What are the advantages and disadvantages of using the t distribution for VaR estimation?

The Student-t distribution is a continuous probability distribution with probability density function given by: · subject to the following conditions: · The ... A key feature of our model is that the conditional t–distributions of the component models are based on autoregressions that have multivariate t–distributions ... We suggest a log-normal prior as a viable prior option. We show that the Bayesian estimator based on a log-normal prior compares favorably to other Bayesian ... Oct 12, 2023 ... We address the problem of computing a consistency factor for the MCD estimator in a heavy-tail scenario, when uncontaminated data come from a multivariate ... Critical Values for Student's t-Distribution. Upper Tail Probability: Pr(T >t) df. 0.2. 0.1. 0.05. 0.04. 0.03. 0.025. 0.02. 0.01. 0.005. 0.0005. 1. 1.376. 3.078. Student's T distribution. Describes a normal variable whose precision is gamma distributed. If only nu parameter is passed, this specifies a standard (central) ... The most commonly used significance level is α = 0.05. For a two-sided test, we compute 1 - α/2, or 1 - 0.05/2 = 0.975 when α = 0.05. If the absolute value of ... Nov 15, 2022 ... The entropy of a Student t random variable with ν degrees of freedom is asymptotically \frac{1}{2} + \frac{\log 2\pi}{2} + \frac{1}{\nu} for large Critical Values for Student's t Distribution. Area c. –t. 0 t. One-tail area. Right-tail area. 0 t. Left-tail area. –t. 0. Two-tail area. Area. –t. 0 t. For ... Nov 5, 2009 ... This paper proposes a new class of asymmetric Student-t (AST) distributions, and investigates its properties, gives procedures for estimation, ...