Our Methodology
Transparency is a core value. Here is exactly how we source data, run backtests, control for biases, and measure performance.
Data Sources
We use institutional-quality data feeds with point-in-time accuracy, covering 8 markets worldwide.
| Market | Data Provider | Coverage |
|---|---|---|
| US Equities | NYSE, NASDAQ via premium data feeds | Full S&P 500, NASDAQ 100, and 3,000+ additional tickers |
| Hong Kong Equities | HKEX official data | HSI constituents, HSCEI, GEM board, all listed securities |
| China A-Shares | SSE, SZSE licensed data | CSI 300, CSI 500, full A-share universe |
| Taiwan Equities | TWSE, TPEx feeds | TAIEX constituents and all listed securities |
| Korean Equities | KRX market data | KOSPI 200, KOSDAQ 150, and broader universe |
| Cryptocurrency | Multiple exchange APIs | Top 100 by market cap, major trading pairs |
| Commodities | CME, LME, ICE data | Gold, Silver, Oil, Natural Gas, Agricultural |
| Global ETFs | Multi-exchange ETF data | 500+ ETFs across all asset classes and geographies |
Backtesting Methodology
Our backtesting engine follows a rigorous, multi-step process designed to produce realistic results.
Walk-Forward Analysis
Each strategy is validated through a walk-forward framework. The historical data is split into rolling in-sample (training) and out-of-sample (validation) windows. Parameters are optimized on in-sample data, then tested on unseen out-of-sample data. This prevents overfitting and provides a realistic estimate of future performance.
In-Sample (70%) → Optimize → Out-of-Sample (30%) → Validate → Roll Forward → RepeatTransaction Cost Modeling
All backtests incorporate realistic transaction costs including brokerage commissions, exchange fees, stamp duty (for HK and UK markets), and estimated slippage. Market impact is modeled using historical volume data -- larger positions in less liquid securities incur higher estimated costs.
Cost = Commission + Exchange Fee + Stamp Duty + Slippage(Volume, Spread)Position Sizing
Default backtests use equal-weight position sizing. Advanced reports include alternative sizing methods: volatility-targeting (risk parity), Kelly criterion, and maximum diversification. Each method's assumptions and limitations are clearly documented in the strategy report.
Benchmark Comparison
Every strategy is benchmarked against the appropriate market index and a risk-free rate. We report alpha, beta, tracking error, and information ratio to help you assess whether a strategy genuinely adds value or is merely taking on market risk.
Bias Controls
We take bias control seriously. Here are the specific biases we address and how we mitigate them.
Survivorship Bias
CriticalWe use point-in-time databases that include delisted securities. Our universe at each backtest date includes only securities that were actually tradeable at that time, preventing the inflation of returns by excluding companies that failed or were acquired.
Look-Ahead Bias
CriticalAll data used in signal generation is strictly timestamped. Financial statement data uses the filing date (not the period end date) to ensure strategies only act on information that was publicly available at the time of the trade decision.
Data-Snooping Bias
HighWe employ walk-forward analysis with expanding or rolling windows. Strategy parameters are optimized on in-sample data and validated on out-of-sample data to prevent overfitting to historical patterns.
Transaction Cost Bias
HighAll backtests include realistic transaction costs: brokerage commissions, exchange fees, stamp duty (where applicable), and estimated market impact based on historical volume and spread data.
Selection Bias
MediumWe report all strategies we test, not just the ones that perform well. Each strategy report includes a clear disclaimer about the number of strategies tested and the risk of multiple comparison bias.
Performance Metrics
Every strategy report includes 50+ metrics across five categories.
Return Metrics
- Total Return
- Annualized Return (CAGR)
- Monthly Returns
- Rolling Returns (1Y, 3Y, 5Y)
- Risk-Adjusted Return
- Excess Return vs Benchmark
Risk Metrics
- Annualized Volatility
- Maximum Drawdown
- Drawdown Duration
- Value at Risk (95%, 99%)
- Conditional VaR (Expected Shortfall)
- Downside Deviation
- Ulcer Index
Risk-Adjusted Ratios
- Sharpe Ratio
- Sortino Ratio
- Calmar Ratio
- Information Ratio
- Treynor Ratio
- Omega Ratio
Trading Metrics
- Win Rate
- Profit Factor
- Average Win / Average Loss
- Maximum Consecutive Losses
- Turnover Rate
- Average Holding Period
Statistical Tests
- T-Statistic of Returns
- Skewness & Kurtosis
- Jarque-Bera Test
- Autocorrelation Analysis
- Regime Analysis
- Monte Carlo Simulation
Questions About Our Methodology?
We welcome scrutiny. Reach out to our research team for detailed documentation.