Entropy, Liquidity, and Momentum - ELMo

This trading strategy provided is incomplete as there is no script detailed. Without the script, it's impossible to outline its functionalities or replicate its method on TradingView manually.

To trade this strategy manually on TradingView, I would need specific details of the strategy's indicators, entry and exit conditions. Since these are not provided, I cannot offer an accurate manual replication process for this strategy.

Improving the Entropy, Liquidity, and Momentum (ELMo) strategy for manual trading on TradingView involves refining the approach to entropy calculation, liquidity assessment, and the integration of additional indicators to bolster decision-making. The following steps can enhance the efficacy of ELMo:

• Entropy Refinement:
  • Use a shorter lookback period for Shannon entropy to capture more recent trend changes.
  • Implement weighted moving averages on entropy scores to prioritize recent price action.
• Liquidity Evaluation:
  • Manually confirm liquidity using the Hui-Heubel Liquidity Ratio (lhh) before making trade entries to ensure the market can absorb trade volume without slippage.
  • Compare lhh values across multiple timeframes for consistency, increasing the reliability of the signal.
• Conditional Indicators:
  • Incorporate Relative Strength Index (RSI) values but adjust the thresholds to pair with current volatility regimes in the market.
  • Add a stochastic oscillator to confirm momentum before entering a trade.
• Entry and Exit Criteria Tuning:
  • Enter long positions when the entropy curve crosses above the moving average line in conjunction with high lhh values and favorable RSI/stochastic readings.
  • Enter short positions under opposite conditions—low liquidity and downward entropy movement.
  • Implement trailing stops based on Average True Range (ATR) for dynamic exit points, adjusting the multiplier based on current market volatility.
• Timeframe Selection and Bias:
  • Suit the strategy to preferred timeframes ranging from 1 minute to 1 month but validate consistency across multiple timeframes.
  • Adopt a long or short bias based on broader market conditions but use the opposing signal as a cautionary cue for potential hedging maneuvers.
• Performance Monitoring:
  • Regularly backtest the strategy, manually adjusting parameters to improve its adaptability and response to changing market conditions.

Note that each of these strategies should be practiced using paper trading or through careful backtesting before applying them to live trading scenarios. Continuous refinement is key, with tweaks based on observed market behaviors and personal trading style.

The Entropy, Liquidity, and Momentum (ELMo) strategy is designed for active traders who specialize in momentum trading and have a quant-based approach to the markets. The strategy is suitable for those comfortable with complex technical analysis and applying statistical concepts like Shannon entropy to evaluate trend strength.

• Tech-Savvy Day Traders: Those who can handle frequent intra-day trades and have the ability to monitor positions continuously.
• Statistically-Inclined: Traders who have an affinity for incorporating mathematical and statistical measures into their trading decisions.
• Adaptable Swing Traders: Individuals who trade on various time scales ranging from short-term to mid-term and are capable of adjusting the strategy's parameters based on market conditions.
• Risk-Conscious: This strategy also caters to traders who are meticulous in risk management and are skilled at using trailing stops and liquidity analysis to protect capital.

• Strategy Concept: Utilizes Shannon entropy and market liquidity analysis to dictate momentum-based trade entries and exits.
• Operational Method: Combines moving averages, liquidity ratio filtering, and conditional indicators like RSI for signal refinement.
• Trading Adaptation: Customizable for various timeframes and suitable for both intra-day and swing trading approaches.
• Manual Implementation: Requires knowledge of statistical analysis for entropy calculation and liquidity assessment using the Hui-Heubel Liquidity Ratio.
• Automation: Can be used with automated signals on TradingView for entry and exit points.
• Alert Combination: Traders can combine automated alerts with manual analysis for an optimized trading strategy.
• Risk Management: Implements trailing stops based on ATR and encourages hedging during windows of market weakness.
• Optimization Tip: Regular backtesting and parameter adjustments help adapt to market changes and improve strategy performance.
• Trader Profile: Best suited for technically inclined traders who are proactive in managing positions and appreciate statistical rigor in their strategies.