UCLA

It is clear that the intricacies of the stock market have prompted many to conduct research in this potentially lucrative topic of analysis. Some suggest that the stock market obeys the random walk hypothesis, some explore cyclical patterns, and others contemplate on the impact of macroeconomic variables on stock market performance. This study aims to investigate these questions by analyzing the Dow Jones Industrial Average (DJIA) data. Through autoregressive moving average (ARMA) modeling, spectral analysis and moving average filtering, we find evidence agreeing to the random walk hypothesis, uncover correlation between the macroeconomic environment and stock market returns, and encounter limits of the ARMA models in sustaining their predicting accuracy during times of uncertainty. In this paper, we present the evidence and meaningful findings of the study, and in addressing the limits we offer potential approach for extended research.