利用lsamvy过程对原油期权定价

Akbar Shahmoradi, A. Swishchuk
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引用次数: 4

摘要

随着时间的推移,原油价格呈现出显著的波动性。原油价格的收益分布呈现出肥尾和偏态,几乎不符合正态分布。因此,我们使用正态高斯过程、跳跃扩散过程和方差伽玛过程作为没有这些缺点的三个Levy过程。它们的尾巴也比正态分布的质量更大。我们采用分数阶快速傅立叶变换来校准优化设置中的参数,使用的数据是纽约商品交易所2015年4月24日结算日期的欧式原油期货期权。我们的研究结果表明,与其他方法相比,这三种Levy方法对于接近价格的期权具有非常好的样本外结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Pricing Crude Oil Options Using Lévy Processes
Crude oil prices exhibit significant volatility over time. The distribution of returns on crude oil prices shows fat tails and skewness that barely follow a normal distribution. For this reason, we use the normal Gaussian process, jump diffusion process and variance gamma process as three Levy processes that do not have these drawbacks. Their tails also carry a heavier mass than in a normal distribution. We employ the fractional fast Fourier transform to calibrate parameters in an optimization setup, using data about European-style options on crude oil futures in the New York Mercantile Exchange for a settlement date of April 24, 2015. Our results indicate that these three Levy processes have very good out-of-sample results for near at-the-money options compared with others.
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