First-passage probability, jump models, and intra-horizon risk

被引:17
作者
Bakshi, Gurdip [2 ]
Panayotov, George [1 ]
机构
[1] Georgetown Univ, McDonough Sch Business, Washington, DC 20057 USA
[2] Univ Maryland, Smith Sch Business, College Pk, MD 20742 USA
关键词
Intra-period risk; First-passage probability; Value-at-risk; Jump-models; VALUE-AT-RISK; MAXIMUM-LIKELIHOOD-ESTIMATION; TIME PRICE DISCOVERY; OPTION; DIFFUSION; VOLATILITY; APPROXIMATION; RETURNS; STOCK; BOND;
D O I
10.1016/j.jfineco.2009.01.003
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
This paper proposes a risk measure, based on first-passage probability, which reflects intra-horizon risk in jump models with finite or infinite jump activity. Our empirical investigation shows, first, that the proposed risk measure consistently exceeds the benchmark value-at-risk (VaR). Second, jump risk tends to amplify intra-horizon risk. Third, we find large variation in our risk measure across jump models, indicative of model risk. Fourth, among the jump models we consider, the finite-moment log-stable model provides the most conservative risk estimates. Fifth, imposing more stringent VaR levels accentuates the impact of intra-horizon risk in jump models. Finally, using an alternative benchmark VaR does not dilute the role of intra-horizon risk. Overall, we contribute by showing that ignoring intra-horizon risk can lead to underestimation of risk exposures. (C) 2009 Elsevier B.V. All rights reserved.
引用
收藏
页码:20 / 40
页数:21
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