OBV-SMA Crossover with RSI Filter Multi-Dimensional Momentum Trading Strategy

Overview

This strategy is a multi-dimensional momentum trading system that combines On-Balance Volume (OBV), Simple Moving Average (SMA), and Relative Strength Index (RSI). It captures market momentum by monitoring crossover signals between OBV and its moving average, while using RSI as a filter to avoid excessive trend chasing. The strategy also incorporates percentage-based stop-loss and take-profit mechanisms to achieve balanced risk-reward management.

Strategy Principles

The core logic is built on three dimensions:

1. OBV indicator measures cumulative volume sentiment by calculating the accumulated volume based on price movement direction to reflect market buying and selling power.
2. The 20-period moving average of OBV serves as a baseline. Long signals are triggered when OBV crosses above its moving average with RSI below 70, while short signals are triggered when OBV crosses below with RSI above 30.
3. RSI implementation serves as a filter to prevent trading in overbought/oversold areas, effectively reducing false breakout risks.

The strategy employs fixed percentage stop-loss (2%) and take-profit (4%) levels, creating a symmetric risk management framework that helps maintain a stable risk-reward ratio.

Strategy Advantages

1. Multi-dimensional signal confirmation reduces the impact of false signals
2. Organic integration of volume, price momentum, and overbought/oversold indicators
3. Clear risk management framework with fixed stop-loss and profit targets
4. Simple and clear strategy logic, easy to understand and maintain
5. Excellent visualization design with clear trading signals and indicator display

Strategy Risks

1. May trigger frequent stop-losses in high volatility markets
2. Fixed percentage stops may not suit all market conditions
3. RSI filtering conditions might miss important trend initiations
4. OBV indicators may generate misleading signals in low liquidity environments
5. Strategy doesn’t account for market cyclical characteristics

Strategy Optimization Directions

1. Introduce adaptive stop-loss mechanisms, such as ATR-based or volatility-adjusted stops
2. Add trend filters, such as long-period moving averages for main trend direction
3. Optimize RSI parameters, consider dynamic adjustment of overbought/oversold thresholds
4. Add volume screening conditions to ensure signals trigger with valid volume support
5. Consider time filters to avoid high volatility periods
6. Implement position management mechanisms for dynamic position adjustment

Summary

This is a well-designed multi-dimensional momentum trading strategy that builds a complete trading system by combining the advantages of technical indicators. The core strength lies in its multi-layered signal confirmation mechanism and standardized risk management framework. While there are potential risks, the suggested optimization directions can further enhance the strategy’s robustness and adaptability. The strategy’s practical value is mainly reflected in its clear logic, ease of implementation, and maintenance. Traders are advised to thoroughly test performance under different market conditions and optimize parameters according to specific needs before live deployment.