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A factor model for option returns
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AI
DOI：10.1016/j.jfineco.2021.12.007.png)
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Due to their short lifespans and migrating moneyness, options are notoriously difficult to study with the factor models commonly used to analyze the risk-return trade-off in other asset classes. Instrumented principal components analysis solves this problem by tracking contracts in terms of their pricing-relevant characteristics via time-varying latent factor loadings. We find that a model with three latent factors prices the cross-section of option returns and explains more than 85% of the variation in a panel of monthly S&P 500 option returns from 1996 to 2017. In particular, we show that the IPCA factors can be rationalized via an economically plausible three-factor model consisting of a level, slope and skew factor. Finally, out-of-sample trading strategies based on insights from the IPCA model have significant alpha over previously studied option strategies. (c) 2022 Elsevier B.V. All rights reserved.
Keyword:
Option return
Factor model
Return predictability
IPCA
期刊
IF:
12
论文数:
3.8K
被引数:
5.5W
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