by combining the best MODWT function (Bl14 function) and the fitted GARCH model. Therefore, the results show that the ability of MODWT in decomposition the stock market data, highlighting the significant events which have the most highly volatile data and improving the forecasting accuracy will be showed based on some mathematical criteria such as Mean Absolute Percentage Error (MAPE), Mean Absolute Scaled Error (MASE), Root Means Squared Error (RMSE), Akaike information criterion. These results will be implemented using MATLAB software and R- software.

목차

1. Introduction

2. Mathematical Models

3. Research Design and Methodology

4. Empirical Results

5. Conclusion

References

키워드

MODWT’s Functions Saudi Stock Market Volatility GARCH Model, Forecasting