Gold Futures Trend Momentum with Volatility Targeting and Impact-Aware Sizing

Summary

This study tests a gold futures strategy built from smoothed trend and momentum state variables. A rolling walk-forward process trains on a decade of data and tests on successive six-month periods across 2015–2025. The signal is translated into positions using volatility targeting, fractional impact-adjusted Kelly sizing, and ATR-based exits, with trading costs and market impact included.

The document reports strong out-of-sample performance, low reported drawdown, near-zero beta to spot gold, and positive alpha. It also cites bootstrap intervals, SPA tests, and stress tests for latency, reversals, and costs as supporting evidence. However, the excerpt provides no underlying data, detailed implementation rules, or independent replication. Its claims of statistical robustness and billion-dollar capacity therefore cannot be evaluated from this summary alone.

Key ideas

• The strategy combines smoothed trend and momentum signals in gold futures.
• A walk-forward design uses rolling training and six-month test periods.
• Position sizing accounts for volatility, estimated impact, and fractional Kelly sizing.
• ATR-based exits and explicit cost assumptions are part of the trade construction.
• The reported results include low spot-gold beta, though the excerpt does not provide enough detail for independent validation.

Tags

# Forecast-to-Fill: Benchmark-Neutral Alpha and Billion-Dollar Capacity in Gold Futures (2015-2025)


# Forecast-to-Fill: Benchmark-Neutral Alpha and Billion-Dollar Capacity in Gold Futures (2015-2025)









We test whether simple, interpretable state variables-trend and momentum-can generate durable out-of-sample alpha in one of the world's most liquid assets, gold. Using a rolling 10-year training and 6-month testing walk-forward from 2015 to 2025 (2,793 trading days), we convert a smoothed trend-momentum regime signal into volatility-targeted, friction-aware positions through fractional, impact-adjusted Kelly sizing and ATR-based exits. Out of sample, the strategy delivers a Sharpe ratio of 2.88 and a maximum drawdown of 0.52 percent, net of 0.7 basis-point linear cost and a square-root impact term (gamma = 0.02). A regression on spot-gold returns yields a 43 percent annualized return (CAGR approximately 43 percent) and a 37 percent alpha (Sharpe = 2.88, IR = 2.09) at a 15 percent volatility target with beta approximately 0.03, confirming benchmark-neutral performance. Bootstrap confidence intervals ([2.49, 3.27]) and SPA tests (p = 0.000) confirm statistical significance and robustness to latency, reversal, and cost stress. We conclude that forecast-to-fill engineering-linking transparent signals to executable trades with explicit risk, cost, and impact control-can transform modest predictability into allocator-grade, billion-dollar-scalable alpha.

Shown in full with attribution under the source's licence. Licence: abstract CC0

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.