Overview

This trading strategy combines moving average convergence divergence (MACD), relative strength index (RSI), simple moving average (SMA), stochastic oscillator and Bollinger bands to identify market entry and exit points. It goes long when indicators show bullish signals and goes short when bearish signals appear. Risk is controlled by stop loss and take profit.

Strategy Logic

It goes long when the MACD DIF line crosses above the DEA line into bullish zone; or when RSI drops below 30 into oversold territory; or when stochastic %K and %D lines fall below 20 showing oversold status.

On the contrary, it goes short when MACD DIF line crosses below DEA line into bearish zone; or when RSI rises above 70 into overbought area; or when stochastic %K and %D lines climb over 80 indicating overbought condition.

Stop loss is set based on ATR multiplied by a coefficient. Take profit is determined by risk-reward ratio.

Advantage Analysis

This strategy combines multiple indicators to judge market status, avoiding errors by single metric and improving accuracy. Also stop loss and take profit are reasonably set to control risk for each trade.

Risk Analysis

Technical indicators are calculated from historical data and cannot predict future prices, leading to certain lags. Combining multiple indicators may also introduce some false signals. In addition, improper stop loss setting can result in larger losses.

To tackle indicator lag issue, parameters can be adjusted to shorten computing cycle. For false signals, additional auxiliary indicators can be added for confirmation. Also, stop loss should be set wider and more reasonably.

Optimization Directions

The strategy can be enhanced in the following aspects:

1. Incorporate statistical model indicators based on trend and correlation analysis for entry;
2. Add machine learning model to judge reliability of indicator signals;
3. Optimize money management for more automated and intelligent stop loss and take profit.

Summary

This strategy combines multiple technical indicators for improved accuracy and controls risk via stop loss and take profit, making it a reliable trend following system. Its performance is expected to be further boosted by introducing statistical and machine learning techniques going forward.