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Estimation of Option-Implied Risk-Neutral into Real-World Density by using Calibration Function

机译:利用校准功能估算可选择暗示风险中立的真实型密度

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Option prices contain crucial information that can be used as a reflection of future development of an underlying assets' price. The main objective of this study is to extract the risk-neutral density (RND) and the risk- world density (RWD) of option prices. A volatility function technique is applied by using a fourth order polynomial interpolation to obtain the RNDs. Then, a calibration function is used to convert the RNDs into RWDs. There are two types of calibration function which are parametric and non-parametric calibrations. The density is extracted from the Dow Jones Industrial Average (DJIA) index options with a one month constant maturity from January 2009 until December 2015. The performance of RNDs and RWDs extracted are evaluated by using a density forecasting test. This study found out that the RWDs obtain can provide an accurate information regarding the price of the underlying asset in future compared to that of the RNDs. In addition, empirical evidence suggests that RWDs from a non-parametric calibration has a better accuracy than other densities.
机译:期权价格包含重要信息,可以用作未来发展潜在资产价格的反映。本研究的主要目标是提取风险中性密度(RND)和期权价格的风险 - 世界密度(RWD)。通过使用四阶多项式插值来应用波动函数技术以获得RND。然后,使用校准函数将RND转换为RWD。有两种类型的校准功能,这是参数和非参数校准。从Dow Jones工业平均值(DJIA)指数选项中提取密度,从2009年1月到2015年12月,一个月持续的成熟度。通过使用密度预测测试来评估RND和RWDS的性能。本研究发现,与RNDS相比,RWDS获得可以提供关于底层资产价格的准确信息。此外,经验证据表明,来自非参数校准的RWD具有比其他密度更好的准确性。

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