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Recovering Probability Distributions from Option Prices

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TLDR
In this paper, the authors derived underlying asset risk-neutral probability distributions of European options on the S&P 500 index and used nonparametric methods to choose probabilities which minimize an objective function subject to requiring that the probabilities are consistent with observed option and underlying asset prices.
Abstract
This paper derives underlying asset risk-neutral probability distributions of European options on the S&P 500 index. Nonparametric methods are used to choose probabilities which minimize an objective function subject to requiring that the probabilities are consistent with observed option and underlying asset prices. Alternative optimization specifications produce approximately the same implied distributions. A new and fast optimization technique for estimating probability distributions based on maximizing the smoothness of the resulting distribution is proposed. Since the crash, the risk-neutral probability of a three (four) standard deviation decline in the index (about-36% (-46%) over a year) is about 10 (100) times more likely than under the assumption of lognormality.

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Negotiating a Market, Performing Theory: The Historical Sociology of a Financial Derivatives Exchange

TL;DR: The Chicago Board Options Exchange (CBOW) as discussed by the authors is one of the most popular derivatives markets in the US, and it has been shown that social interaction in such markets generates trust, permits solution of collective action problems, and affects pricing.
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Recovering Risk Aversion from Option Prices and Realized Returns

TL;DR: The authors empirically derive risk aversion functions implied by option prices and realized returns on the S&P 500 index simultaneously, showing that the risk aversion function dramatically change shape around the 1987 crash.
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Ex Ante Skewness and Expected Stock Returns

TL;DR: This paper used a sample of option prices and the method of Bakshi, Kapadia and Madan (2003) to estimate the ex ante higher moments of the underlying individual securities' risk-neutral returns distribution.
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The Cross-Section of Volatility and Expected Returns

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Density Forecasting: A Survey

TL;DR: A density forecast of the realization of a random variable at some future time is an estimate of the probability distribution of the possible future values of that variable as mentioned in this paper, i.e., the probability of a variable being realized at a given time.