GC's Backtest Function: Reliable Investment Analysis Using Historical Data

The backtest function provided by the GC platform is an essential tool that simulates the past performance of investment strategies, allowing users to review and improve their investment methods. Based on the question, "What if this strategy had been applied over the past N years?", users can verify how their investment strategies actually performed using historical data. This can provide crucial insights for making investment decisions.

Identical Code Path to Real Trading

GC's backtest goes beyond simple simulation, using the exact same code path as real trading. All processes, including market regime judgment, signal validation, and position sizing, align with actual trading, allowing users to evaluate their strategies based on more reliable data. For example, one user who recently conducted a backtest recorded an annual average return of 5% with a maximum drawdown of only 10%. Reliable backtesting like this helps investors refine their strategies using historical data and stay better prepared for future investment decisions.

Providing Various Performance Metrics

When executing a backtest, users can select the period, universe, and strategy options, and the results include account-specific returns, maximum drawdown (MDD), Sharpe ratio, trade frequency, and more. These various performance metrics greatly assist investors in clearly understanding the strengths and weaknesses of their strategies. For instance, if the maximum drawdown is high, it may indicate a need for a more conservative approach. Users have also discovered strategies that record an average return of 7% and a maximum drawdown of 3% through various strategy scenarios.

Caution: Limits of Past Performance

However, since the results of backtesting are based on past performance, they do not guarantee future returns. Factors that can occur in real trading, such as slippage, commissions, and market shocks, may not be perfectly reflected, and there is also the risk of over-optimization. For these reasons, GC applies walk-forward validation and turnover penalties to derive more realistic results. This approach gives users the opportunity to review their strategies more thoroughly.

The GC platform aims to help investors ensure that emotions do not override reason at the moment of judgment. Through backtesting, users can clarify their reasoning and adjust their strategies if necessary. GC's principle of not hiding the basis for judgment provides users with a transparent investment environment.

Investment decisions always hinge on one's own judgment. Participate in the GC Investor Challenge to validate your investment strategy and directly explore the tools needed to make better decisions. On October 1, you can start in just 5 minutes!