Exploring The Main Factors Influencing Stock Price Volatility in China Based on The GARCH-MIDAS Model
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Abstract
This article comprehensively explores factors that affect stock price fluctuations from four perspectives: macroeconomic factors, geopolitical events, economic indicators, and financial factors. In order to analyze these influences, we used data from July 1997 to February 2023 and employed the GARCH-MIDAS model with the Shanghai Composite Index variable for empirical analysis. The main findings of this study are summarized as follows. Firstly, the Chinese Investors' Confidence Index, Consumer confidence index, Entrepreneur Confidence Index, Housing starts, Default spread, and Industrial Added Value positively impact long-term stock market volatility. This effect gradually strengthens over time. Other variables hurt the long-term volatility of the stock market. Secondly, Default spread has the highest predictive power, followed by USDX and Retail of Consumer Goods. Thirdly, the impact of macroeconomic variables, geopolitical events, economic indicators, and financial factors on stock market fluctuations varies significantly.
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References
Agrawal, G., Srivastav, A. K., & Srivastava, A. (2010). A study of exchange rates movement and stock market volatility. International Journal of business and management, 5(12), 62.
Audrino, F., Sigrist, F., & Ballinari, D. (2020). The impact of sentiment and attention measures on stock market volatility. International Journal of Forecasting, 36(2), 334-357.
Antonakakis, N., Chatziantoniou, I., & Filis, G. (2014). Dynamic spillovers of oil price shocks and economic policy uncertainty. Energy Economics, 44, 433-447.
Asgharian, H., Hou, A. J., & Javed, F. (2013). The importance of the macroeconomic variables in forecasting stock return variance: A GARCH‐MIDAS approach. Journal of Forecasting, 32(7), 600-612.
Baker, S. R., Bloom, N., & Davis, S. J. (2016). Measuring economic policy uncertainty. The quarterly journal of economics, 131(4), 1593-1636.
Bakkar, Y., Nilavongse, R., & Saha, A. K. (2021). Spillovers of the US real and financial uncertainty on the Euro area. Applied Economics Letters, 28(15), 1249-1258.
Bernanke, B. S. (1983). Irreversibility, uncertainty, and cyclical investment. The quarterly journal of economics, 98(1), 85-106.
Barsky, R. B., & Sims, E. R. (2012). Information, animal spirits, and the meaning of innovations in consumer confidence. American Economic Review, 102(4), 1343-1377.
Belcaid, K., & El Ghini, A. (2019). US, European, Chinese economic policy uncertainty and Moroccan stock market volatility. The Journal of Economic Asymmetries, 20, e00128.
Chang, B. K. (2012). The Impact of Exchange Rate and Interest Rate on Financial Institutions’ Stock Returns and Volatility. Journal of The Korean Data Analysis Society, 14(3), 1-645.
Chuliá, H., Guillén, M., & Uribe, J. M. (2017). Measuring uncertainty in the stock market. International Review of Economics & Finance, 48, 18-33.
Chun, S. J. (2021). Korean stock market return predictability in the context of data-mining effect, Journal of The Korean Data Analysis Society, 23(1), 369-384.
Chen, N. F., Roll, R., & Ross, S. A. (1986). Economic forces and the stock market. Journal of business, 383-403.
Christiansen, C., Schmeling, M., & Schrimpf, A. (2012). A comprehensive look at financial volatility prediction by economic variables. Journal of Applied Econometrics, 27(6), 956-977.
Conrad, C., & Loch, K. (2015). Anticipating long‐term stock market volatility. Journal of Applied Econometrics, 30(7), 1090-1114.
Conrad, C., & Kleen, O. (2020). Two are better than one: volatility forecasting using multiplicative component GARCH‐MIDAS models. Journal of Applied Econometrics, 35(1), 19-45.
Caldara, D., & Iacoviello, M. (2022). Measuring geopolitical risk. American Economic Review, 112(4), 1194-1225.
Desai, H., Ramesh, K., Thiagarajan, S. R., & Balachandran, B. V. (2002). An investigation of the informational role of short interest in the Nasdaq market. The Journal of Finance, 57(5), 2263-2287.
Drechsler, I. (2013). Uncertainty, time‐varying fear, and asset prices. The Journal of Finance, 68(5), 1843-1889.
Engle, R. F., & Rangel, J. G. (2008). The spline-GARCH model for low-frequency volatility and its global macroeconomic causes. The review of financial studies, 21(3), 1187-1222.
Engle, R. F., Ghysels, E., & Sohn, B. (2013). Stock market volatility and macroeconomic fundamentals. Review of Economics and Statistics, 95(3), 776-797.
Elder, J., & Serletis, A. (2010). Oil price uncertainty. Journal of Money, Credit and Banking, 42(6), 1137-1159.
Engle, R. F., Ghysels, E., & Sohn, B. (2013). Stock market volatility and macroeconomic fundamentals. Review of Economics and Statistics, 95(3), 776-797.
Fama, E. F., & French, K. R. (1989). Business conditions and expected returns on stocks and bonds. Journal of financial economics, 25(1), 23-49.
Fang, T., Lee, T. H., & Su, Z. (2020). Predicting the long-term stock market volatility: A GARCH-MIDAS model with variable selection. Journal of Empirical Finance, 58, 36-49.
Feng, Y., Xu, D., Failler, P., & Li, T. (2020). Research on the time-varying impact of economic policy uncertainty on crude oil price fluctuation. Sustainability, 12(16), 6523.
Hamilton, J. D., & Lin, G. (1996). Stock market volatility and the business cycle. Journal of applied econometrics, 11(5), 573-593.
Huang, R. D., & Kracaw, W. A. (1984). Stock market returns and real activity: a note. The Journal of Finance, 39(1), 267-273.
Inaba, K. I. (2020). A global look into stock market comovements. Review of World Economics, 156(3), 517-555.
Jurado, K., Ludvigson, S. C., & Ng, S. (2015). Measuring uncertainty. American Economic Review, 105(3), 1177-1216.
Jung, D. S. (2021). A study on the return spillover effects of the Korean financial markets using spillover index, Journal of The Korean Data Analysis Society, 22(3), 1241-1253.
Jiang Yu. (2019). Has the international influence of China's stock market increased? -- Empirical tests based on major stock markets in China and the world. Journal of Southeast University: Philosophy and Social Sciences Edition, 21(3), 53-63.
Kaul, G. (1987). Stock returns and inflation: The role of the monetary sector. Journal of financial economics, 18(2), 253-276.
Khalid, W., & Khan, S. (2017). Effects of macroeconomic variables on the stock market volatility: the Pakistan experience. International Journal of Econometrics and Financial Management, 5(2), 42-59.
Kam, H., & Shin, Y. (2017). The impact of macroeconomic variables on stock returns in Korea. Korean Journal of Business Administration, 30(1), 33-52.
Koh, G. S. (2019). A study on the relationship among exchange rate changes, industry performances, and stock returns in Korea, Journal of The Korean Data Analysis Society, 21(6), 3017-3031.
Kejlberg, S. (2018). The Effects of Economic Variables on Swedish Stock Market Volatility A GARCH-MIDAS Approach.
Kim Boo-kwon, Choi Ki-hong, & Yoon Sung-min. (2021). Effects of macroeconomic variables, global economic uncertainty, and sentiment index on volatility in the Korean stock market. Journal of The Korean Data Analysis Society (JKDAS), 23(4), 1699-1715.
Liu, Y., Han, L., & Yin, L. (2019). News implied volatility and long-term foreign exchange market volatility. International review of financial analysis, 61, 126-142.
Liu, L., & Zhang, T. (2015). Economic policy uncertainty and stock market volatility. Finance Research Letters, 15, 99-105.
Lei Li-Kun, Yu Jiang, Wei Yu, & Lai Xiao-Dong. (2018). Economic policy uncertainty and Volatility prediction of Chinese stock market. Journal of Management Science, 21(6), 88-98.
Mollick, A. V., & Assefa, T. A. (2013). US stock returns and oil prices: The tale from daily data and the 2008–2009 financial crisis. Energy Economics, 36, 1-18.
Mazur, M., Dang, M., & Vega, M. (2021). COVID-19 and the march 2020 stock market crash. Evidence from S&P1500. Finance research letters, 38, 101690.
Mei, D., Ma, F., Liao, Y., & Wang, L. (2020). Geopolitical risk uncertainty and oil future volatility: Evidence from MIDAS models. Energy Economics, 86, 104624.
Niu Tianjiao, & Wang Lu. (2020). Extreme Granger Causality between Chinese Stock Market and Macroeconomy. Henan Science.
Ozcelebi, O. (2021). Assessing the impacts of global economic policy uncertainty and the long-term bond yields on oil prices. Applied Economic Analysis, 29(87), 226-244.
Peng K S. (2021). The impact of international crude oil price fluctuation on Chinese stock market. Investment and entrepreneurship.
Ross, S. A. (1973). The economic theory of agency: The principal's problem. The American economic review, 63(2), 134-139.
Sutrisno, B. (2020). The determinants of stock price volatility in Indonesia, Economics and Accounting Journal, 3(1), 73-79.
Schwert, G. W. (1989). Why does stock market volatility change over time? Journal of Finance, 44(5), 1115-1153.
Su, Z., Fang, T., & Yin, L. (2018). Does NVIX matter for market volatility? Evidence from Asia-Pacific markets. Physica A: Statistical Mechanics and its Applications, 492, 506-516.
Srivastava, A., Bhatia, S., & Gupta, P. (2015). Financial crisis and stock market integration: An analysis of select economies. Global Business Review, 16(6), 1127-1142.
Shi Qiang, Yang Yiwen, & Liu Yakai. (2019). The relationship between macroeconomics and stock market volatility based on GARCH-MIDAS model. Computer Engineering and Applications, 55(15), 257-262.
Wang Juan, & Li Rui. (2019). Time-varying volatility of Chinese stock market: Based on long memory and leverage effect perspective. Journal of Beihang University (Social Sciences Edition), 32(3), 57-65.
Wei, Y., Yu, Q., Liu, J., & Cao, Y. (2018). Hot money and China’s stock market volatility: Further evidence using the GARCH–MIDAS model. Physica A: Statistical Mechanics and Its Applications, 492, 923-930.
Wang, W., & Lv, Y. (2013). A study of the USDX based on ARIMA model—A correlation analysis between the USDX and the Shanghai index. In 2013 3rd International Conference on Consumer Electronics, Communications and Networks (pp. 49-53). IEEE.
Yoon, Y. J., & Ohk, K. Y. (2014). A study on relation between bond yields and equity volatility, Journal of The Korean Data Analysis Society, 16(2), 837-846.
Yu, H., Fang, L., & Sun, W. (2018). Forecasting performance of global economic policy uncertainty for volatility of Chinese stock market. Physica A: Statistical Mechanics and Its Applications, 505, 931-940.
Zheng Tingguo, & Shang Yuhuang. (2014). Stock Market volatility Measurement and Prediction based on macro fundamentals. World Economy, (12), 118-139.
Zhong Lixin, Yao Qian, & Wang Congcong. (2020). Will policy factors affect stock market volatility in the long run? -- Analysis based on GARCH-MIDAS model. Journal of Finance and Economics, 260(6), 51.