Yee Wai Sim
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Yee Wai Sim has a total of 21 co-authors. Here are the top co-authors by number of shared publications:
- Hui Hwang Goh
School of Engineering, Taylors University Lakeside Campus, Subang Jaya, Malaysia
2 shared publications - Chee-Onn Chow
Universiti Malaya
1 shared publication - Denesh Sooriamoorthy
School of Engineering, Asia Pacific University, 57000, Kuala Lumpur, Malaysia
1 shared publication Dongdong Zhang
1 shared publication- Doong Toong Lim
Faculty of Computing and Engineering, QUEST International University, Perak, Malaysia
1 shared publication - Haonan Xie
School of Electrical Engineering, Guangxi University, Nanning 530004, China
1 shared publication
Latest Publications
- Top Cited PapersOpen Access
- 11 February 2026
- Published by Elsevier in Results in Engineering
- Vol. 29
Synthesizing physics and quantum machine learning for next-generation battery health prognostics: A critical review and roadmap
- 11 February 2026
- Published by Elsevier in Results in Engineering
- Vol. 29
Top Cited PapersOpen AccessSynthesizing physics and quantum machine learning for next-generation battery health prognostics: A critical review and roadmap
- 2 March 2023
- Published by Asian Economic and Social Society in Asian Economic and Financial Review
- Vol. 13 (3) , 162-179
Estimation of stock market index volatility using the GARCH model: Causality between stock indices
This paper aims to model the volatility of returns for selected stock indices and examine the causal relationships between the markets using the historical daily prices of the Financial Times Stock Exchange (FTSE), Bursa Malaysia Kuala Lumpur Composite Index (KLCI), the Indonesia Stock Exchange Index (LQ45), and the Stock Exchange of Thailand (SET) from January 2008 to November 2019. The study employs univariate GARCH models that are prominent in capturing the volatility clustering of financial instruments in association with the Box–Jenkins methodology for better estimation. Generally, the ARMA-GARCH model is used to capture the volatility series, while the Granger causality test examines the causal directions between the markets. The findings revealed leverage effects on the markets, with the outperformance of the EGARCH in analyzing the empirical properties of stock returns. An initial test that yielded positive correlations suggests the existence of co-movement between the derived volatility series. The study concluded bidirectional causal relationships between the selected markets, and based on the resulting relationships, it is proposed that supervision of markets among the ASEAN members could be advantageous in predicting the corresponding market performance.
- 2 March 2023
- Published by Asian Economic and Social Society in Asian Economic and Financial Review
- Vol. 13 (3) , 162-179
Estimation of stock market index volatility using the GARCH model: Causality between stock indices
This paper aims to model the volatility of returns for selected stock indices and examine the causal relationships between the markets using the historical daily prices of the Financial Times Stock Exchange (FTSE), Bursa Malaysia Kuala Lumpur Composite Index (KLCI), the Indonesia Stock Exchange Index (LQ45), and the Stock Exchange of Thailand (SET) from January 2008 to November 2019. The study employs univariate GARCH models that are prominent in capturing the volatility clustering of financial instruments in association with the Box–Jenkins methodology for better estimation. Generally, the ARMA-GARCH model is used to capture the volatility series, while the Granger causality test examines the causal directions between the markets. The findings revealed leverage effects on the markets, with the outperformance of the EGARCH in analyzing the empirical properties of stock returns. An initial test that yielded positive correlations suggests the existence of co-movement between the derived volatility series. The study concluded bidirectional causal relationships between the selected markets, and based on the resulting relationships, it is proposed that supervision of markets among the ASEAN members could be advantageous in predicting the corresponding market performance.