Market Sentiment and Stock Return Volatility in Malaysia: Evidence using the GARCH-X Model
Abstract
Market sentiment is a key determinant of stock market volatility, particularly in globally interconnected economies such as Malaysia. With the rising role of retail investors in digital trading environments, understanding sentiment’s influence on market behavior has become increasingly important. Although regulatory frameworks exist to protect investors, surveillance practices often rely on traditional indicators like price and trading volume, which may not fully capture real market dynamics.
This study addresses this gap by empirically examining the effects of market sentiment—measured through the Consumer Sentiment Index (CSI)—alongside macroeconomic variables on stock returns and volatility in Malaysia. Using the GARCH-X Model with stock return data from January 1990 to January 2025, results reveal that CSI has a positive and significant relationship with stock returns. This suggests that investor confidence influenced Malaysia’s stock market returns more strongly than geopolitical events or monetary policy factors. Findings also indicate that the stock market does not always align with macroeconomic fundamentals in the short term. Instead, volatility intensifies during periods of instability, amplifying when new shocks occur. Over the long run, however, the market adjusts and reverts to equilibrium. These results underscore the importance of enhancing regulatory tools for real-time volatility monitoring and improving structured, legal, and accessible data sharing. Such measures would strengthen market resilience and ensure effective responses during crises or adverse global events, ultimately supporting more stable and transparent financial markets in Malaysia.
Downloads
References
Aggarwal, V., Doifode, A., & Tiwary, M. K. (2022). Do lower foreign flows and higher domestic flows reduce indian equity market volatility? Vision, 26(4), 461–470.
Apergis, N., & Rezitis, A. N. (2011). Food price volatility and macroeconomic factors: evidence from GARCH and GARCH-X estimates. Journal of Agricultural and Applied Economics, 43(1), 95–110.
Batala, L. K., Yu, W., Khan, A., Regmi, K., & Wang, X. (2021). Natural disasters' influence on industrial growth, foreign direct investment, and export performance in the South Asian region of Belt and road initiative. Natural Hazards, 108(2), 1853-1876.
Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327.
Bursa Malaysia Berhad. (2025). Market Surveillance Overview. Retrieved June 29, 2025, from https://www.bursamalaysia.com/regulation/about_bursa_malaysia_regulatory/market_surveillance/overview
Caldara, D., & Iacoviello, M. (2022). Measuring geopolitical risk. American Economic Review, 112(4), 1194–1225.
Deveikyte, J., Geman, H., Piccari, C., & Provetti, A. (2022). A sentiment analysis approach to the prediction of market volatility. Frontiers in Artificial Intelligence, 5, 836809.
Dickey, D. A., & Fuller, W. A. (1981). Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica: journal of the Econometric Society, 1057-1072.
Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica: Journal of the econometric society, 987-1007.
Engle, R. F., & Bollerslev, T. (1986). Modelling the persistence of conditional variances. Econometric reviews, 5(1), 1-50.
Ghulam, S., Mubashar, A., Bashir, M., & Hussain, S. (2025). Foreign Direct Investment and Stock Market Development: Evidence from Asia. Journal of Social Sciences Review, 5(1), 1-10.
Hsu, Y. J., Lu, Y. C., & Yang, J. J. (2021). News sentiment and stock market volatility. Review of Quantitative Finance and Accounting, 57(3), 1093-1122.
Kim, T., & Ha, A. (2010, August). Investor sentiment and market anomalies. In 23rd Australasian Finance and Banking Conference.
Kong, E. Y. F., & Tang, K. B. (2024). Are Malaysian IPO Investors Influenced by Sentiment Factors or Fundamental Factors? Capital Markets Review, 32(1), 29-58.
Lai, F., Li, S., Lv, L., & Zhu, S. (2023). Do global geopolitical risks affect connectedness of global stock market contagion network? Evidence from quantile-on-quantile regression. Frontiers in Physics, 11, 1124092.
Lamine, A., & Zribi, S. (2024). Do geopolitical risks affect stock market returns and volatilities: an analysis based on the TVP-VAR model. European Journal of Government and Economics, 13(2), 240-261.
Lamoureux, C. G., & Lastrapes, W. D. (1990). Persistence in variance, structural change, and the GARCH model. Journal of Business & Economic Statistics, 8(2), 225-234.
Li, Y., Shi, Y., Shi, Y., Xiong, X., & Yi, S. (2024). Time-frequency extreme risk spillovers between COVID-19 news-based panic sentiment and stock market volatility in the multi-layer network: Evidence from the RCEP countries. International Review of Financial Analysis, 94, 103339.
Loang, O. K., Candra, S., & Naveenan, R. V. (2024). Stability in chaos: Impact of monetary, fiscal, and firm characteristics on investor sentiment in Asian emerging markets. International Journal of Business and Society, 25(3), 1145-1164.
Luong, A. T. (2025). How does the asymmetric spillover of investor sentiment respond to economic policy uncertainty in G7 and BRICS countries? Review of Behavioral Finance, 17(2), 317-341.
Mohnot, R., Banerjee, A., Ballaj, H., & Sarker, T. (2024). Re-examining asymmetric dynamics in the relationship between macroeconomic variables and stock market indices: empirical evidence from Malaysia. The Journal of Risk Finance, 25(1), 19-34.
New Straits Times. (2025, May). Impact of FOMO on stock investing. New Straits Times. Retrieved June 29, 2025, from https://www.nst.com.my/business/insight/2025/05/1209894/impact-fomo-stock-investing
Pan, C., Zhang, W., & Wang, W. (2023). Global geopolitical risk and volatility connectedness among China's sectoral stock markets. Finance Research Letters, 58, 104487.
Paramanik, R. N., & Singhal, V. (2020). Sentiment analysis of Indian stock market volatility. Procedia Computer Science, 176, 330-338.
Ph, H., & Rishad, A. (2020). An empirical examination of investor sentiment and stock market volatility: evidence from India. Financial Innovation, 6(1), 34.
Ruan, Q., Yang, H., Lv, D., & Zhang, S. (2018). Cross-correlations between individual investor sentiment and Chinese stock market return: New perspective based on MF-DCCA. Physica A: Statistical Mechanics and its Applications, 503, 243-256.
Securities Commission Malaysia. (2025, June). Equity Market Statistics. https://www.sc.com.my/api/documentms/download.ashx?id=8ebbc40c-8ce6-479f-b8d6-e6f1afdb23e5
Staikouras, S. K. (2006). Testing the stabilization hypothesis in the UK short-term interest rates: Evidence from a GARCH-X model. The Quarterly Review of Economics and Finance, 46(2), 169-189.
Sun, C., Yi, S., Wu, F., Li, Y., & Dong, Z. (2025). Mainshocks and aftershocks: Assessing the resilience of Asia-Pacific stock markets amid global financial cycle shocks. Pacific-Basin Finance Journal, 91, 102720.
Wang, J., Zhang, L., & Sun, Y. (2025). Geopolitical risk and corporate environmental investment. Applied Economics, 1-15.
Xiao, J., Jiang, J., & Zhang, Y. (2024). Policy uncertainty, investor sentiment, and good and bad volatilities in the stock market: Evidence from China. Pacific-Basin Finance Journal, 84, 102303.
Xie, D., Cui, Y., & Liu, Y. (2023). How does investor sentiment impact stock volatility? New evidence from Shanghai A-shares market. China Finance Review International, 13(1), 102-120.
Copyright (c) 2025 Nasha Shafridah Binti Abdullah, Siti Nurhidayah Mohd Roslen, Nur Zahidah Binti Bahrudin, Pang Mary, Siti Nur Nadhirah Binti Mohd Roslen

This work is licensed under a Creative Commons Attribution 4.0 International License.
Author (s) should affirm that the material has not been published previously. It has not been submitted and it is not under consideration by any other journal. At the same time author (s) need to execute a publication permission agreement to assume the responsibility of the submitted content and any omissions and errors therein. After submission of revised paper in the light of suggestions of the reviewers, the editorial team edits and formats manuscripts to bring uniformity and standardization in published material.
This work will be licensed under Creative Commons Attribution 4.0 International (CC BY 4.0) and under condition of the license, users are free to read, copy, remix, transform, redistribute, download, print, search or link to the full texts of articles and even build upon their work as long as they credit the author for the original work. Moreover, as per journal policy author (s) hold and retain copyrights without any restrictions.