Cross-Sectional Momentum: Results from Commodities and Equities

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Momentum strategies can be divided into two categories: time series and cross-sectional. In a previous newsletter, I discussed time series momentum. In this edition, I focus on cross-sectional momentum strategies.

In this issue:

• Latest Posts

• Cross-Sectional Momentum in the Commodity Market

  • Findings

• Profitability of Cross-Sectional Momentum Strategy

  • Findings

• Closing Thoughts

• Educational Video

  • Momentum explained and time-series and cross-secti …

• Volatility Weekly Recap

• Around the Quantosphere

Latest Posts

• Predictive Information of Options Volume in Equity Markets (11 min)

• The Impact of Market Regimes on Stop Loss Performance (12 min)

• The Limits of Out-of-Sample Testing (12 min)

• Sentiment as Signal: Forecasting with Alternative Data and Generative AI (12 min)

• Behavioral Biases and Retail Options Trading (10 min)

Cross-Sectional Momentum in the Commodity Market

Momentum trading is often divided into 2 categories: time-series momentum and cross-sectional momentum. Time-series based trading strategies generate trading signals based on the asset’s past returns. A typical time-series trading strategy usually involves buying assets with positive trend signals and selling those with negative trend signals. In contrast, cross-sectional trading strategies generate trading signals based on the relative performance of assets. A typical cross-sectional trading strategy involves buying assets with the highest-ranked trend signals and selling those with the lowest-ranked trend signals. So basically, this is a relative value strategy.

Reference [1] examined trend trading in the commodity market from the cross-sectional momentum perspective. The authors conducted a study on a portfolio of 35 commodity futures.

Findings

• The study introduces a trend factor that uses short-, intermediate-, and long-run moving averages of settlement prices in commodity futures markets.

• The trend factor generates statistically and economically significant returns during the post-financialization period (2004–2020).

• It outperforms the momentum factor by more than nine times in the Sharpe ratio and carries less downside risk.

• Unlike the momentum factor, which delivers insignificant returns in the sample, the trend factor consistently generates large positive returns.

• The trend factor cannot be explained by existing multifactor asset pricing models.

• It also provides a significant positive risk premium, confirming its economic relevance.

• The trend factor is correlated with funding liquidity, as measured by the TED spread.

• Overall, the findings highlight the economic value of using historical price information in commodity futures markets beyond traditional momentum strategies.

In short, cross-sectional momentum exists in the commodity market, and it is possible to construct a profitable trend trading strategy.

Reference

[1] Han, Yufeng and Kong, Lingfei, A Trend Factor in Commodity Futures Markets: Any Economic Gains From Using Information Over Investment Horizons? SSRN 3953845

Profitability of Cross-Sectional Momentum Strategy

Reference [2] examines the profitability of cross-sectional momentum strategies over the past decades

Findings

• The study investigates how different definitions of cross-sectional momentum affect the performance of long-short momentum strategies under varying market conditions.

• A long-short momentum portfolio buys stocks with strong past performance and shorts stocks with weak past performance.

• Standard long-short momentum strategies have delivered declining returns in recent decades, leading researchers and practitioners to search for solutions.

• A key weakness of momentum strategies is their tendency to experience “crashes,” where large gains are followed by sudden and substantial losses.

• The thesis proposes a method to mitigate crash risk, conditional on market states.

• While the literature offers complex methods for constructing long-short portfolios, the study demonstrates that relatively simple adjustments can meaningfully improve outcomes.

• Techniques such as volatility scaling and adjusting long and short positions based on market state enhance performance.

• These adjustments restore the robustness of the momentum premium and improve the risk-return profile of the strategy.

In short, the paper concludes that the profitability of cross-sectional momentum strategies has diminished. The author subsequently proposes an approach to enhance the strategy’s returns.

By applying techniques such as volatility scaling and adjusting long and short positions based on the market state we can significantly enhance the efficacy of the momentum strategy, restoring its former robustness.

Reference

[2] Pyry Pohjantähti, Revisiting (Revitalizing) Momentum, 2024, Aalto University School of Business

Closing Thoughts

In summary, both studies highlight that momentum remains useful but requires refinement. The first shows that a trend factor in commodity futures, built on moving averages, delivers strong returns and outperforms traditional momentum benchmarks. The second finds that cross-sectional momentum, though weakened and crash-prone, can be improved with simple adjustments like volatility scaling and conditioning on market states. Together, they show that momentum strategies are still effective when adapted to market conditions.

Educational Video

Momentum explained and time-series and cross-sectional momentum defined

In this video, P. Docherty explains momentum as a simple yet effective investment strategy based on past returns. Two main approaches are covered: time-series momentum, which uses an asset’s own return history to forecast future performance, and cross-sectional momentum, which ranks assets relative to one another over a 3–12 month window and goes long recent winners while shorting losers.

Evidence from the U.S., Australia, and global markets shows that momentum strategies deliver abnormal returns, even after adjusting for risk, and extend beyond equities into commodities, currencies, and bonds. The video also highlights variations like the 52-week high strategy, which uses simple heuristics to capture momentum effects. While effective in intermediate horizons, momentum returns reverse over longer periods, suggesting mean reversion.

Despite this limitation and occasional drawdowns, the persistence of momentum across assets and markets has made it one of the most widely studied and applied strategies in finance.

Volatility Weekly Recap

The figure below shows the term structures for the VIX futures (in colour) and the spot VIX (in grey).

The S&P 500 began the week quietly, but volatility picked up on Tuesday as weakness in the tech sector weighed on the market. Selling continued through Thursday, before reversing sharply on Friday after Fed Chair Powell suggested the Fed may be considering interest rate cuts. This sent stocks higher, erasing earlier losses by the week’s close.

For the week, the S&P 500 gained 0.27% while the Nasdaq fell 0.58%. Oil prices rebounded after the previous week’s decline, and gold posted a modest bounce. Bitcoin pulled back for most of the week but rallied on Friday following Powell’s comments.

Volatility rose until Thursday, then eased on Friday, with both spot and VIX futures returning to contango and the roll yield remaining firmly positive. Notably, while the roll yield had been in steady decline for about three years, it has shown a new upward trend over the past two months. The question is whether this marks the start of a sustained recovery.

Around the Quantosphere

• The highest-paying jobs in crypto to watch in 2025 (tradingview)

• Students on the best cheap quant masters are earning $25k per month on their internships (efinancialcareers)

• Optiver opens NYC office to challenge Citadel Securities and Jane Street (bloomberg)

• Investors push back on multi-strategy hedge fund fee structures (hedgeweek)

• Man Group sparks backlash over non-compete agreements (ft)

• Hedge funds are shorting Ethereum in record numbers—short squeeze coming? (mitrade)

• Boom in bespoke ETFs drives growth of niche a-la-carte options (bloomberg)

• A high-frequency trading firm is offering its interns $425k to come back as OpenAI looms (efinancialcareers)

Disclaimer

This newsletter is not investment advice. It is provided solely for entertainment and educational purposes. Always consult a financial professional before making any investment decisions.

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