Adaptive Trend Selector

The Adaptive Trend Selector is a comprehensive trend-following tool designed to automatically identify the optimal moving average crossover strategy. It features adjustable parameters and an integrated backtester that delivers institutional-grade insights into the recommended strategy. The model continuously adapts to new data in real time by evaluating multiple moving average combinations, determining the best performing lengths, and presenting the backtest results in a clear, color-coded table that benchmarks performance against the buy-and-hold strategy.

At its core, the model systematically backtests a wide range of moving average combinations to identify the configuration that maximizes the selected optimization metric. Users can choose to optimize for absolute returns or risk-adjusted returns using the Sharpe, Sortino, or Calmar ratios. Alternatively, users can enable manual optimization to test custom fast and slow moving average lengths and view the corresponding backtest results. The label displays the Compounded Annual Growth Rate (CAGR) of the strategy, with the buy-and-hold CAGR in parentheses for comparison. The table presents the backtest results based on the fast and slow lengths displayed at the top:

• Sharpe = CAGR per unit of standard deviation.
  
• Sortino = CAGR per unit of downside deviation.
  
• Calmar = CAGR relative to maximum drawdown.
  
• Max DD = Largest peak-to-trough decline in value.
  
• Beta (β) = Return sensitivity relative to buy-and-hold.
  
• Alpha (α) = Excess annualized risk-adjusted returns.
  
• Win Rate = Ratio of profitable trades to total trades.
  
• Profit Factor = Total gross profit per unit of losses.
  
• Expectancy = Average expected return per trade.
  
• Trades/Year = Average number of trades per year.
  

This indicator is designed with flexibility in mind, enabling users to specify the start date of the backtesting period and the preferred moving average strategy. Supported strategies include the Exponential Moving Average (EMA), Simple Moving Average (SMA), Wilder’s Moving Average (RMA), Weighted Moving Average (WMA), and Volume-Weighted Moving Average (VWMA). To minimize overfitting, users can define constraints such as a minimum and maximum number of trades per year, as well as an optional optimization margin that prioritizes longer, more robust combinations by requiring shorter-length strategies to exceed this threshold. The table follows an intuitive color logic that enables quick performance comparison against buy-and-hold (B&H):

• Sharpe = Green indicates better than B&H, while red indicates worse.
  
• Sortino = Green indicates better than B&H, while red indicates worse.
  
• Calmar = Green indicates better than B&H, while red indicates worse.
  
• Max DD = Green indicates better than B&H, while red indicates worse.
  
• Beta (β) = Green indicates better than B&H, while red indicates worse.
  
• Alpha (α) = Green indicates above 0%, while red indicates below 0%.
  
• Win Rate = Green indicates above 50%, while red indicates below 50%.
  
• Profit Factor = Green indicates above 2, while red indicates below 1.
  
• Expectancy = Green indicates above 0%, while red indicates below 0%.
  

In summary, the Adaptive Trend Selector is a powerful tool designed to help investors make data-driven decisions when selecting moving average crossover strategies. By optimizing for risk-adjusted returns, investors can confidently identify the best lengths using institutional-grade metrics. While results are based on the selected historical period, users should be mindful of potential overfitting, as past results may not persist under future market conditions. Since the model recalibrates to incorporate new data, the recommended lengths may evolve over time.