Market crash factors and developing an early warning system: Evidence from Asia
-
DOIhttp://dx.doi.org/10.21511/imfi.20(3).2023.10
-
Article InfoVolume 20 2023, Issue #3, pp. 116-125
- Cited by
- 381 Views
-
118 Downloads
This work is licensed under a
Creative Commons Attribution 4.0 International License
Market crashes pose significant risks to the stability and performance of financial markets, making the development of an early warning system crucial. This study utilizes exchange rate volatility and investor sentiment to predict market crashes. While several studies have examined factors affecting market crashes in developing countries. This study aims to develop an early warning system for investors to minimize investment risk using Exchange Rate Volatility and Investor Sentiment. The study focused on seven countries: Indonesia, Malaysia, Singapore, the Philippines, Thailand, Vietnam, and Mongolia. The stock exchanges examined included Jakarta Stock Exchange Composite, FTSE Malaysia KLCI, FTSE Singapore, SET Index, PSEi, HNX/HNXI, and MNE Top 20/MNETOP20. The analysis involved assessing early warning systems to provide valuable supplementary information for decision making and evaluating market vulnerabilities. The logistic regression equation was utilized to model market crashes, incorporating variables such as exchange rate volatility and investor sentiment while considering their interactions as moderating factors. The results indicate that exchange rate volatility and investor sentiment have a significant negative effect on market crashes, with probabilities of 0.0082 and 0.000 Furthermore, investor sentiment acts as a mediator for exchange rate volatility, amplifying its impact on market crashes. This suggests that higher exchange rate volatility and negative investor sentiment increase the likelihood of market crashes. Exchange rate volatility and investor sentiment can serve as early warning indicators, emphasizing the importance of monitoring these factors for market participants and policymakers.
- Keywords
-
JEL Classification (Paper profile tab)G01, G32, E44
-
References30
-
Tables5
-
Figures1
-
- Figure 1. Research framework
-
- Table 1. Operational variables
- Table 2. Descriptive analysis
- Table 3. Correlation matrix
- Table 4. Matrix of constant Markov transition probabilities
- Table 5. Binary logit regression output
-
- Alamsyah, N., & Zhu, Y. Q. (2021). We Shall Endure: Exploring the Impact of Government Information Quality and Partisanship on Citizens’ Well-Being During the COVID-19 Pandemic. Government Information Quarterly, 39, 1-12.
- Ali, R., Mangla, I. U., Rehman, R. U., & Xue, W. (2020). Exchange Rate, Gold Price, and Stock Market Nexus: A Quantile Regression Approach. Risks, 8(3), 1-16.
- Alnafea, M., & Chebbi, K. (2022). Does Investor Sentiment Influence Stock Price Crash Risk? Evidence from Saudi Arabia. Journal of Asian Finance, Economics and Business, 9(1), 143-152.
- Asekome, M. O., & Agbonkhese, A. O. (2015). Macroeconomic Variables, Stock Market Bubble, Meltdown and Recovery: Evidence from Nigeria. Journal of Finance and Bank Management, 3(2), 25-34.
- Bouteska, A. (2020). The Journal of Economic Asymmetries Understanding the impact of investor sentiment on the price formation process: A review of the conduct of American stock markets. The Journal of Economic Asymmetries, 22, 1-29.
- Contessi, S., & Pace, P. De. (2021). The International Spread of COVID-19 Stock Market Collapses. Finance Research Letters Journal, 42, 101894.
- Cui, H., & Zhang, Y. (2019). Does Investor Sentiment Affect Stock Price Crash Risk? Applied Economics Letters, 1-5.
- Fan, Y., Zhou, F., An, Y., & Yang, J. (2021). Investor Sentiment and Stock Price Crash Risk: Evidence from China. Global Economic Review, 50(4), 310-339.
- Febriandika, N. R., Hakimi, F., Awalliyah, M., & Yayuli. (2023). Contagion and Spillover Effects of Global Financial Markets on the Indonesian Sharia Stock Index. Investment Management and Financial Innovations, 20(3), 35-47.
- Fu, J., Wu, X., Liu, Y., & Chen, R. (2020a). Firm-specific investor sentiment and stock price crash risk. Finance Research Letters, August 2019, 101442.
- Fu, J., Wu, X., Liu, Y., & Chen, R. (2020b). Firm-specific Investor Sentiment and Stock Price Crash Risk. Finance Research Letters, 1-11.
- Gong, X., Wen, F., He, Z., Yang, J., Yang, X., & Pan, B. (2016). Extreme Return, Extreme Volatility and Investor Sentiment. Quantitative Economics, 30(15), 3949-3961.
- Haritha, P. H., & Rishad, A. (2020). An Empirical Examination of Investor Sentiment and Stock Market Volatility: Evidence From India. Financial Innovation, 6(34), 1-15.
- Klopotan, I., Zoroja, J., & Meško, M. (2018). Early Warning System in Business, Finance, and Economics: Bibliometric and Topic Analysis. International Journal of Engineering Business Management, 10, 1-12.
- Liu, Z., Huynh, T. L. D., & Dai, P. F. (2021). The Impact of COVID-19 on the Stock Market Crash Risk in China. Research in International Business and Finance, 57, 1-10.
- Mazur, M., Dang, M., & Vega, M. (2020). COVID-19 and the March 2020 Stock Market Crash. Evidence from S&P1500. Finance Research Letters, 38, 1-20.
- Moradi, M., Appoloni, A., Zimon, G., Tarighi, H., & Kamali, M. (2021). Macroeconomic Factors and Stock Price Crash Risk: Do Managers Withhold Bad News in the Crisis-Ridden Iran Market? Sustainability, 13, 1-16.
- Pan, W. (2019). Does Investor Sentiment Drive Stock Market Bubbles? Beware of Excessive Optimism! Journal of Behavioral Finance, 21(20), 27-41.
- Peng, Z., & Hu, C. (2020). The Threshold Effect of Leveraged Trading on the Stock Price Crash Risk: Evidence from China. Entropy, 22(3), 268.
- Rai, A., Mahata, A., Nurujjaman, M., & Prakash, O. (2021). Statistical Properties of the Aftershocks of Stock Market Crashes Revisited: Analysis Based on the 1987 Crash, Financial-Crisis-2008 and COVID-19 Pandemic. International Journal of Modern Physics C (World Scientific), 1-9.
- Salisu, A. A., Isah, K., & Ogbonnaya-Orji, N. (2022). A Firm Level Analysis of Asymmetric Response of U.S. stock Returns to Exchange Rate Movements. International Journal of Finance and Economics, 27(1), 1220-1239.
- Samitas, A., Kampouris, E., & Kenourgios, D. (2020). Machine Learning as an Early Warning System to Predict Financial Crisis. International Review of Financial Analysis, 71(April), 101507.
- Sheikh, U. A., Asad, M., Ahmed, Z., & Mukhtar, U. (2020). Asymmetrical Relationship Between Oil Prices, Gold Prices, Exchange Rate, and Stock Prices During Global Financial Crisis 2008: Evidence from Pakistan. Cogent Economics & Finance, 8(1), 1-20.
- Song, R., Shu, M., & Zhu, W. (2020). The 2020 Global Stock Market Crash: Endogenous or Exogenous? Cornell University, 1-25.
- Syahri, A., & Robiyanto, R. (2020). The Correlation of Gold, Exchange Rate, and Stock Market on Covid-19 Pandemic Period. Jurnal Keuangan Dan Perbankan, 24(3), 350-362.
- Tian, M., Li, W., & Wen, F. (2021). The Dynamic Impact of Oil Price Shocks on Stock Market and The USD/RMB Exchange Rate: Evidence From Implied Volatility Indices. The North American Journal Of Economics and Finance, 1-66.
- Yang, X., Zhu, Y., & Cheng, T. Y. (2019). How the Individual Investor Took on Big Data: The Effect of Panic in the Internet Stock Message Boards on Stock Price Crash. Pacific-Basin Finance Journal, 1-40.
- Yin, Y., & Tian, R. (2015). Investor Sentiment, Financial Report Quality and Stock Price Crash Risk: Role of Short-Sales Constraints Investor Sentiment, Financial Report Quality and Stock Price Crash Risk: Role of Short-Sales Constraints. Emerging Markets Finance and Trade, 1-18.
- Zhang, R., Xian, X., & Fang, H. (2019). The Early-Warning System of Stock Market Crises with Investor Sentiment: Evidence from China. International Journal of Finance and Economics, 24(1), 361-369.
- Zouaoui, M. (2011). How Does Investor Sentiment Affect Stock Market Crises? Evidence from Panel Data. The Financial Review, 46, 723-747.