@article {Figlewski29,
author = {Figlewski, Stephen},
title = {What Goes into Risk-Neutral Volatility? Empirical Estimates of Risk and Subjective Risk Preferences },
volume = {43},
number = {1},
pages = {29--42},
year = {2016},
doi = {10.3905/jpm.2016.43.1.029},
publisher = {Institutional Investor Journals Umbrella},
abstract = {Under Black{\textendash}Scholes (BS) assumptions, empirical volatility and risk-neutral volatility are given by a single parameter that captures all aspects of risk. Inverting the model to extract implied volatility from an option{\textquoteright}s market price gives the market{\textquoteright}s forecast of future empirical volatility. But real world returns are not lognormal, volatility is stochastic, and arbitrage is limited; thus, option prices embed both the market{\textquoteright}s estimate of the empirical returns distribution and also investors{\textquoteright} risk attitudes, including possibly distinct preferences over different volatility-related aspects of the returns process, such as tail risk. All these influences are reflected in the risk-neutral density (RND), which can be extracted from option prices without requiring restrictive assumptions from a pricing model. The author computes daily RNDs for the S\&P 500 Index over 15 years and finds that risk-neutral volatility is strongly influenced both by investors{\textquoteright} projections of future realized volatility and by the risk-neutralization process. Several significant variables are connected in different ways to realized volatility, such as the daily trading range and tail risk; others reflect risk attitudes, such as the level of investor confidence and the size of recent volatility forecast errors.},
issn = {0095-4918},
URL = {https://jpm.pm-research.com/content/43/1/29},
eprint = {https://jpm.pm-research.com/content/43/1/29.full.pdf},
journal = {The Journal of Portfolio Management}
}