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The paper discusses capital allocation using the Euler formula and focuses on the risk measures Value-at-Risk (VaR) and Expected shortfall (ES). Some new results connected to this capital allocation is known. Two examples illustrate that…

Risk Management · Quantitative Finance 2024-05-02 Lars Holden

Despite the fact that the Euler allocation principle has been adopted by many financial institutions for their internal capital allocation process, a comprehensive description of Euler allocation seems still to be missing. We try to fill…

Portfolio Management · Quantitative Finance 2008-12-02 Dirk Tasche

Risk contributions of portfolios form an indispensable part of risk adjusted performance measurement. The risk contribution of a portfolio, e.g., in the Euler or Aumann-Shapley framework, is given by the partial derivatives of a risk…

Risk Management · Quantitative Finance 2022-11-14 Akif Ince , Ilaria Peri , Silvana Pesenti

Portfolio selection in the periodic investment of securities modeled by a multivariate Merton model with dependent jumps is considered. The optimization framework is designed to maximize expected terminal wealth when portfolio risk is…

Statistics Theory · Mathematics 2021-04-22 Bahareh Afhami , Mohsen Rezapour , Mohsen Madadi , Vahed Maroufy

For long term investments, model portfolios are defined at the level of indexes, a setup known as Strategic Asset Allocation (SAA). The possible outcomes at a scale of a few decades can be obtained by Monte Carlo simulations, resulting in a…

Risk Management · Quantitative Finance 2025-11-25 Gilles Zumbach

In the paper, we use and investigate copulas models to represent multivariate dependence in financial time series. We propose the algorithm of risk measure computation using copula models. Using the optimal mean-$CVaR$ portfolio we compute…

Risk Management · Quantitative Finance 2017-07-13 Mikhail Semenov , Daulet Smagulov

An importance sampling approach for sampling copula models is introduced. We propose two algorithms that improve Monte Carlo estimators when the functional of interest depends mainly on the behaviour of the underlying random vector when at…

Computation · Statistics 2015-04-08 Philipp Arbenz , Mathieu Cambou , Marius Hofert

The ability to adequately model risks is crucial for insurance companies. The method of "Copula-based hierarchical risk aggregation" by Arbenz et al. offers a flexible way in doing so and has attracted much attention recently. We briefly…

Risk Management · Quantitative Finance 2015-06-22 Fabio Derendinger

The minimization of some multivariate risk indicators may be used as an allocation method, as proposed in C\'enac et al. [6]. The aim of capital allocation is to choose a point in a simplex, according to a given criterion. In a previous…

Probability · Mathematics 2015-07-07 Véronique Maume-Deschamps , Didier Rullière , Khalil Said

Capital allocation is a procedure for quantifying the contribution of each source of risk to aggregated risk. The gradient allocation rule, also known as the Euler principle, is a prevalent rule of capital allocation under which the…

Risk Management · Quantitative Finance 2024-06-28 Takaaki Koike , Cathy W. S. Chen , Edward M. H. Lin

Accurately estimating risk measures for financial portfolios is critical for both financial institutions and regulators. However, many existing models operate at the aggregate portfolio level and thus fail to capture the complex…

Portfolio Management · Quantitative Finance 2023-02-10 Emanuel Sommer , Karoline Bax , Claudia Czado

We develop the idea of using Monte Carlo sampling of random portfolios to solve portfolio investment problems. In this first paper we explore the need for more general optimization tools, and consider the means by which constrained random…

Portfolio Management · Quantitative Finance 2010-08-24 William T. Shaw

In this paper, we study large losses arising from defaults of a credit portfolio. We assume that the portfolio dependence structure is modelled by the Archimedean copula family as opposed to the widely used Gaussian copula. The resulting…

Risk Management · Quantitative Finance 2024-11-12 Hengxin Cui , Ken Seng Tan , Fan Yang

A factor copula model is proposed in which factors are either simulable or estimable from exogenous information. Point estimation and inference are based on a simulated methods of moments (SMM) approach with non-overlapping simulation…

Econometrics · Economics 2022-12-02 Alexander Mayer , Dominik Wied

Signals coming from multivariate higher order conditional moments as well as the information contained in exogenous covariates, can be effectively exploited by rational investors to allocate their wealth among different risky investment…

Portfolio Management · Quantitative Finance 2016-01-21 Mauro Bernardi , Leopoldo Catania

We consider the problem of simulating loss probabilities and conditional excesses for linear asset portfolios under the t-copula model. Although in the literature on market risk management there are papers proposing efficient variance…

Risk Management · Quantitative Finance 2017-08-07 Halis Sak , İsmail Başoğlu

Determining contributions by sub-portfolios or single exposures to portfolio-wide economic capital for credit risk is an important risk measurement task. Often economic capital is measured as Value-at-Risk (VaR) of the portfolio loss…

Statistics Theory · Mathematics 2009-06-18 Dirk Tasche

In many real-world engineering systems, the performance or reliability of the system is characterised by a scalar parameter. The distribution of this performance parameter is important in many uncertainty quantification problems, ranging…

Methodology · Statistics 2022-10-03 Robert Millar , Jinglai Li , Hui Li

Computing risk measures of a financial portfolio comprising thousands of derivatives is a challenging problem because (a) it involves a nested expectation requiring multiple evaluations of the loss of the financial portfolio for different…

Mathematical Finance · Quantitative Finance 2023-01-10 Michael B. Giles , Abdul-Lateef Haji-Ali

Conditional Monte Carlo refers to sampling from the conditional distribution of a random vector X given the value T(X) = t for a function T(X). Classical conditional Monte Carlo methods were designed for estimating conditional expectations…

Methodology · Statistics 2020-10-15 Bo Henry Lindqvist , Rasmus Erlemann , Gunnar Taraldsen
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