I11L - Meanreverter 4h

This trading strategy uses a mean reversion approach based on RSI (Relative Strength Index) and its relationship to a moving average, identifying when the asset's price is expected to revert to its mean. It sets buying conditions when RSI is below its average by a certain percentage and aims to close the trade when RSI crosses above the moving average.

To trade this strategy manually on TradingView:

• Set an RSI indicator with a period of 40 to get "momentumRSI".
• Add a Simple Moving Average (SMA) to the RSI calculated above with a period of 10 to get "momentumRSI_slow".
• Calculate the RSI buy zone to be the "momentumRSI_slow" value minus a 5% offset.
• Calculate the sell/exit threshold using the "momentumRSI_slow" directly.
• Set a buy condition if the RSI is below the calculated buy zone and either no trades are open, or the average down condition is met based on an Average True Range (ATR) times three subtracted from the average position price.
• Ignore the isShort conditions as they are commented out in the code.
• Prepare to exit the trade when RSI goes above the "momentumRSI_slow", signaling a potential trend shift.
• Monitor the trades with potential exits at market price.

Additionally, the code implies that an absolute RSI barrier can be used; however, the input for this is fixed at 50 in the script and is not meant to be edited by default unless the code is modified.

Improving the I11L - Meanreverter 4h strategy through manual trading involves a combination of refining parameters, conducting in-depth market analysis, and adapting to changing market conditions. Consider the following plan to enhance the effectiveness of this strategy:

• Analyze market conditions: Since this strategy hinges on the negative beta of bonds to stocks, monitor economic indicators that influence this relationship. Utilize macroeconomic news updates and market sentiment tools to better anticipate shifts in correlation. This will allow for timely adjustments to the trading strategy.
• Adjust RSI and moving averages: Experiment with different periods for RSI and the moving average (SMA) to find the most responsive settings for the current market. For instance, during times of high market volatility, consider decreasing the RSI period to become more sensitive to price changes.
• Optimize buyZoneDistance:
  • Backtest with various buyZoneDistance percentages to determine the optimal spacing for entry signals.
  • Assess the impact of different spacings on the frequency of trades and holding periods during various market phases.
• Fine-tune AvgDownATRSum: The current setting might not be optimal in all conditions. Regularly re-evaluate and adjust this multiple based on prevailing volatility trends in the market, to enhance responsiveness to market turns without overexposing the strategy to unnecessary risk.
• Implement checks against survivorship bias: Keep the portfolio diversified and review the constituent stocks periodically, removing poor performers and considering new entrants to ensure the strategy is not skewed by only historically successful stocks.
• Account for trading costs: Analyze historical trades to quantify the impact of trading costs on net returns. Adjust the spacing between buy zones to find a balance that minimizes costs without significantly reducing signal quality.
• Continual investment: To mimic the strategy's requirement of being invested 100% of the time, develop a schedule for reviewing open positions and a clear set of criteria for reinvestment to maintain continuous market exposure.
• Manage risk through position sizing: Use the average ATR to determine position sizes, ensuring that each trade is proportionate to the current market risk level. Adjust positions dynamically in response to changes in the ATR to maintain a consistent risk profile.

By applying these improvements, you can manually enhance the I11L - Meanreverter 4h strategy beyond its automated origins, tailoring it to current market conditions and your personal risk tolerance.

This strategy is ideal for traders who are comfortable with technical analysis and have a penchant for closely monitoring the markets. It suits those who respect the cyclical nature of the markets and recognize the tendency of asset prices to revert to a mean over time. In particular:

• Mean-reversion traders: Those who focus on spotting and capitalizing on extreme deviations from an asset's historical average price.
• Quantitatively-inclined traders: Individuals who favor statistically-backed decision-making, given the reliance on indicators like RSI and ATR for trade signals and position sizing.
• Intermediate to advanced traders: The requirement of consistent market participation and adjustment of parameters based on market conditions suggests a need for some trading experience.
• Active and hands-on traders: The strategy necessitates regular strategy review, adjustment, and diligent risk management, aligning with a more active trading style.

This strategic approach is less suited for traders looking for set-and-forget systems or those who are averse to frequent interaction with the markets.

• Strategy Essence: A mean-reversion system that leverages RSI and MAs to detect overbought/oversold markets, typically benefiting from bond-stock market inverse correlations.
• Execution Method: Can be utilized through automated TradingView scripts or manual trading, with manual intervention allowing for refined control and optimization.
• Optimization: Backtest to adjust RSI periods, moving average frequencies, and buy zone distances; balance trade frequency and cost; adapt to volatility with AvgDownATRSum adjustments.
• Risk Management: ATR-based position sizing helps maintain consistent risk exposure; continuous investment is key to performance consistency.
• Trader Profile: Best for technically adept traders capable of adapting to market nuances and managing regular position reviews.
• Trading Style: Suitable for active traders with intermediate to advanced skills, particularly those who employ quantitative strategies and seek to actively manage risk and returns.