Value at Risk Estimation in a Mixture Normality Framework

Diego Zappa, Riccardo Bramante

Risultato della ricerca: Contributo in libroContributo a convegno

Abstract

Value at Risk (VaR) has emerged as a useful tool to risk management. A relevant driving force has been the diffusion as a benchmark of JP Morgan RiskMetricsTM methodology and the subsequent BIS adoption of VaR for all trading portfolios of financial institutions. In this paper we analyze the use of mixture of truncated normal distributions in VaR modelling along with an optimization algorithm to identify the optimal thresholds. The approach gives evidence to capture the extreme tails much better than the standard VaR RiskMetricsTM method completely maintaining local normality properties in the model. Simulation results applied to international equity portfolios are presented
Lingua originaleEnglish
Titolo della pubblicazione ospiteProceedings of the Eighteenth International Conference “Forecasting Financial Markets - Advances for Exchange Rates, Interest Rates and Asset Management”
Pagine1-18
Numero di pagine18
Stato di pubblicazionePubblicato - 2011
EventoForecasting Financial Markets - Advances for Exchange Rates, Interest Rates and Asset Management - Marsiglia
Durata: 25 mag 201127 mag 2011

Convegno

ConvegnoForecasting Financial Markets - Advances for Exchange Rates, Interest Rates and Asset Management
CittàMarsiglia
Periodo25/5/1127/5/11

Keywords

  • mixtures of distributions
  • tail probability
  • truncated normal
  • value at risk

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