Optimization of Trading Strategies on Indian Stock Market System using Moving Average Convergence Divergence (MACD) Indicator

Investors have been using technical analysis techniques in their own trading frequently in recent years. Due to improved computational power and a burgeoning public data supply, it is now possible to evaluate the success of technical analysis. Optimization analysis on the data set is being done for an accurate result oriented approach. Independent investors may now easily undertake stock research and back test their own trading strategies. Trading optimization use a variety of technical indicators to assess the efficacy of different trading methods. One of the widely used technical indicators in numerous techniques is the Moving Average Convergence Divergence (MACD) indicator. Here in this optimization approach, several trading strategies using the MACD indicator with conventional settings (12, 26, 9) is being used to confirm the MACD's efficacy. Finally, the application is made possible by using equities listed on NIFTY 50, and optimized the performance in terms of win rate, number of trades, profitability, and sortino ratio, sharpe ratio and maximum drawdown. Python is being used to programme the back testing, which spans the dates of 2016 and 2022. The optimized outcomes demonstrate that this trading approach has greatly improved in terms of win-rate and risk-adjusted performance. Overall, the optimized results indicate that while all of the above-mentioned MACD trading techniques can produce positive returns, the performance is subpar without the use of additional momentum indicators