英文标题：
《Inference on Self-Exciting Jumps in Prices and Volatility using High
  Frequency Measures》
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作者：
Worapree Maneesoonthorn, Catherine S. Forbes and Gael M. Martin
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最新提交年份：
2016
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英文摘要：
  Dynamic jumps in the price and volatility of an asset are modelled using a joint Hawkes process in conjunction with a bivariate jump diffusion. A state space representation is used to link observed returns, plus nonparametric measures of integrated volatility and price jumps, to the specified model components; with Bayesian inference conducted using a Markov chain Monte Carlo algorithm. An evaluation of marginal likelihoods for the proposed model relative to a large number of alternative models, including some that have featured in the literature, is provided. An extensive empirical investigation is undertaken using data on the S&P500 market index over the 1996 to 2014 period, with substantial support for dynamic jump intensities - including in terms of predictive accuracy - documented.
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中文摘要：
资产价格和波动性的动态跳跃采用联合霍克斯过程和双变量跳跃扩散进行建模。状态空间表示用于将观察到的收益，加上综合波动率和价格跳跃的非参数度量，与指定的模型组件联系起来；使用马尔可夫链蒙特卡罗算法进行贝叶斯推理。与大量替代模型（包括文献中的一些模型）相比，本文对拟议模型的边际可能性进行了评估。利用1996年至2014年期间标准普尔500指数的数据进行了广泛的实证调查，并记录了对动态跳跃强度（包括预测准确性）的实质性支持。
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分类信息：

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
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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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