Mastery of “Monthly Effects”: Big Data Insights into Contrarian Strategies for DJI 30 and NDX 100 Stocks over a Two-Decade Period

Abstract

In contrast to finding better monthly performance shown in a specific month, such as the January effect (i.e., better stock price performance in January as opposed to other months), which has been extensively studied, the goal of this study is to determine whether investors would obtain better subsequent performance as technical trading signals emitted in a specific month because, from the investment perspective, investors purchasing stocks now would not know their performance until later. We contend that our analysis emphasizes its critical role in steering investment decisions and enhancing profitability; nonetheless, this issue appears to be overlooked in the relevant literature. As such, utilizing big data to analyze the constituent stocks of the DJI 30 and NDX 100 indices from 2003 to 2022 (i.e., two-decade data), this study investigates whether trading these stocks as trading signals emitted via contrarian regulation of stochastic oscillator indicators (SOIs) and the relative strength index (RSI) in specific months would result in superior subsequent performance (hereafter referred to as “monthly effects”). This study discovers that the oversold signals generated by these two contrarian regulations in March were associated with higher subsequent performance for holding 100 to 250 trading days (roughly one year) than other months. These findings highlight the importance of the trading time and the superiority of the RSI over SOIs in generating profits. This study sheds light on the significance of oversold trading signals and suggests that the “monthly effect” is crucial for achieving higher returns.