Skew exponential power stochastic volatility model for analysis of skewness, non-normal tails, quantiles and expectiles
Skew exponential power stochastic volatility model for analysis of skewness, non-normal tails, quantiles and expectiles
复制标题
用于分析偏度、非正态尾部、分位数和期望值的偏斜指数幂随机波动率模型
DOI：
10.1007/s00180-015-0596-4
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发表时间：
2016
影响因子：
1.3
通讯作者：
Genya Kobayashi
中科院分区：
文献类型：
--
作者：
Kota Ogasawara;Shinichiro Shirota;Genya Kobayashi;Genya Kobayashi
本文提出了一个统一的框架来分析基于随机波动率模型的回归分布的偏度、尾重、分位数和期望。SEP分布可以通过两个形状参数和一个偏度参数来表达广泛的分布形状。由于不对称拉普拉斯分布和偏态正态分布作为特殊情况被考虑在内，因此所提出的模型与分位数回归和期望回归有关。介绍了一种高效、简单的马尔可夫链蒙特卡罗估计方法。利用外汇汇率日收益率的模拟数据和实际数据对模型进行了验证。
This paper proposes a unified framework to analyse the skewness, tail heaviness, quantiles and expectiles of the return distribution based on a stochastic volatility model using a new parametrisation of the skew exponential power (SEP) distribution. The SEP distribution can express a wide range of distribution shapes through two shape parameters and one skewness parameter. Since the asymmetric Laplace and skew normal distributions are included as special cases, the proposed model is related to quantile regression and expectile regression. The efficient and simple Markov chain Monte Carlo estimation methods are also described. The proposed model is demonstrated using the simulated data and real data on daily return of foreign exchange rate.