Parametric VaR under the normality assumption
The Assumption(s) of Normality
... In order to see why this gives us another reason to assume that populations are normal, note the following two points. First, it is assumed that any error in estimating the population mean is independent of any error in ...
6
A test of the normality assumption in the ordered probit model
... where is a matrix consisting of the last two columns of an dimensional identity matrix and all of the elements of are evaluated at their ordered probit MLE values. The proofs in the appendix to BJL may be ...
10
An Econometric Approach to Incorporating Non Normality in VaR Measurement
... This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/ Abstract Following the recent financial crises, there has been a ...
17
On the Assumption of Bivariate Normality in Selection Models A Copula Approach Applied to Estimating HIV Prevalence
... As outlined in Geneletti et al. (2011), it is particularly important to evaluate the robustness of results obtained from surveys involving missing data due to the fact that we never observe the true HIV status of those ...
19
Consistency and asymptotic normality for a nonparametric prediction under measurement errors
... estimators under much less restrictive ...asymptotic normality of the estimators under the assumption that there are two types of measurement errors on the observed values of ...
41
Thumbs Up to Parametric Measures of Relative VaR and CVaR in Indonesian Sectors
... Parametric methods, which assume a normal distribution, are one of the most popular and easiest methods of measuring VaR. All that is needed is the standard deviation σ of the daily returns of an entity, ...
18
"Tests for Multivariate Analysis of Variance in High Dimension Under Non-Normality"
... The variation due to the error which can be used to estimate the correlation matrix Λ with or without the hypothesis H being true is given by S = n −1 Y ′ (I N − H)Y , H = X(X ′ X) −1 X ′ , n = N − k, (1.11) where I N − ...
24
Estimating Impact of a Continuous Program under a Conditional Independence Assumption
... Table 1 presents estimates of γ and θ using OLS regression and the so-called semi- parametric approach in which the propensity score matching is used to estimate program impact for remittance-receiving households ...
10
Estimating Impact of a Continuous Program under a Conditional Independence Assumption
... Table 1 presents estimates of γ and θ using OLS regression and the so-called semi- parametric approach in which the propensity score matching is used to estimate program impact for remittance-receiving households ...
10
Pricing and Hedging Basis Risk under No Good Deal Assumption
... In contrast to buy and hold strategies, “NGD-B”, “NGD-MV” and “BS” intend to approach ( a.s. for “BS”, in a quadratic way for “NGD-MV” and according to the risk measure ρ t for “NGD-B”) the optional call payoff. When ρ ...
36
Pricing and Hedging Basis Risk under No Good Deal Assumption
... In contrast to buy and hold strategies, “NGD-B”, “NGD-MV” and “BS” intend to approach ( a.s. for “BS”, in a quadratic way for “NGD-MV” and according to the risk measure ρ t for “NGD-B”) the optional call payoff. When ρ ...
37
Preliminary tests of homogeneity- type I error rates under non-normality
... The ANOVA is used to assess whether the k populations have a common mean µ. For this, k samples 𝑥 𝑖1 , 𝑥 𝑖2 , … . , 𝑥 𝑖𝑛 , of size 𝑛 𝑖 with respective means, 𝜇 𝑖 and variances, 𝜎 𝑖 2 , 𝑖 = 1, … . . , 𝑘 are drawn from ...
12
Preliminary tests of homogeneity type I error rates under non normality
... The ANOVA is used to assess whether the k populations have a common mean µ. For this, k samples 𝑥 𝑖1 , 𝑥 𝑖2 , … . , 𝑥 𝑖𝑛 , of size 𝑛 𝑖 with respective means, 𝜇 𝑖 and variances, 𝜎 𝑖 2 , 𝑖 = 1, … . . , 𝑘 are drawn from ...
12
The Hidden Risks of Optimizing Bond Portfolios under VaR
... the VaR, we repeatedly generated random weights for any portfolio in the two case sets where the integer and the budget constraints are the only ...expected VaR is ...the VaR such that the frequency ...
25
Fixed point theorems for generalized quasi-contractions in cone $b$-metric spaces over Banach algebras without the assumption of normality with applications
... Remark 3.16. Compared with [24, Theorem 3.1], Example 3.14 shows that under the same condi- tions the unique solution to the integral equation (3.9) is not only continuous but also differential, while [24, Theorem ...
19
Generalization Error Bounds in Semi-supervised Classification Under the Cluster Assumption
... interest for the user who wants to try several values of λ. Note also that a wide range of density estimators is available in usual software. A density estimator can be parametric, typically based on a mixture ...
24
THE IMPORTANCE OF THE NORMALITY ASSUMPTION IN LARGE PUBLIC HEALTH DATA SETS
... It is widely but incorrectly believed that the t-test and linear regression are valid only for Normally distributed outcomes. This belief leads to the use of rank tests for which confidence intervals are very hard to ...
21
Inferences on the Generalized Variance under Normality
... However, our paper is organized as follows: In Section 2, for constructing confidence interval and testing the hypotheses in (1) and (2), we give a computational ap- proach and review thr[r] ...
11
RSA-OAEP is Secure under the RSA Assumption
... Recently Victor Shoup noted that there is a gap in the widely-believed se- curity result of OAEP against adaptive chosen-ciphertext attacks. More- over, he showed that, presumably, OAEP cannot be proven secure from the ...
16
RSA OAEP is Secure under the RSA Assumption
... the under- lying trapdoor ...model, under the partial-domain one-wayness of the underlying ...proven under the sole RSA assumption, although the reduction is not ...
15