Strategy of Synthesis between Multiple Relative Strength Indicators

Overview

The strategy of synthesis between multiple relative strength indicators (RSI) is a timing trading strategy that utilizes multiple RSIs with different periods to trade stocks. It tracks 1-, 2-, 3-, 4-, and 5-period RSI indicators simultaneously. Buying signals are generated when any of the RSI goes below a threshold. Selling signals are generated when all RSIs exceed their own thresholds, in order to earn profits. Thus, timing entries and exits can be achieved in stocks.

Strategy Logic

The key rationale behind this strategy is to track 1-, 2-, 3-, 4-, and 5-period RSI indicators simultaneously, including 4-, 7-, 14-, 21-, and 28-period RSIs. Separate threshold values are set for each of the 5 RSI indicators. A buying signal is triggered when any of the RSI drops below its own threshold.

For example, the threshold of the 4-period RSI is set as 15. A buying signal is generated when the 4-period RSI falls below 15. The strategy checks other RSIs to see whether they also drop below their own thresholds. If yes, more buying signals will be produced.

When all the 5 RSI indicators rally and exceed their own thresholds, a selling signal is generated in order to gain profits. By congregation signals of the multiple-period indicators, accuracy of entries can be improved.

Strategy Strengths

1. Improve accuracy of entries with multiple RSIs

The strategy utilizes 5 RSIs of different periods to generate buy and sell signals. One single indicator may generate false signal at times. However, with the congregation of multiple ones, accuracy of signal can be improved, hence enhancing accuracy of entries.

2. RSIs of different periods suitable for various market conditions

   The 1-, 2-, 3-, 4-, 5-period RSIs used in this strategy can adapt to stock fluctuations of different frequencies. For instance, 28-period RSI suits long-term trading while 4-period RSI suits short-term trading. This guarantees the strategy works under different market situations.

3. Clean and clear code structure

   The variable naming and overall structure of the strategy code is neat and self-evident. The logic flow for different indicators and signals is clear. This makes the strategy easy to understand, modify and optimize, which is of great essence for quantitative strategies.

Risks of The Strategy

1. Invalid in trending market

   The strategy relies heavily on overbought and oversold signals. Its effectiveness would be compromised in persistent up- or downtrend market. This is a ubiquitous flaw of mean-reversion strategies using reverse indicators.

2. Difficulty in parameter optimization

   A variety of indicators and input parameters exist in this strategy. This poses immense challenges for parameter optimization. Improper parameter combination may diminish the strategy efficacy drastically. Optimizing tools should be utilized to seek for the parameter set that maximizes strategy performance.

3. Frequent reversals between long and short

   Due to the usage of multiple-period indicators, long and short position changes in the strategy could be rather frequent. This may lead to higher costs associated with trading and risks related to price slippage.

Directions for Optimization

1. Incorporate trend-following indicators

   Trend tools such as MA and BOLL can be added. Signals are only taken when trend tools concur to the signals generated by reverse indicators. This helps avoid losses in persistent trend situations.

2. Reduce the number of RSI indicators

   Try decreasing the number of RSI tools used. This mitigates the difficulty in parameter optimization. Experiments manifest 2 to 3 indicators can already create satisfying efficacy.

3. Optimize parameter ranges

   Seek optimal ranges and combinations of RSI parameters and thresholds using optimization methods like gradient descent and random search. This maximizes strategy performance.

Conclusion

The strategy of RSI synthesis generates trading signals by congregation signals from multiple RSIs with different periods. This improves accuracy of entries to realize timing trading in stocks. Despite advantages inherited from the usage of multiple indicators, flaws including ineffectiveness in trending markets and difficulty in optimization remain. Methods like adding trend tools, reducing indicator numbers, and parameter optimization can help further boost the strategy’s robustness.