Comparative Performance Evaluation of Relative Strength Index and Moving Average Convergence & Divergence: A Case of Twenty Sectoral Indices

Abstract

Forecasting stock price movements is a critical endeavor for investors and speculators, particularly in the realm of short-term investments and high-frequency trading. In these scenarios, fundamental analysis often takes a backseat, giving way to technical analysis as a more practical tool for predicting short-term price trends. This paper undertakes a comprehensive analysis of two prominent technical analysis indicators, the Relative Strength Index (RSI) and the Moving Average Convergence and Divergence (MACD), with the aim of determining which tool yields superior returns for investors engaged in multiple entry and exit strategies in the trading of twenty sectoral indices on the Bombay Stock Exchange. The study encompasses a dataset of 983 daily closing prices spanning from January 2014 to December 2017.

 The findings reveal a notable discrepancy between RSI and MACD in terms of key decisionmaking points across all twenty indices. RSI tends to offer fewer signals for action compared to MACD, implying that decisions made using RSI may lead to longer-term positions. In contrast, MACD signals prompt more frequent trading activity, potentially resulting in increased transaction costs due to frequent buy and sell actions. Additionally, the study observes that brokerage costs, typically averaging 0.1% of the transaction amount in India, may further impact the returns of investors employing the MACD technique.

In conclusion, investors seeking to optimize their trading strategies and transaction costs may benefit from a judicious combination of both RSI and MACD signals, capitalizing on the strengths of each indicator to navigate the complex landscape of stock market volatility. This approach allows for a balanced approach to trading, ensuring higher returns while mitigating transaction costs, thereby enhancing overall profitability across diverse sectoral indices.