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The Implied Volatility Surface and the Cross-Section of Stock Returns: Evidence from Machine Learning

https://doi.org/10.2139/ssrn.6890048
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Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1016/0304-405x(93)90023-5openalex-snapshot
Common risk factors in the returns on stocks and bonds
inferredcites →https://doi.org/10.1016/0893-6080(89)90020-8openalex-snapshot
Multilayer feedforward networks are universal approximators
inferredcites →https://doi.org/10.1016/j.jempfin.2024.101538openalex-snapshot
Pooling and winsorizing machine learning forecasts to predict stock returns with high-dimensional data
inferredcites →https://doi.org/10.1016/j.jempfin.2025.101598openalex-snapshot
Is machine learning a necessity? A regression-based approach for stock return prediction
inferredcites →https://doi.org/10.1016/j.jfineco.2009.11.004openalex-snapshot
O/S: The relative trading activity in options and stock
inferredcites →https://doi.org/10.1016/j.jfineco.2010.08.011openalex-snapshot
Jump risk, stock returns, and slope of implied volatility smile
inferredcites →https://doi.org/10.1016/j.jfineco.2012.05.008openalex-snapshot
The option to stock volume ratio and future returns
inferredcites →https://doi.org/10.1016/j.jfineco.2014.10.010openalex-snapshot
A five-factor asset pricing model
inferredcites →https://doi.org/10.1016/j.jfineco.2015.02.010openalex-snapshot
Tail risk premia and return predictability
inferredcites →https://doi.org/10.1016/j.jfineco.2015.08.019openalex-snapshot
Why does the option to stock volume ratio predict stock returns?
inferredcites →https://doi.org/10.1016/j.jfineco.2021.08.017openalex-snapshot
Machine learning in the Chinese stock market
inferredcites →https://doi.org/10.1016/j.jfineco.2025.104153openalex-snapshot
Why does options market information predict stock returns?
inferredcites →https://doi.org/10.1017/s002210901000013xopenalex-snapshot
Deviations from Put-Call Parity and Stock Return Predictability
inferredcites →https://doi.org/10.1017/s0022109010000220openalex-snapshot
What Does the Individual Option Volatility Smirk Tell Us About Future Equity Returns?
inferredcites →https://doi.org/10.1086/296025openalex-snapshot
Prices of State-Contingent Claims Implicit in Option Prices
inferredcites →https://doi.org/10.1093/rfs/13.2.433openalex-snapshot
Recovering Risk Aversion from Option Prices and Realized Returns
inferredcites →https://doi.org/10.1093/rfs/16.1.0101openalex-snapshot
Stock Return Characteristics, Skew Laws, and the Differential Pricing of Individual Equity Options
inferredcites →https://doi.org/10.1093/rfs/hhaa009openalex-snapshot
Empirical Asset Pricing via Machine Learning
inferredcites →https://doi.org/10.1093/rfs/hhg002openalex-snapshot
Delta-Hedged Gains and the Negative Market Volatility Risk Premium
inferredcites →https://doi.org/10.1093/rfs/hhj024openalex-snapshot
The Information in Option Volume for Future Stock Prices
inferredcites →https://doi.org/10.1093/rfs/hhn038openalex-snapshot
Variance Risk Premiums
inferredcites →https://doi.org/10.1093/rfs/hhp005openalex-snapshot
Demand-Based Option Pricing
inferredcites →https://doi.org/10.1093/rfs/hhu068openalex-snapshot
Digesting Anomalies: An Investment Approach
inferredcites →https://doi.org/10.1093/rfs/hhz075openalex-snapshot
A Bound on Expected Stock Returns
inferredcites →https://doi.org/10.1093/rfs/hhz123openalex-snapshot
Dissecting Characteristics Nonparametrically
inferredcites →https://doi.org/10.1109/5.726791openalex-snapshot
Gradient-based learning applied to document recognition
inferredcites →https://doi.org/10.1111/0022-1082.00352openalex-snapshot
Expected Option Returns
inferredcites →https://doi.org/10.1111/0022-1082.194060openalex-snapshot
Option Volume and Stock Prices: Evidence on Where Informed Traders Trade
inferredcites →https://doi.org/10.1111/j.1467-9868.2005.00503.xopenalex-snapshot
Regularization and Variable Selection Via the Elastic Net
inferredcites →https://doi.org/10.1111/j.1540-6261.1997.tb03808.xopenalex-snapshot
On Persistence in Mutual Fund Performance
inferredcites →https://doi.org/10.1111/j.1540-6261.2011.01695.xopenalex-snapshot
Tails, Fears, and Risk Premia
inferredcites →https://doi.org/10.1111/j.1540-6261.2012.01795.xopenalex-snapshot
Ex Ante Skewness and Expected Stock Returns
inferredcites →https://doi.org/10.1111/jofi.12181openalex-snapshot
The Joint Cross Section of Stocks and Options
inferredcites →https://doi.org/10.1111/jofi.12220openalex-snapshot
Aggregate Jump and Volatility Risk in the Cross‐Section of Stock Returns
inferredcites →https://doi.org/10.1111/jofi.12778openalex-snapshot
What Is the Expected Return on a Stock?
inferredcites →https://doi.org/10.1111/jofi.12883openalex-snapshot
Taming the Factor Zoo: A Test of New Factors
inferredcites →https://doi.org/10.1111/jofi.13268openalex-snapshot
(Re‐)Imag(in)ing Price Trends
inferredcites →https://doi.org/10.1214/aos/1013203451openalex-snapshot
Greedy function approximation: A gradient boosting machine.
inferredcites →https://doi.org/10.1287/mnsc.1090.1063openalex-snapshot
Volatility Spreads and Expected Stock Returns
inferredcites →https://doi.org/10.1287/mnsc.2015.2379openalex-snapshot
What Does Risk-Neutral Skewness Tell Us About Future Stock Returns?
inferredcites →https://doi.org/10.1287/mnsc.2019.3520openalex-snapshot
Information Content of Aggregate Implied Volatility Spread
inferredcites →https://doi.org/10.2307/1913610openalex-snapshot
A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix
inferredcites →https://doi.org/10.2307/2348005openalex-snapshot
A Note on the Use of Principal Components in Regression
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