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- Title
TIME SERIES MODELING OF THE DYNAMICS OF THE DOW AND S&P 500 INDEXES OVER TIME.
- Authors
Hassan, Morsheda; Nassar, Raja; Keleta, Ghebre
- Abstract
Performance of the stock market affects many individuals and corporations and is of importance for the economy of the country. Therefore, it is of prime importance to be able to determine variables that relate to stock returns and develop models that can predict the behavior of the stock market over time. In this study, from a set of nine macroeconomic variables, we developed linear time series models (using transfer function and auto-regression time series analyses) relating the DOW index and the S&P 500 index as dependent variables to the GDP as the independent variable. For both indexes, the index at time t was a function of its lag at time t-1 and the GDP at time t and its lag at time t-1. This simple model gave an excellent fit to the data for pre and post the 2008 recession. Forecasts from the model were good for the pre-2008 recession but underestimated somewhat the observed indexes for 2017 and 2018. This could be attributed to outside intervention due to deregulation (or in anticipation of) during the Trump presidency. GDP seems to be a good predictor of the DOW and S&P behaviors over time under normal circumstances, barring any intervention, such as recessions, regulations or deregulations, or world political events.
- Subjects
TRUMP, Donald, 1946-; STANDARD &; Poor's Financial Services LLC; TIME series analysis; STANDARD &; Poor's 500 Index; MARKET timing; INDEPENDENT variables; STOCK exchanges
- Publication
Journal of International Business Disciplines, 2020, Vol 15, Issue 2, p13
- ISSN
1934-1814
- Publication type
Article