Cross-sectional momentum in equities is one of the most extensively studied and most stubborn anomalies in the empirical finance literature. Since Jegadeesh and Titman’s 1993 demonstration that recent winners outperform recent losers, the effect has been replicated across countries, asset classes, and decades, and survived a great deal of transaction-cost adjustment. The natural follow-on question, asked many times and answered with varying degrees of rigor, is whether an analogous cross-sectional momentum exists in the single-stock options market — and if so, whether it survives the substantially higher implementation costs that listed equity options carry.
Framing the question
We use the term “options momentum” loosely to refer to a family of related signals: persistence in the implied-volatility level relative to the realized, persistence in short-dated implied-volatility skew, persistence in the delta-hedged option return itself, and the closely related implied-realized spread highlighted by Goyal and Saretto (2009). Each of these has a measurable cross-sectional structure in single-stock options, and each has at least some published evidence of forward predictive power. The unanswered question is not whether such effects exist in sample but whether they are capturable by an investor who must transact in the actual listed options market and bear the corresponding bid-ask, exchange, and clearing costs.
That qualifier matters. In equities, the round-trip cost on a liquid US large-cap is typically a small handful of basis points; capturing a 2–3% annualized cross-sectional spread on a well-diversified book is mechanically feasible with disciplined execution. In single-stock options the round-trip cost on comparable names — measured as a fraction of the option premium, not the underlying notional — is routinely an order of magnitude larger. A signal that produces a 30 basis-point monthly cross-sectional spread on the underlying may be completely inverted after costs once expressed through option positions.
Where the standard methodology breaks
The most common research setup in the academic literature ranks option-based signals across a name universe, forms long-short portfolios at a monthly or weekly cadence, and reports equal-weighted or notional-weighted returns. The two failure modes we see most often in subsequent live testing are:
First, the universe filter is applied with hindsight. A study that requires options to have at least some minimum open interest and a liquid continuous quote tends to be performed on the names that eventually became liquid, not on the names that were liquid in real time. The bias this introduces is systematic and non-trivially in favor of the documented effect.
Second, the cost model is too coarse. Half-spread is a defensible first approximation in equity research; in options it understates the practical cost of moving meaningful size, often by a factor between two and five. Once realistic implementation shortfall is modeled — including price impact when more than a small fraction of displayed liquidity is consumed at a given strike and expiry — the gross-to-net erosion is severe.
What we believe survives
Our internal work suggests that a residual cross-sectional effect does survive realistic costs, but only on a relatively narrow universe and with strict capacity discipline. Three ingredients matter:
The first is universe construction that is dynamic and forward-looking. Names enter and leave the eligible set based on real-time liquidity metrics applied at the moment of portfolio formation, not on look-ahead filtering.
The second is signal aggregation across multiple horizons and measurement choices. Single-signal versions of the effect are fragile; ensemble versions that combine implied-volatility level, term-structure slope, skew, and delta-hedged return are substantially more robust, in part because the noise sources decorrelate across measurement choices.
The third is hard capacity sizing. The capturable spread shrinks quickly as the deployed book grows, and there is no shortcut around this. We size each strategy below the level at which transaction-cost analysis flags meaningful slippage, and we close capacity rather than let alpha decay.
Implications for portfolio construction
The implication for a multi-strategy book is not that single-stock options momentum should be ignored — it shouldn’t — but that it should be sized as the constrained, capacity-limited program it is, rather than scaled with the same risk budgets one might apply to a comparable equity book. A well-implemented options-momentum sleeve typically contributes a modest but stable component of overall returns, decorrelated from the equity sleeves it sits alongside. Treated that way, it earns its place. Treated as a primary alpha engine to be scaled, it disappoints.
A note on ongoing work
We continue to investigate whether the effect survives in shorter-dated weekly options, where the cross-sectional microstructure differs materially from the monthly cycle the academic literature has historically studied. Preliminary indications suggest the answer depends sensitively on how the transition between monthly and weekly expiries is handled in the signal. We expect to publish further notes on this topic later in 2026.
References. Jegadeesh, N., and S. Titman (1993). Returns to buying winners and selling losers: Implications for stock market efficiency. Journal of Finance. · Goyal, A., and A. Saretto (2009). Cross-section of option returns and volatility. Journal of Financial Economics. · Cao, J., and B. Han (2013). Cross-section of option returns and idiosyncratic stock volatility. Journal of Financial Economics.
This research note is provided for informational purposes only and does not constitute investment, legal, tax, or accounting advice. Nothing herein constitutes an offer to sell or a solicitation of an offer to buy any security. See our disclosures for the full notice.