Currently, there is a controversy regarding fundamental predictability of the market, which has created a gap in understanding the fundamental principles of market performance. The problem this study addressed was the unknown predictability of the market that stems from under-investigated trading rules with current market data. The purpose of this quantitative study was to investigate the discrepant results of predictability from various types of technical analysis tools utilizing recent stock market data from the Dow Jones Industrial Average (DJIA) 1987 to 2009 to verify that these tools still produce positive trading results. The hypotheses explored whether market predictability is validated when those analytic techniques that were successfully applied in previous studies are applied to the original study using current stock market data. The sample used in this study was an ex-post facto research design that investigated simple analytic trading tools. The theoretical support for this study was from a model-based bootstrap study that found consistent positive returns by using simple technical analysis trading tools. A bootstrap methodology was used to construct tests on 5,800 trading days of the DJIA collected from the Center for Research in Security Prices. Replication of the study was analyzed via t test, random walk, autoregressive process of order one (AR (1)), a generalized autoregressive conditional heteroskedasticity in-mean model (GARCH-M), exponential GARCH (EGARCH) of the null model, descriptive analysis, autocorrelation, skewness, and kurtosis using a 5% significance level. The possible social significance of this study is the future benefit investors may realize by utilizing technical analysis trading strategies and protective buy (sell) stops to obtain positive returns in their long-term investment strategies.
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