Validating RBOB Futures Mean Reversion
Have you ever watched your RBOB futures backtest show a perfect equity curve, only to see it crumble in live trading? The culprit is often hidden in the...
Have you ever watched your RBOB futures backtest show a perfect equity curve, only to see it crumble in live trading? The culprit is often hidden in the data resolution. When validating mean reversion strategies on volatile energy contracts like gasoline, using low-resolution bar data can mask slippage and spread widening that destroy profitability. A proper RBOB futures backtest requires tick-level precision to capture every price movement during contract rolls and intraday spikes. This is especially critical for mean reversion approaches where entry timing dictates the entire trade outcome. Without granular data, your simulation creates a false sense of security by ignoring the microstructure that defines real execution costs. Mean reversion strategies rely on identifying price extremes and betting on a return to an average level. This approach is highly sensitive to entry precision because profits are often small per trade, while losses can be catastrophic if the trend continues against you.