FOMO: FLEX Options and Market Outcomes

Paper: arXiv 2610.13044

Authors: Shivesh Prakash, Frank Ferstler, Nicholas Pezolano

Abstract

FLEX options are customized exchange-traded contracts allowing participants to choose nonstandard strikes, expirations, exercise styles, and settlement terms while retaining central clearing. We investigate whether single-name FLEX activity leaves measurable footprints in regular listed-option markets and underlying equities. Using a linked dataset of FLEX consolidations, daily open-interest files, listed-option chains, equity returns, and corporate actions over 250 trading days (March 2025-March 2026) across 41 underlyings and 53 event dates, we document three primary empirical findings: (1) Matched-control difference-in-differences estimates reveal a robust post-event increase in listed-option open interest (beta = 0.3061, p = 0.0042, Benjamini-Hochberg p = 0.0168). (2) FLEX activity is strongly selected into high implied-volatility (IV) environments, concentrated in mid-price underlyings (date-fixed-effect ATM IV premium beta = 0.1235, p = 0.0030). (3) Event-day IV-minus-realized-volatility spreads predict execution-stressed short-straddle returns (beta = 0.0366, p = 0.0100). Short-lived equity return effects (CAR_0 difference of -0.85%, p = 0.0442) do not persist over 1-to-5-day horizons. Overall, FLEX activity serves primarily as an observable marker of institutional volatility demand and open-interest positioning rather than a directional stock-return predictor.

Complexity vs Empirical Score

• Math Complexity: 6.0/10
• Empirical Rigor: 6.0/10 (capped from 8.0: no out-of-sample test; see penalty flags)
• Quadrant: Holy Grail — high math complexity, high empirical rigor

Why this score: The paper employs robust statistical methods like difference-in-differences and matched-control designs on a unique, linked dataset. Its novelty lies in empirically investigating FLEX options’ impact, a previously under-researched area, providing new insights into institutional volatility demand.

Research Flowchart

  flowchart TD
    A[Research Goal: Impact of FLEX Options on Market Outcomes?] --> B{Methodology: Matched-control DiD & Regression Analysis};
    B --> C[Data: FLEX Consolidations, Open Interest, Listed Options, Equity Returns, Corporate Actions];
    C --> D{Computational Processes: Estimate DiD, IV Premium, Return Spreads, CARs};
    D --> E[Outcome 1: Post-event Increase in Listed-Option Open Interest (beta=0.3061)];
    D --> F[Outcome 2: FLEX Activity Selected into High IV & Mid-price Underlyings (IV premium beta=0.1235)];
    D --> G[Outcome 3: Event-day IV-RV Spreads Predict Stressed Short-Straddle Returns (beta=0.0366), Transient Equity CARs];
    E & F & G --> H[Conclusion: FLEX as marker of Institutional Volatility Demand & Open Interest Positioning, Not Directional Stock-Return Predictor];

Cited References (27)

1. Estimating dynamic treatment effects in event studies with heterogeneous treatment effects (2018) — link
2. Difference-in-Differences with multiple time periods (2018) — link
3. Theory of Rational Option Pricing (2015) — link
4. The Joint Cross Section of Stocks and Options (2013) — link
5. Is There Price Discovery in Equity Options (2013) — link
6. The option to stock volume ratio and future returns (2012) — link
7. Deviations from Put-Call Parity and Stock Return Predictability (2010) — link
8. Cross-Section of Option Returns and Volatility (2009) — link

0 of 27 cited works are in the corpus; resolved via arXiv source bundles, Semantic Scholar and OpenAlex. Corpus-wide: 2518 linked papers.