英文标题：
《Mean-correction and Higher Order Moments for a Stochastic Volatility
Model with Correlated Errors》
---
作者：
Sujay Mukhoti, Pritam Ranjan
---
最新提交年份：
2016
---
英文摘要：
In an efficient stock market, the log-returns and their time-dependent variances are often jointly modelled by stochastic volatility models (SVMs). Many SVMs assume that errors in log-return and latent volatility process are uncorrelated, which is unrealistic. It turns out that if a non-zero correlation is included in the SVM (e.g., Shephard (2005)), then the expected log-return at time t conditional on the past returns is non-zero, which is not a desirable feature of an efficient stock market. In this paper, we propose a mean-correction for such an SVM for discrete-time returns with non-zero correlation. We also find closed form analytical expressions for higher moments of log-return and its lead-lag correlations with the volatility process. We compare the performance of the proposed and classical SVMs on S&P 500 index returns obtained from NYSE.
---
中文摘要：
在一个有效的股票市场中，对数收益率及其随时间变化的方差通常由随机波动率模型（SVM）联合建模。许多支持向量机假设对数收益率和潜在波动率过程中的误差是不相关的，这是不现实的。事实证明，如果支持向量机中包含非零相关性（例如Shephard（2005）），那么在t时刻以过去收益为条件的预期对数收益率是非零的，这不是有效股票市场的理想特征。在本文中，我们提出了一种非零相关离散时间收益率支持向量机的均值校正方法。我们还找到了对数收益的高阶矩及其与波动过程的超前-滞后关系的封闭式解析表达式。我们比较了所提出的支持向量机和经典支持向量机在纽约证券交易所获得的标准普尔500指数收益率上的性能。
---
分类信息：

一级分类：Statistics 统计学
二级分类：Methodology 方法论
分类描述：Design, Surveys, Model Selection, Multiple Testing, Multivariate Methods, Signal and Image Processing, Time Series, Smoothing, Spatial Statistics, Survival Analysis, Nonparametric and Semiparametric Methods
设计，调查，模型选择，多重检验，多元方法，信号和图像处理，时间序列，平滑，空间统计，生存分析，非参数和半参数方法
--
一级分类：Quantitative Finance 数量金融学
二级分类：Statistical Finance 统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
--
一级分类：Statistics 统计学
二级分类：Applications 应用程序
分类描述：Biology, Education, Epidemiology, Engineering, Environmental Sciences, Medical, Physical Sciences, Quality Control, Social Sciences
生物学，教育学，流行病学，工程学，环境科学，医学，物理科学，质量控制，社会科学
--

---
PDF下载：
-->