摘要翻译：
本文基于一般的多维扩散过程，提出了一个简单的连续时间资产定价框架，该框架将半解析定价与市场风险价格的非线性规范相结合。我们的框架保证了非线性SDEs在物理测量下的弱解的存在性，从而允许使用到目前为止文献中未考虑的真实世界动力学的非线性模型。时间序列建模的额外灵活性在经济上是相关的：对标准普尔100和VXO隐含波动率指数数据的联合时间序列的非线性随机波动率扩散模型显示出优于隐含和实现方差预测标准规范的预测能力。
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英文标题：
《Empirical asset pricing with nonlinear risk premia》
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作者：
Aleksandar Mijatovic and Paul Schneider
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最新提交年份：
2009
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分类信息：

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
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一级分类：Quantitative Finance        数量金融学
二级分类：Pricing of Securities        证券定价
分类描述：Valuation and hedging of financial securities, their derivatives, and structured products
金融证券及其衍生产品和结构化产品的估值和套期保值
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英文摘要：
  In this paper we introduce a simple continuous-time asset pricing framework, based on general multi-dimensional diffusion processes, that combines semi-analytic pricing with a nonlinear specification for the market price of risk. Our framework guarantees existence of weak solutions of the nonlinear SDEs under the physical measure, thus allowing to work with nonlinear models for the real world dynamics not considered in the literature so far. It emerges that the additional flexibility in the time series modelling is econometrically relevant: a nonlinear stochastic volatility diffusion model for the joint time series of the S&P 100 and the VXO implied volatility index data shows superior forecasting power over the standard specifications for implied and realized variance forecasting.
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PDF链接：
https://arxiv.org/pdf/0911.0928