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- W2102951738 abstract "One of the central goals in finance is to find better models for pricing and hedging financial derivatives such as call and put options. We present a new semi-nonparametric approach to risk-neutral density extraction from option prices, which is based on an extension of the concept of mixture density networks. The central idea is to model the shape of the risk-neutral density in a flexible, nonlinear way as a function of the time horizon. Thereby, stylized facts such as negative skewness and excess kurtosis are captured. The approach is applied to a very large set of intraday options data on the FTSE 100 recorded at LIFFE. It is shown to yield significantly better results in terms of out-of-sample pricing accuracy in comparison to the basic and an extended Black-Scholes model. It is also significantly better than a more elaborate GARCH option pricing model which includes a time-dependent volatility process. From the perspective of risk management, the extracted risk-neutral densities provide valuable information for value-at-risk estimations." @default.
- W2102951738 created "2016-06-24" @default.
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- W2102951738 date "2001-07-01" @default.
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- W2102951738 title "Risk-neutral density extraction from option prices: improved pricing with mixture density networks" @default.
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- W2102951738 doi "https://doi.org/10.1109/72.935085" @default.
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