Report
Inference on Self-Exciting Jumps in Prices and Volatility using High Frequency Measures
| العنوان: | Inference on Self-Exciting Jumps in Prices and Volatility using High Frequency Measures |
|---|---|
| المؤلفون: | Maneesoonthorn, Worapree, Forbes, Catherine S., Martin, Gael M. |
| سنة النشر: | 2014 |
| المجموعة: | Quantitative Finance Statistics |
| مصطلحات موضوعية: | Statistics - Applications, Quantitative Finance - Statistical Finance |
| الوصف: | 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. |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/1401.3911 |
| رقم الانضمام: | edsarx.1401.3911 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |