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Decomposing portfolio value-at-risk : a general analysis

Hallerbach, Winfried G. - 1999 - This rev.: May 10, 1999

the underlying statistical distributions, a variety of analyticalmethods and simulation-based methods are available. Aside … orhistorical and Monte Carlo simulation methods. Although these approaches to overall VaR estimation have receivedsubstantial … and incremental VaR in either a non-normal analytical setting or a MonteCarlo / historical simulation context.This paper …

Persistent link: https://www.econbiz.de/10011301159

Teasing Out Tail Risk or, Quantum Mechanics to the Rescue : A Practical Method for Characterizing Downside Risk in Non-Gaussian Return Distributions

Stock, Robert D. - 2020

Using equations that arise in quantum mechanics, this paper describes a way to more accurately and efficiently represent non-Gaussian return distributions than the standard method of invoking skewness and kurtosis. Then, it provides a new single intuitive number, defined here as the “crash...

Persistent link: https://www.econbiz.de/10012844430

Option pricing and portfolio optimization under a multi-asset jump-diffusion model with systemic risk

Makarov, Roman - In: Risks : open access journal 11 (2023) 12, pp. 1-24

We explore a multi-asset jump-diffusion pricing model, combining a systemic risk asset with several conditionally independent ordinary assets. Our approach allows for analyzing and modeling a portfolio that integrates high-activity security, such as an exchange trading fund (ETF) tracking a...

Persistent link: https://www.econbiz.de/10014446758

Robust and Practical Estimation for Measures of Tail Risk

Homescu, Cristian - 2014

We describe characteristics of various risk measures (Value-at-Risk, Expected Shortfall, etc.) that are used to analyze and quantify the tail risk exposure, and discuss their relative strengths and weaknesses. Emphasis is placed on presenting and comparing methodologies to compute and backtest...

Persistent link: https://www.econbiz.de/10013053188

Managing portfolio risk using multivariate extreme value methods

Hilal, Sawson; Poon, Ser-Huang; Tawn, Jonathan - 2013

This paper provides a strategy for portfolio risk management by inferring extreme movements in financial markets. The core of the provided strategy is a statistical model for the joint tail distribution that attempts to capture accurately the data generating process through an extremal modelling...

Persistent link: https://www.econbiz.de/10010206955

A Method to Estimate Power Parameter in Exponential Power Distribution Via Polynomial Regression

Coin, Daniele - 2012

The Exponential Power Distribution (EPD), also known as Generalized Error Distribution (GED), is a flexible symmetrical unimodal family belonging to the exponential family. The EPD becomes the density function of a range of symmetric distributions with different values of its power parameter B....

Persistent link: https://www.econbiz.de/10014172617

On approximating the distributions of goodness-of-fit test statistics based on the empirical distribution function : the case of unknown parameters

Capasso, Marco; Alessi, Lucia; Barigozzi, Matteo; … - 2007

This note discusses some problems possibly arising when approximating via MonteCarlo simulations the distributions of goodness-of-fit test statistics based on the empirical distribution function. We argue that failing to reestimate unknown parameters on each simulated Monte-Carlo sample - and...

Persistent link: https://www.econbiz.de/10003746039

On the robustness of the fat-tailed distribution of firm growth rates : a global sensitivity analysis

Dosi, Giovanni; Pereira, Marcelo de Carvalho; … - 2016

. (2015) we implemented a simple multi-firm evolutionary simulation model, built upon the coupling of a replicator dynamic and …

Persistent link: https://www.econbiz.de/10011446461

Monte Carlo Approximations for Low Moments of Order Deviates from Arbitrary Continuous Distribution

Nawar, Abdel-Hameed - 2006

A simple and readily computable algorithm is developed for approximating the low moments of order deviates from any continuous distribution. The results are compared with those obtained from exact closed form moments, obtained from quadrature as well as other non-Monte Carlo integral computations

Persistent link: https://www.econbiz.de/10012779480

Elliptical Black-Litterman Portfolio Optimization

Palczewski, Andrzej - 2017

We extend the Black-Litterman framework beyond normality to general elliptical distributions of investor's views and asset returns and portfolio risk measured by CVaR. Unlike existing solutions, cf. Xiao and Valdez [Quant. Finan. 2015, 15:3, 509-519], the choice of distributions, with the first...

Persistent link: https://www.econbiz.de/10012960088

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