Statistical foundations for assessing the difference between the classical and weighted-Gini betas

DOI10.3103/S1066530717040020MaRDI QIDQ1702429

Ričardas Zitikis, N. V. Gribkova

Publication date: 28 February 2018

Published in: Mathematical Methods of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1706.05510

zbMATH Keywords

consistencyasymptotic normalitycapital allocationbetaportfolio constructionweighted Gini

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Asymptotic properties of nonparametric inference (62G20) Applications of statistics to actuarial sciences and financial mathematics (62P05) Nonparametric estimation (62G05)

Related Items (6)

Inference for the tail conditional allocation: large sample properties, insurance risk assessment, and compound sums of concomitants ⋮ On the strong law of large numbers for linear combinations of concomitants ⋮ Statistical detection and classification of background risks affecting inputs and outputs ⋮ Weighted allocations, their concomitant-based estimators, and asymptotics ⋮ Non-parametric inference for Gini covariance and its variants ⋮ Empirical tail conditional allocation and its consistency under minimal assumptions

Uses Software

• QRM

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• The cumulative quantile regression function with censored and truncated response
• Estimating the distortion parameter of the proportional-hazard premium for heavy-tailed losses
• Empirical estimation of the proportional hazard premium for heavy-tailed claim amounts
• Weighted risk capital allocations
• Bootstrap of the mean in the infinite variance case
• A single-parameter generalization of the Gini indices of inequality
• A strong law for linear functions of order statistics
• Linear combination of concomitants of order statistics with application to testing and estimation
• When does bootstrap work! Asymptotic results and simulations
• Convergence of sample paths of normalized sums of induced order statistics
• Background risk in generalized expected utility theory
• Convergence theorems for empirical cumulative quantile regression functions
• Insurance pricing and increased limits ratemaking by proportional hazards transforms
• Risk measures, distortion parameters, and their empirical estimation
• On the cumulative quantile regression process
• On the Edgeworth expansion and the \(M\) out of \(N\) bootstrap accuracy for a Studentized trimmed mean
• On the Consistency of the $M\llN$ Bootstrap Approximation for a Trimmed Mean
• Statistical estimate of the proportional hazard premium of loss
• General Stein-Type Covariance Decompositions with Applications to Insurance and Finance
• A FORM OF MULTIVARIATE PARETO DISTRIBUTION WITH APPLICATIONS TO FINANCIAL RISK MEASUREMENT
• BEYOND THE PEARSON CORRELATION: HEAVY-TAILED RISKS, WEIGHTED GINI CORRELATIONS, AND A GINI-TYPE WEIGHTED INSURANCE PRICING MODEL
• The Asymptotic Distribution of the S–Gini Index
• Weighted Pricing Functionals With Applications to Insurance
• Functions of Order Statistics
• The bootstrap and Edgeworth expansion

This page was built for publication: Statistical foundations for assessing the difference between the classical and weighted-Gini betas