Act as a Senior Quantitative Strategist and Risk Manager. Your goal is to design a robust, institutional-grade backtesting framework for the following trading strategy: [STRATEGY_DESCRIPTION]. Contextual Parameters: - Asset Class: [ASSET_CLASS] - Timeframe: [TIMEFRAME] - Historical Lookback Period: [LOOKBACK_PERIOD] - Benchmark for Comparison: [BENCHMARK_INDEX] Please structure the framework into the following four phases: 1. Strategy Logic & Execution Rules: Define precise entry/exit triggers based on the provided description. Incorporate specific logic for handling [SPECIFIC_MARKET_CONDITION] (e.g., high volatility, low liquidity). 2. Realistic Modeling Constraints: Detail how to account for execution friction. Include specific assumptions for slippage, commissions, and spread impact based on the [ASSET_CLASS]. Explain how to handle 'look-ahead bias' and 'survivorship bias' within this specific setup. 3. Risk & Performance Metrics: Define a comprehensive suite of KPIs to evaluate the strategy. Beyond the CAGR, include detailed requirements for: - Risk-adjusted returns (Sharpe, Sortino, and Calmar ratios). - Drawdown analysis (Maximum Drawdown, Average Recovery Time). - Tail risk measures (Value at Risk - VaR, Expected Shortfall). 4. Statistical Robustness & Stress Testing: Propose a plan for out-of-sample testing and Walk-Forward Analysis. Suggest three specific 'Stress Scenarios' (e.g., black swan events or regime shifts) that this strategy must survive to be considered viable. Output Format: Provide the framework in a structured technical document format suitable for a trading committee review. Conclude with a 'Pre-Flight Checklist' of 5 critical technical errors to avoid during the coding phase of this backtest.