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On approximations for the distribution of a heterogeneous risk portfolio

Bjorn Sundt

On approximations for the distribution of a heterogeneous risk portfolio

by Bjorn Sundt

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  • 8 Currently reading

Published by Laboratory of Actuarial Mathematics, Univ. of Copenhagen in Copenhagen .
Written in English


The Physical Object
Pagination15 p.
Number of Pages15
ID Numbers
Open LibraryOL24715193M

Approximate Aggregation in Heterogeneous-Agent Models∗ Michael Reiter, Institute for Advanced Studies, Vienna VERY PRELIMINARY AND INCOMPLETE VERSION! February 14, Abstract The paper shows how to get precise approximations to the solution of DSGE models with a great number of heterogeneous agents. The examples studied are. An unbalanced exposure distribution of a loan portfolio, either across regional or business sectors, in generally increases the associated credit risk. If credit risk is measured by a single systematic risk factor, sector concentration is usually not accounted for. The purpose of this paper is twofold.

Heterogeneous Beliefs, Trading Risk, and the Equity bond prices do depend on the distribution of beliefs. However, despite the consumption smoothing attained by trading in financial assets, the difference in opinions remains, and agents continue to face an exposure to the trading risk. Therefore, despite trading, the model equity premium does. When heterogeneity exists in variables’ effects on the outcome across studies, the simple pooling strategy fails to present a fair and complete picture of the effects of heterogeneous variables. Thus, it is important to investigate the homogeneous and heterogeneous structure of variables in pooled sunshinesteaming.com by: 6.

Heterogeneous Preferences, Investment and Asset Pricing Bo Liu, Lei Lu, Jinqiang Yang July 3, Abstract We present a continuous-time general equilibrium model in which agents have het-erogenous risk aversion levels and discount rates. We examine the impact of risk aversion and discount rate heterogeneity on agents’ consumption and. Defining Risk Heterogeneity for Internalizing Symptoms among Children of Alcoholic Parents. Adopting a developmental epidemiology perspective (see Costello & Angold, ), the current study examines sources of risk heterogeneity for internalizing symptoms among children of alcoholic parents (COAs).Understanding factors contributing to risk heterogeneity among COAs is important for several Cited by:


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On approximations for the distribution of a heterogeneous risk portfolio by Bjorn Sundt Download PDF EPUB FB2

Sep 30,  · The large homogeneous portfolio approximation with a two-factor Gaussian copula and random recovery rate In order to derive semianalytic formulas for the loss distribution and the expected tranche loss, we use a Gaussian two-factor model and assume that the recovery rate depends on one systematic factor.

assumptions under the Gaussian Author: Carolyn Moclair. On approximations for the distribution of a heterogeneous risk portfolio. Bulletin of the Association of Swiss Actuaries, – Improved approximations for the aggregate claims distribution.

APPROXIMATING THE DISTRIBUTION OF A DYNAMIC RISK PORTFOLIO paper, Jewell and Sundt showed how to approximate a distribution of total losses from a large, fixed, heterogeneous portfolio, using a recursive algorithm developed by Panjer for the distribution of a random sum of random DISTRIBUTION OF DYNAMIC RISK PORTFOLIO This paper develops approximations for the distribution of losses from default in a normal copula framework for credit risk.

We put particular emphasis on approximating small probabilities of Author: Paul Glasserman. In a moderately heterogeneous portfolio with risk index correlations 0 of the portfolio loss distribution in theorem 1 can particularly be used to calculate single ex-posures’ (approximate) contributions to portfolio risk without having to perform a full-fleged.

Downloadable (with restrictions). Abstract This article proposes a three-step procedure to estimate portfolio return distributions under the multivariate Gram–Charlier (MGC) distribution. The method combines quasi maximum likelihood (QML) estimation for conditional means and variances and the method of moments (MM) estimation for the rest of the density parameters, including the correlation Cited by: 1.

Nov 21,  · The FRTB requires replacing VaR by ES, as risk measure of the trading portfolio, to capture tail risk and address other VaR weaknesses. We recall that VaR at the confidence level 𝛽 is defined as the percentile of the loss distribution of a financial portfolio such that:Author: Noureddine Lehdili, Arshia Givi.

Homogeneity and heterogeneity are concepts often used in the sciences and statistics relating to the uniformity in a substance or organism. A material or image that is homogeneous is uniform in composition or character (i.e.

color, shape, size, weight, height, distribution, texture, language, income, disease, temperature, radioactivity, architectural design, etc.); one that is heterogeneous is. OPTIMAL PRICING OF A HETEROGENEOUS PORTFOLIO FOR A GIVEN RISK LEVEL BY YANIV ZAKS,ESTHER FROSTIG AND BENNY LEVIKSON1 ABSTRACT Consider a portfolio containing heterogeneous risks, where the policyholders’ premiums to the insurance company might not cover the claim payments.

This risk has to be taken into consideration in the premium pricing. Optimal pricing for a heterogeneous portfolio for a given risk factor and convex distance measure This article is dedicated to the memory of our beloved friend Professor Benjamin Zeev Levikson who passed away on July 16, Cited by: In this paper we consider heterogeneous portfolios of endowment insurance policies with a 12 months maturation time.

We apply majorization order, Schur functions, and fractional approximations to study the effects of statistical heterogeneity on the premium, on the death benefit and on the survival benefit of the endowment sunshinesteaming.com by: 7. Heterogeneous Risk Preferences in Financial Markets Tyler Abbot November 10, Abstract In this paper I build a continuous time model of a complete nancial market portfolio compositions.

The distribution of these groups determines the market price of risk and the risk free rate. The risk free rate is low and the market price of risk high. Approximating Independent Loss Distributions with an Adjusted Binomial Distribution and fast enough to allow daily risk-management of a large correlation book.

of the exact loss distribution for a portfolio with inhomogeneous losses can result in a significant increase in. Nov 14,  · Assessing individuals’ time and risk preferences is crucial in domains such as health-related decisions (e.g., dieting, addictions), environmentally-friendly practices, and saving opportunities.

We propose a new method to jointly elicit and estimate risk attitudes and intertemporal choices. We use a novel individual level estimation procedure based on a hierarchical Bayes methodology, which Cited by: We shall use the data of Exhibit to construct a maximum likelihood estimat for the unknown mean vector of the mixed-normal distribution.

A Tractable Model to Measure Sector Concentration Risk in Credit Portfolios Klaus Düllmann1 and Nancy Masschelein2 This version: October Abstract This paper explores a simplified version of the analytic value-at-risk approximation developed by Pykhtin () which Cited by: granularity.

This implies that the analytic approximations err on the conservative side. To our knowledge there is only one recent empirical paper that considers the impact of sector concentration risk on economic capital.

Burton et al () simulated the distribution of portfolio credit losses for a number of real US syndicated loan portfolios. where ƒ is a distribution on the unit sphere S n−1. The number λ, which is the degree of the homogeneous distribution S, may be real or complex.

Any homogeneous distribution of the form on R n \ {0} extends uniquely to a homogeneous distribution on R n provided Re λ > −n. gates the effect of heterogeneity in risk preferences on efficient risk sharing within a group.

It is shown that with heterogeneous risk preferences efficient risk sharing can increase group savings even if it reduces the amount of uncertainty faced by the group. Hara, Huang, and Kuzmics () analyze 3.

Don’t Fall from the Saddle: the importance of higher moments of credit loss distributions1 Jan Annaert distribution, thereby avoiding time-consuming Monte Carlo simulations.

Additionally, the model portfolio for which the risk factors are normally distributed with correctly specified covarianceCited by: 6. Analytic Loss Distributions of Heterogeneous Portfolios in the Asset Value Credit Risk Model.

by Uwe Wehrspohn of Heidelberg University. May Abstract: We provide an analytic solution to the asset value credit risk model that allows for heterogeneous correlations.USA1 US10/, USA USA1 US A1 US A1 US A1 US A US A US A US A1 US ACited by: The study of random heterogeneous materials is an exciting and rapidly growing multidisciplinary endeavor.

This field demands a unified rigorous means of characterizing the microstructures and macroscopic properties of the widely diverse types of heterogeneous materials that abound in nature and synthetic products.