# A comparative study of the MACD-base trading strategies: evidence from the US stock market

**Authors:** Pat Tong Chio  
**arXiv:** [2206.12282](https://arxiv.org/abs/2206.12282)  
**Date:** 2022-06-18  
**Summary page:** https://www.summarizepaper.com/en/paper/2206.12282v1/

## Key points

- Growing trend among investors to incorporate technical analysis methods into trading strategies
- Advancements in computing power and availability of extensive public data make it easier for individual investors to analyze stocks and backtest their own strategies
- Moving Average Convergence Divergence (MACD) indicator is widely used
- Extensive analysis conducted using traditional MACD parameters (12, 26, 9) to develop various trading strategies
- Strategies applied to stocks listed on Dow-Jones, Nasdaq, and S&P 500 indices
- Performance evaluated based on win rate, profitability, Sharpe ratio, number of trades, and maximum drawdown
- MACD strategy as a standalone indicator had a win rate of less than 50%
- Win rate improved significantly when combined with other momentum indicators such as Money Flow Index (MFI) and Relative Strength Index (RSI)
- Proposed redesign of MACD formula by incorporating additional factors such as trading volume and daily price volatility led to the development of VPVMA indicator
- VPVMA strategy showed enhanced win rates and improved risk-adjusted performance compared to all previous MACD-based strategies
- All MACD-based strategies generated positive returns but were suboptimal without incorporating other momentum indicators
- VPVMA indicator outperforms traditional MACD indicator in terms of generating consistent profits and managing risk effectively
- Research provides valuable insights for investors seeking to enhance trading strategies using technical analysis methods in the US stock market.

## Summary

In recent years, there has been a growing trend among investors to incorporate technical analysis methods into their trading strategies. This shift can be attributed to advancements in computing power and the availability of extensive public data, which have made it easier for individual investors to analyze stocks and backtest their own trading strategies. One widely used technical indicator is the Moving Average Convergence Divergence (MACD) indicator. To evaluate the effectiveness of the MACD indicator, this study conducted an extensive analysis using traditional MACD parameters (12, 26, 9) to develop various trading strategies. These strategies were then applied to stocks listed on three major US stock market indices - Dow-Jones, Nasdaq, and S&P 500. The performance of these strategies was evaluated based on several key metrics including win rate, profitability, Sharpe ratio, number of trades, and maximum drawdown. The backtesting process was carried out using Python programming language and covered a period ranging from January 1st, 2015 to August 28th 2021. The results revealed that when used as a standalone indicator, the MACD strategy had a win rate of less than 50%. However, when combined with other momentum indicators such as the Money Flow Index (MFI) and Relative Strength Index (RSI), the win rate improved significantly. Based on these findings, the researcher proposed a redesign of the MACD mathematical formula by incorporating additional factors such as trading volume and daily price volatility. This led to the development of a new indicator called VPVMA. The results demonstrated that this new trading strategy utilizing VPVMA showed enhanced win rates and improved risk-adjusted performance compared to all previous MACD-based strategies. Overall, while all MACD-based trading strategies generated positive returns according to the study's findings, their performance was suboptimal without incorporating other momentum indicators. Therefore, it can be concluded that the VPVMA indicator outperforms the traditional MACD indicator in terms of generating consistent profits and managing risk effectively. This research provides valuable insights for investors seeking to enhance their trading strategies using technical analysis methods in the US stock market.