Economic risk capital allocation from top down

2002 ◽  
Vol 25 (4) ◽  
pp. 885-891 ◽  
Author(s):  
Werner Hürlimann
Keyword(s):  
Capital Allocation ◽  
Economic Risk ◽  
Risk Capital ◽  
Top Down ◽  
Risk Capital Allocation

scholarly journals τ-value for risk capital allocation problems

2020 ◽  
Vol 48 (6) ◽  
pp. 752-757
Author(s):  
Tim J. Boonen
Keyword(s):  
Capital Allocation ◽  
Risk Capital ◽  
Allocation Problems ◽  
Risk Capital Allocation

Properties and comparison of risk capital allocation methods

2017 ◽  
Vol 259 (2) ◽  
pp. 614-625 ◽  
Author(s):  
Dóra Balog ◽  
Tamás László Bátyi ◽  
Péter Csóka ◽  
Miklós Pintér
Keyword(s):  
Capital Allocation ◽  
Risk Capital ◽  
Risk Capital Allocation ◽  
Allocation Methods

Toward an efficient people-risk capital allocation for financial firms: evidence from US banks

2017 ◽  
Vol 12 (4) ◽  
pp. 71-94
Author(s):  
José Manuel Feria-Dominguez ◽  
Enrique Jiménez-Rodríguez
Keyword(s):  
Capital Allocation ◽  
Risk Capital ◽  
Financial Firms ◽  
Risk Capital Allocation

A numerical approach to the risk capital allocation problem

2021 ◽  
Author(s):  
Henryk Gzyl ◽  
Silvia Mayoral
Keyword(s):  
Numerical Approach ◽  
Capital Allocation ◽  
Allocation Problem ◽  
Risk Capital ◽  
Risk Capital Allocation

scholarly journals A Generalization of the Aumann-Shapley Value for Risk Capital Allocation Problems

2012 ◽  
Author(s):  
Tim Boonen ◽  
Anja M.B. De Waegenaere ◽  
Henk W. Norde
Keyword(s):  
Shapley Value ◽  
Capital Allocation ◽  
Risk Capital ◽  
Allocation Problems ◽  
Risk Capital Allocation

scholarly journals THE EFFECTS OF BANK CONSOLIDATION ON RISK CAPITAL ALLOCATION AND MARKET LIQUIDITY

2006 ◽  
Vol 29 (2) ◽  
pp. 271-291 ◽  
Author(s):  
Chris D'Souza ◽  
Alexandra Lai
Keyword(s):  
Capital Allocation ◽  
Market Liquidity ◽  
Risk Capital ◽  
Bank Consolidation ◽  
Risk Capital Allocation

scholarly journals Fair estimation of capital risk allocation

2020 ◽  
Vol 37 (1-2) ◽  
pp. 1-24
Author(s):  
Tomasz R. Bielecki ◽  
Igor Cialenco ◽  
Marcin Pitera ◽  
Thorsten Schmidt
Keyword(s):  
Numerical Study ◽  
Risk Measures ◽  
Estimation Procedure ◽  
Capital Allocation ◽  
Expected Shortfall ◽  
Substantial Part ◽  
Risk Allocation ◽  
Fair Allocation ◽  
Risk Capital ◽  
Risk Capital Allocation

AbstractIn this paper, we develop a novel methodology for estimation of risk capital allocation. The methodology is rooted in the theory of risk measures. We work within a general, but tractable class of law-invariant coherent risk measures, with a particular focus on expected shortfall. We introduce the concept of fair capital allocations and provide explicit formulae for fair capital allocations in case when the constituents of the risky portfolio are jointly normally distributed. The main focus of the paper is on the problem of approximating fair portfolio allocations in the case of not fully known law of the portfolio constituents. We define and study the concepts of fair allocation estimators and asymptotically fair allocation estimators. A substantial part of our study is devoted to the problem of estimating fair risk allocations for expected shortfall. We study this problem under normality as well as in a nonparametric setup. We derive several estimators, and prove their fairness and/or asymptotic fairness. Last, but not least, we propose two backtesting methodologies that are oriented at assessing the performance of the allocation estimation procedure. The paper closes with a substantial numerical study of the subject and an application to market data.

Modelling random vectors of dependent risks with different elliptical components

2021 ◽  
pp. 1-19
Author(s):  
Zinoviy Landsman ◽  
Tomer Shushi
Keyword(s):  
At Risk ◽  
Value At Risk ◽  
Degrees Of Freedom ◽  
Risk Measures ◽  
Capital Allocation ◽  
Risk Capital ◽  
Dependent Risks ◽  
Risk Capital Allocation ◽  
Elliptical Copula ◽  
T Distribution

Abstract In Finance and Actuarial Science, the multivariate elliptical family of distributions is a famous and well-used model for continuous risks. However, it has an essential shortcoming: all its univariate marginal distributions are the same, up to location and scale transformations. For example, all marginals of the multivariate Student’s t-distribution, an important member of the elliptical family, have the same number of degrees of freedom. We introduce a new approach to generate a multivariate distribution whose marginals are elliptical random variables, while in general, each of the risks has different elliptical distribution, which is important when dealing with insurance and financial data. The proposal is an alternative to the elliptical copula distribution where, in many cases, it is very difficult to calculate its risk measures and risk capital allocation. We study the main characteristics of the proposed model: characteristic and density functions, expectations, covariance matrices and expectation of the linear regression vector. We calculate important risk measures for the introduced distributions, such as the value at risk and tail value at risk, and the risk capital allocation of the aggregated risks.

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