Crunchster's Normalised Trend Strategy

This trading strategy uses a normalization of price returns relative to their standard deviation, applies a Hull Moving Average (HMA) to the normalized price, and triggers entries and exits based on crossovers between the normalized price and the HMA.

To trade this strategy manually on TradingView:

• Apply a Standard Deviation indicator with a lookback period of 14 days to the price difference series (close - close[1]).
• Calculate normalized returns as the price difference divided by the standard deviation, then create a cumulative sum to form the normalized price series.
• Compute the Hull Moving Average using the square root of the lookback period (100 days) based on the normalized price series and apply an optional offset if needed.
• Establish entry conditions: Go long when the normalized price crosses over the HMA, and go short when it crosses under.
• Determine exit conditions: Close long positions when the normalized price crosses under the HMA, and close short positions when it crosses over.
• Set a stop-loss based on a multiple of the Average True Range (ATR) at the time of entry, adjusted for the specific risk management settings and calculated leverage.
• Trade only within the user-defined backtesting date range, ensuring it adheres to the timestamp confines given by the starting and ending years, months, and days.
• Adjust position size according to the volatility of recent returns, the annualized target volatility, and the specified compounding settings if toggled.
• Ensure that the position size does not exceed the maximum allowed capital, taking into consideration the leverage set by the user.

Improving the Crunchster's Normalised Trend Strategy for manual trading involves refining key aspects of the method and incorporating aspects of discretionary trading to enhance performance. An actionable plan can focus on the following components:

• Optimize Lookback Periods: Conduct thorough backtesting to determine the optimal lookback periods for the volatility adjustment and Hull Moving Average (HMA), to refine the entry and exit signals. This may vary by asset, so multiple assets should be tested to assess the strategy's versatility and robustness.
• Manual Chart Reviews: Regularly review charts to identify if the automated signals are aligning with significant technical analysis patterns or support and resistance levels. Manually override the automated signal if contrary evidence suggests a higher probability trade in the opposite direction.
• Adjust Position Sizing: Apply a more dynamic position sizing approach instead of strictly relying on the inverse volatility method. Consider the use of Kelly Criterion or Fixed Ratio methods to achieve better capital efficiency and enhance growth curves over time.
• Enhance Risk Management: Implement a tiered stop loss system where stops are gradually moved to favorable positions as the trade progresses, securing profits and reducing risk exposure. Utilize breakeven stops or trailing stops to capture more upside while protecting against market reversals.
• Fundamental Analysis Overlay: Infuse elements of fundamental analysis to adjust trading biases. For instance, during earnings seasons, additional caution must be applied when holding trades over announcement periods. Economic calendars should also be consulted to avoid trading around high-impact news events.
• Market Sentiment Analysis: Monitor market sentiment using social media analytics, news feed sentiment, or VIX trends to gauge the overall market mood. Use this information to adjust leverage and position sizes accordingly or to time market entries and exits better.
• Edge Refinement: Keep a comprehensive trading journal to log the performance of manual trading decisions over the automated strategy signals. Analyze the outcomes to identify specific circumstances where manual intervention typically leads to better results, and systematically integrate these findings into the trading plan.
• Periodic Review and Adaptation: Set regular intervals for reviewing the entire trading strategy, including the manual adjustments, to ensure it remains current with evolving market dynamics and personal trading skills. Be prepared to adapt the strategy as needed to maintain a competitive edge.

This strategy suits traders who appreciate systematic approaches and have an affinity for quantitative, rules-based trading setups. It's ideal for:

• Intermediate to Advanced Traders: Those with a working knowledge of technical analysis, particularly moving averages, volatility adjustments, and risk management.
• Trend Followers: Traders who prefer to capture profits from the momentum by following established market trends over daily timeframes.
• Risk-conscious Individuals: The strategy's advanced position sizing and risk management cater to traders with a strong emphasis on capital preservation.
• Time-efficient Practitioners: Its rules-based nature makes it manageable for traders who cannot constantly watch the markets, allowing positions to unfold over longer periods.
• Technologically Savvy: Given the quantitative aspects, it is apt for traders comfortable with the use of trading scripts and automation in TradingView.

The overall trading style is disciplined and data-driven, relying on statistical measures rather than subjective judgment to open and close trades.

• Strategy Essence: Utilizes 'real price', transformed by volatility-adjusted daily returns, with Hull Moving Average as the trend indicator.
• Automation and Alerts: Automated by script in TradingView, with user-defined settings tailored for entry, exit, and position sizing.
• Manual Trading: Can be manually traded by calculating normalized returns, applying the HMA indicator, and following specified entry and exit conditions.
• Optimization: Backtest to finetune lookback periods, integrate chart pattern recognition, and apply discretionary decisions to override signals.
• Risk Management: Features advanced position sizing inversely correlated with volatility and adjustable stop loss levels based on ATR multiples.
• Improvement Plan: Enhance by incorporating dynamic position sizing, tiered stop-loss system, fundamental and sentiment analysis adjustments.
• Trader Suitability: Well-suited for trend followers, intermediate to advanced traders with risk-averse tendencies, desiring systematic methodologies.
• Trading Style: The strategy favors a disciplined, data-driven approach, with room for manual intervention based on market analysis.