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We propose a new method to estimate the empirical pricing kernel based on option data. We estimate the pricing kernel nonparametrically by using the ratio of the risk-neutral density estimator and the subjective density estimator. The risk-neutral density is approximated by a weighted kernel...
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A primary goal in modelling the implied volatility surface (IVS) for pricing and hedging aims at reducing complexity … approach, however, neglects the degenerated string structure of the implied volatility data and may result in a modelling bias … generalized vega-hedging strategy for exotic options that are priced in the local volatility framework. The generalized vega …
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digital asset returns are driven by high frequency jumps clustered around black swan events, resembling volatility and trading …
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The economic theory of option pricing imposes constraints on the structure of call functions and state price densities (SPDs). Except in a few polar cases, it does not prescribe functional forms. This paper proposes a nonparametric estimator of option pricing models which incorporates various...
Persistent link: https://www.econbiz.de/10009620779
-neutral density estimator and the subjective density estimator. The former density can be represented as the second derivative w …
Persistent link: https://www.econbiz.de/10003952791
of the risk neutral density. The first estimator is a kernel smoother of the second derivative of call prices, while the … second procedure applies kernel type smoothing in the implied volatility domain. In the conceptually different third approach …
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