کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
417564 | 681534 | 2012 | 16 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Efficient Bayesian estimation of a multivariate stochastic volatility model with cross leverage and heavy-tailed errors
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نظریه محاسباتی و ریاضیات
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چکیده انگلیسی
An efficient Bayesian estimation using a Markov chain Monte Carlo method is proposed in the case of a multivariate stochastic volatility model as a natural extension of the univariate stochastic volatility model with leverage and heavy-tailed errors. The cross-leverage effects are further incorporated among stock returns. The method is based on a multi-move sampler that samples a block of latent volatility vectors. Its high sampling efficiency is shown using numerical examples in comparison with a single-move sampler that samples one latent volatility vector at a time, given other latent vectors and parameters. To illustrate the proposed method, empirical analyses are provided based on five-dimensional S&P500 sector indices returns.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computational Statistics & Data Analysis - Volume 56, Issue 11, November 2012, Pages 3674–3689
Journal: Computational Statistics & Data Analysis - Volume 56, Issue 11, November 2012, Pages 3674–3689
نویسندگان
Tsunehiro Ishihara, Yasuhiro Omori,