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

ArXiv ID: 2511.08571 “View on arXiv”

Authors: Mainak Singha, Jose Aguilera-Toste, Vinayak Lahiri

Abstract

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.

Keywords: Momentum Strategy, Systematic Trading, Kelly Criterion, Volatility Targeting, Algorithmic Execution

Complexity vs Empirical Score

  • Math Complexity: 4.5/10
  • Empirical Rigor: 9.2/10
  • Quadrant: Street Traders
  • Why: The paper is highly data-driven with a detailed walk-forward backtest, specific cost/impact modeling, and robust statistical validation, but the mathematics, while precise, is relatively accessible (mainly Kelly sizing and basic signal smoothing) rather than conceptually dense or advanced.
  flowchart TD
    A["Research Goal<br>Identify durable, interpretable alpha in liquid gold futures using simple state variables"] --> B["Data & Methodology<br>2015-2025 OOS Walk-Forward<br>Rolling 10yr Train / 6mo Test<br>2,793 Trading Days"]
    B --> C["Signal Generation<br>Smoothed Trend-Momentum Regime State"]
    C --> D["Position Sizing & Execution<br>Volatility-Targeted (15%)<br>Fractional Kelly Sizing<br>ATR-based Exits<br>Impact-Adjusted Costs: 0.7bps + sqrt(gamma=0.02)"]
    D --> E["Performance & Statistical Validation<br>Sharpe 2.88, Max DD 0.52%<br>CAGR ~43%, Alpha 37% (Beta ~0.03)<br>Bootstrap CI [2.49, 3.27"], SPA p=0.000]
    E --> F["Key Finding<br>Forecast-to-Fill engineering creates allocator-grade, billion-dollar scalable alpha<br>from modest predictability"]