英文标题：
《Volatility Spillovers and Heavy Tails: A Large t-Vector AutoRegressive
Approach》
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作者：
Luca Barbaglia, Christophe Croux and Ines Wilms
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最新提交年份：
2017
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英文摘要：
Volatility is a key measure of risk in financial analysis. The high volatility of one financial asset today could affect the volatility of another asset tomorrow. These lagged effects among volatilities - which we call volatility spillovers - are studied using the Vector AutoRegressive (VAR) model. We account for the possible fat-tailed distribution of the VAR model errors using a VAR model with errors following a multivariate Student t-distribution with unknown degrees of freedom. Moreover, we study volatility spillovers among a large number of assets. To this end, we use penalized estimation of the VAR model with t-distributed errors. We study volatility spillovers among energy, biofuel and agricultural commodities and reveal bidirectional volatility spillovers between energy and biofuel, and between energy and agricultural commodities.
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中文摘要：
波动率是财务分析中衡量风险的关键指标。今天一种金融资产的高波动性可能会影响明天另一种资产的波动性。利用向量自回归（VAR）模型研究了波动率之间的滞后效应，我们称之为波动率溢出。我们使用一个带有误差的VAR模型来解释VAR模型误差的可能厚尾分布，该模型遵循一个具有未知自由度的多元Student t分布。此外，我们还研究了大量资产之间的波动溢出。为此，我们使用具有t分布误差的VAR模型的惩罚估计。我们研究了能源、生物燃料和农产品之间的波动溢出，揭示了能源和生物燃料之间以及能源和农产品之间的双向波动溢出。
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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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