✦ Backtesting Methodology · How We Build and Evaluate Strategies
Transparent Strategy Development
This page explains how WealthSignal develops, backtests, and evaluates algorithm strategies using paper-trading simulations against historical market data. Our methodology prioritizes transparency and rigorous testing practices.
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Trading days of simulation data
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Core methodology principles
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Risk metrics tracked per strategy
Important Disclosure: All strategy evaluations are based on hypothetical paper-trading simulations. Simulated results do not represent actual trading or investment returns. Past simulated performance does not guarantee future results. All investing involves risk of loss, including possible loss of principal.
📅 Simulation Period
January 2024 - Present
Paper-trading simulation data
📊 Strategies Evaluated
Multiple
Algorithm strategies tested
🔬 Bias Controls
4 Types
Survivorship, look-ahead, slippage, cherry-picking
How Backtesting Works
Understanding our strategy evaluation process
Backtesting is the process of applying a trading strategy to historical market data to evaluate how it would have performed. It is a standard tool in quantitative finance for strategy development and research.
What backtesting can tell you: Whether a strategy's logic is internally consistent, how it behaves across different market conditions, and what its risk characteristics look like historically.
What backtesting cannot tell you: How a strategy will perform in the future. Historical results -- even rigorous ones -- do not predict future outcomes. Market conditions change, and past patterns may not repeat.
Paper trading vs. live trading: WealthSignal strategies are evaluated in a paper-trading environment using real-time market prices. Paper trading removes the risk of real capital loss during evaluation, but does not account for all real-world factors such as liquidity constraints, market impact, and execution timing differences.
All strategy evaluations are hypothetical. Simulated results do not reflect actual trading. Past simulated performance does not guarantee future results.
What We Measure
Key metrics used in strategy evaluation
Risk-Adjusted Returns
Metrics like the Sortino and Calmar ratios help evaluate whether a strategy's returns are proportionate to the risk taken, rather than looking at returns in isolation.
Drawdown Analysis
Maximum drawdown measures the largest peak-to-trough decline during a simulation period. This helps understand worst-case scenarios within the tested timeframe.
Volatility Measurement
Annualized volatility (standard deviation of returns) quantifies how much a strategy's value fluctuates. Higher volatility means larger swings in both directions.
Win/Loss Ratios
The ratio of average gains to average losses across individual trades. This helps assess whether profitable trades sufficiently offset losing ones in simulation.
Understanding Risk Metrics
Key concepts used in quantitative strategy evaluation
Our Testing Methodology
Principles that guide our strategy evaluation
WealthSignal strategies are evaluated in paper-trading mode using live market prices at strategy issuance time, with realistic slippage assumptions (0.1% per trade). Simulated results do not guarantee live trading outcomes. All investing involves risk of loss.
Common Backtesting Pitfalls
What to watch out for when evaluating any strategy's simulated results