PREDICTING STOCK MARKET TRENDS WITH TIME-SERIES ECONOMETRIC MODELS
Keywords:
Time-Series Econometric Models, Stock Market Trends, ARIMA,Abstract
The dynamic nature of the stock market, influenced by a myriad of factors ranging from economic indicators to global events, presents a complex challenge for prediction. This article delves into the application of time-series econometric models as a pivotal tool for forecasting stock market trends. By dissecting the methodology and utility of prominent models such as ARIMA, SARIMA, ARIMAX, VAR, and VECM, the paper illustrates their potency in capturing temporal dependencies and patterns within stock data. It further discusses the integration of traditional econometric methods with emerging technologies like machine learning to enhance predictive accuracy. Despite the inherent challenges posed by market volatility and the unpredictability of exogenous shocks, the article argues for the strategic use of time-series econometric models, underpinned by a nuanced understanding of their limitations and strengths, in navigating the uncertainties of financial markets.
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References
Box, G.E.P., Jenkins, G.M., & Reinsel, G.C. (2015). Time Series Analysis: Forecasting and Control. John Wiley & Sons.
Tsay, R.S. (2010). Analysis of Financial Time Series. Wiley-Interscience.
Enders, W. (2014). Applied Econometric Time Series. John Wiley & Sons.
Hamilton, J.D. (1994). Time Series Analysis. Princeton University Press.
Brooks, C. (2014). Introductory Econometrics for Finance. Cambridge University Press.
Hyndman, R.J., & Athanasopoulos, G. (2018). Forecasting: Principles and Practice. OTexts.
Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer.
Granger, C.W.J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica.
Sims, C.A. (1980). Macroeconomics and Reality. Econometrica.
Engle, R.F., & Granger, C.W.J. (1987). Co-integration and Error Correction: Representation, Estimation, and Testing. Econometrica.
Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics.
Bai, J., & Perron, P. (2003). Computation and Analysis of Multiple Structural Change Models. Journal of Applied Econometrics.
