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Wavelet-based option pricing: An empirical study
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DOI：10.1016/j.ejor.2018.07.025.png)
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摘要
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In this paper, we scrutinize the empirical performance of a wavelet-based option pricing model which leverages the powerful computational capability of wavelets in approximating risk-neutral moment-generating functions. We focus on the forecasting and hedging performance of the model in comparison with that of popular alternative models, including the stochastic volatility model with jumps, the practitioner Black-Scholes model and the neural network based model. Using daily index options written on the German DAX 30 index from January 2009 to December 2012, our results suggest that the wavelet-based model compares favorably with all other models except the neural network based one, especially for long-term options. Hence our novel wavelet-based option pricing model provides an excellent non parametric alternative for valuing option prices. Crown Copyright (C) 2018 Published by Elsevier B.V. All rights reserved.
Keyword:
Pricing
Option valuation
Artificial neural networks
Stochastic volatility
Jump risk
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IF:
6
论文数:
2.2W
被引数:
6.4W
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