Golden Opportunities: Extracting Alpha from Gold Futures

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Author: Denis Avetisyan

A systematic strategy combining trend following and rigorous risk management unlocks substantial, out-of-sample returns in gold markets.

This paper details a robust, friction-adjusted model demonstrating billion-dollar capacity and benchmark-neutral alpha generation in gold futures from 2015-2025.

Despite persistent claims of market efficiency, evidence suggests exploitable, albeit modest, predictability in liquid asset classes. This paper, ‘Forecast-to-Fill: Benchmark-Neutral Alpha and Billion-Dollar Capacity in Gold Futures (2015-2025)’, rigorously tests a trend-following strategy applied to gold futures, demonstrating a robust, out-of-sample Sharpe ratio of 2.88 with minimal drawdown, achieved through volatility targeting, friction modeling, and careful capacity constraints. These findings suggest that disciplined implementation—linking transparent signals to executable trades—can unlock substantial alpha, even in highly scrutinized markets. Can forecast-to-fill engineering become a standard for scalable, allocator-grade strategies across diverse asset classes?

Decay and the Signal: Identifying Market Trends

Successful trading hinges on identifying market trends, though signals are often obscured by noise. Discerning genuine patterns from random fluctuations poses a significant challenge for both traders and algorithmic systems. Traditional methodologies struggle to adapt to dynamic conditions, particularly amidst volatility and real-world trading frictions. A robust strategy requires both dependable signal generation and sophisticated risk management; protecting capital is as crucial as identifying opportunities. Every trading plan is a chapter in a temporal record—its true test lies in graceful aging.

Optimizing Exposure: The Calculus of Position Size

Determining appropriate position size is critical for maximizing returns while controlling risk, requiring a nuanced approach beyond simple allocation. Effective capital deployment balances potential profit with inherent loss, varying significantly with market conditions and asset characteristics. The Kelly Criterion offers a theoretical framework for optimal bet sizing, maximizing long-term capital growth. However, practical application is often limited by sensitivity to estimation errors. Friction-Adjusted Kelly refines this model by incorporating transaction costs and market impact, acknowledging that even optimal strategies are constrained by real-world liquidity and information availability.

Adaptive Resilience: Managing Risk and Validating Performance

Effective risk management is paramount for sustained success, requiring robust tools for assessing and controlling potential losses. Strategies must dynamically adapt to changing market conditions. Volatility Targeting adjusts position sizes in response to realized volatility, maintaining consistent risk exposure. Thorough validation, particularly Out-of-Sample Testing, prevents overfitting and enhances generalizability. Recent evaluations demonstrate a Sharpe Ratio of 2.88 and a maximum drawdown of only 0.52%, indicating strong risk-adjusted performance.

Practicality and Persistence: Implementation Considerations

A successful trading strategy demands meticulous attention to practical implementation details, beyond theoretical modeling. Real-world profitability is shaped by factors often overlooked. Transaction costs directly impact net profitability and must be considered when determining optimal position sizes. Market impact, stemming from trade volume, can induce price fluctuations. The proposed approach integrates these considerations for an effective solution. Performance metrics demonstrate a Compound Annual Growth Rate (CAGR) of 2.65% net of realistic transaction costs, with low annual volatility (0.91%) and a 26.67% hit rate. A mean absolute weight of 0.0326 indicates minimal market impact, and an information ratio of 2.09 confirms persistent alpha. Like all structures, even the most elegant trading system ultimately surrenders to time’s currents—its true measure of success lies not merely in profit, but in the grace with which it adapts.

The pursuit of persistent alpha, as detailed within this study of gold futures, inevitably encounters the reality of decaying systems. The research meticulously accounts for transaction costs and capacity limitations – friction that erodes initial advantage. This aligns with the observation that all systems, even those engineered for profit, are subject to the passage of time and the accumulation of errors. As Blaise Pascal noted, “All of humanity’s problems stem from man’s inability to sit quietly in a room alone.” While seemingly unrelated, this speaks to the necessity of disciplined observation and adaptation. Recognizing the inherent limitations—the ‘quiet room’ representing a realistic assessment of market capacity and risk—is a critical first step toward building a strategy that ages gracefully, even amidst inevitable decay and the constant need for refinement. The study’s focus on friction-adjusted Kelly criteria demonstrates an acceptance of this fundamental truth: acknowledging constraints is not a weakness, but a pathway to sustainable performance.

What Lies Ahead?

The demonstrated efficacy of combining trend-following with disciplined risk management in gold futures is, predictably, not a revelation about gold itself. Rather, it’s an observation on the persistent, if ephemeral, nature of state-dependent risk premia. The friction-adjusted Kelly criterion, while offering a pragmatic refinement, doesn’t erase the fundamental truth: any model, no matter how elegantly constructed, operates with incomplete information. Each simplification – each attempt to distill market behavior into quantifiable signals – incurs a future cost, a debt accruing against potential performance.

The capacity constraints highlighted in this work are particularly telling. Alpha, it seems, isn’t a freely available resource; it’s a diminishing return, eroded by its own pursuit. The field now faces the inevitable question: how to anticipate, and perhaps even model, the decay of alpha itself? Focusing solely on signal construction feels increasingly myopic. A more fruitful avenue likely lies in understanding the systemic factors that create these temporary inefficiencies, and the mechanisms by which they are inevitably arbitraged away.

Ultimately, this research underscores a principle applicable across all markets: time isn’t a metric of performance; it’s the medium in which systems evolve, degrade, and ultimately, surrender to entropy. The challenge isn’t to beat the market, but to gracefully navigate its inevitable reversion to equilibrium, acknowledging that even the most robust strategies are merely delaying, not defeating, the onset of decay.

Original article: https://arxiv.org/pdf/2511.08571.pdf

Contact the author: https://www.linkedin.com/in/avetisyan/

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2025-11-12 14:41