Options
Tobias Wiest
A Bayesian Stochastic Discount Factor for the Cross-Section of Individual Equity Options
Option Factor Momentum
2024-02-16
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Käfer, Niclas
,
Mörke, Mathis
,
Weigert, Florian
,
Wiest, Tobias
We utilize Bayesian model averaging to estimate a stochastic discount factor (SDF) for single-stock options. A Bayesian model averaging SDF outperforms reduced-form benchmark models in-sample and out-of-sample in pricing option return anomalies and portfolios. We document that the SDF is dense in characteristics with the impliedrealized volatility spread, option return momentum, and jump risk emerging as the most likely included factors. Noteworthy, we find that (i) our results remain largely robust after controlling for transaction costs and (ii) characteristics linked to behavioral biases gain in importance for options with high retail trading volume.
2023-04-13
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Niclas Robin Käfer
,
Mathis Rudolf Werner Mörke
,
Tobias Wiest
We document profitable cross-sectional and time-series momentum in 56 option factors constructed from monthly sorts on daily delta-hedged option positions. Option factor returns are highly autocorrelated, but momentum profits of strategies with longer formation periods are mainly driven by high mean returns that persistently differ across factors. Momentum effects are the strongest in the factors' largest principal components, consistent with findings for stock factor momentum. Finally, we find a new form of momentum in options markets: momentum in single delta-hedged option returns. Option factor momentum fully subsumes option momentum, whereas option momentum cannot explain option factor momentum. Our findings provide insights into the channels that drive option momentum and have implications for designing profitable option trading strategies.