Investigating the Efficacy of RSI Divergence in the Nifty 50 Index - Khatavkar, Sagar (Digital Repository of Theses, 2024)
This dissertation empirically evaluates the performance of Relative Strength Index Divergence (RSID) as a predictive tool in the NIFTY50 index, focusing on its practical applications in financial market trading. The research tests the hypothesis that RSI divergences reliably predict trend reversals. It was found that divergences forming within 14-21 days, and beyond, exhibited the highest success rates, with bullish divergences outperforming bearish ones in terms of reliability and immediate success. The study employed a manual observation methodology, analyzing data across three eight-year periods (2000–2024). The empirical results revealed that most divergences formed within an 8-14 day range, with longer divergences showing higher predictive reliability. Bullish divergences, particularly those exceeding 21 days, demonstrated near-perfect success rates, while bearish divergences often experienced delayed success or occasional failures, especially during market downtrends. The validation phase involved executing real-world trades based on RSI divergences in Reliance Industries Ltd., yielding a 15.34% quarterly return on investment. These practical results corroborated the theoretical findings, reinforcing the value of RSI divergence as a tool for traders. Despite the robustness of the methodology, limitations include the reliance on manual observation and potential biases, as well as the study’s focus on the NIFTY50 index. Future research should explore the use of automated algorithms and extend the analysis to other markets and technical indicators. In conclusion, this study provides valuable insights into RSI divergences, contributing to the broader understanding of their predictive capabilities and offering a strong foundation for future research in technical analysis.