论文标题
MACD基本交易策略的比较研究：美国股票市场的证据
A comparative study of the MACD-base trading strategies: evidence from the US stock market
论文作者
论文摘要
近年来，越来越多的投资者在自己的交易中使用技术分析方法。由于增加了计算能力和开花公共数据，评估技术分析的有效性变得更加可行，独立投资者可以方便地进行股票分析并进行股票分析并进行回报。移动平均收敛差异（MACD）指标是广泛用于不同策略的流行技术指标之一。为了验证MACD有效性，在本文中，我使用带有传统参数（12、26、9）的MACD指标来构建各种交易策略。然后，我将这些策略应用于美国股市三个指数上列出的股票（即陶氏琼斯，纳斯达克股票和标准普尔500指数），并评估其在获胜率，盈利能力，卓越比率，交易数量和最大缩水量的方面。回测试是使用Python编程的，涵盖了2015年1月1日和28-08-2021之间的周期。结果表明，只有MACD指标的策略的胜利率小于50％。但是，将MACD指标与其他势头指标（例如货币流量指数（MFI）和相对强度指数（RSI））（RSI）（RSI）等其他动量指标相结合的交易策略改善了胜利率。基于此结果，我通过考虑交易量和每日价格波动率来重新设计MACD数学公式，以得出一个称为VPVMA的新指标。结果表明，这种新交易策略的赢率和风险调整绩效得到了显着改善。通常，调查结果表明，尽管上述所有MACD交易策略都可以产生正回报，但如果不使用其他动量指标，则性能不佳。因此，VPVMA指示器的性能更好。
In recent years, more and more investors use technical analysis methods in their own trading. Evaluating the effectiveness of technical analysis has become more feasible due to increasing computing capability and blooming public data, which indie investors can perform stock analysis and backtest their own trading strategy conveniently. The Moving Average Convergence Divergence (MACD) indicator is one of the popular technical indicators that are widely used in different strategies. In order to verify the MACD effectiveness, in this thesis, I use the MACD indicator with traditional parameters (12, 26, 9) to build various trading strategies. Then, I apply these strategies to stocks listed on three indices in the US stock market (i.e., Dow-Jones, Nasdaq, and S&P 500) and evaluate its performance in terms of win rate, profitability, Sharpe ratio, number of trades and maximum drawdown. The backtesting is programmed using Python, covering the period between 01/01/2015 and 28-08-2021. The result shows that the win-rate of the strategy with only the MACD indicator is less than 50%. However, the win-rate is improved for the trading strategies that combine the MACD indicator with other momentum indicators like the Money Flow Index (MFI) and the Relative Strength Index (RSI). Based on this result, I redesign the MACD mathematical formula by taking the trading volume and daily price volatility into consideration to derive a new indicator called VPVMA. The results show that the win-rate and risk-adjust performance of this new trading strategy have been improved significantly. In general, the findings suggest that while all the MACD trading strategies mentioned above can generate positive returns, the performance is not good without using other momentum indicators. Hence, the VPVMA indicator performs better.
