Add to ORKGThis paper describes,analyzes and evaluates an algorithm for estimating portfolio loss probabilities using Monte Carlo simulation. Obtaining accurate estimates of such loss probabilities is essential to calculating value-at-risk,which is a quantile of the loss distribution. The method employs a quadratic (’’delta-gamma’’) approximation to the change in portfolio value to guide the selection of effective variance reduction techniques; specifically importance sampling and stratified sampling. If the approximation is exact,then the importance sampling is shown to be asymptotically optimal. Numerical results indicate that an appropriate combination of importance sampling and stratified sampling can result in large variance reductions when estim...
Monte Carlo variance reduction methods have attracted significant interest due to the continuous dem...
Value-at-risk (VaR) and conditional value-at-risk (CVaR) are two widely used risk measures of large ...
International audienceAdaptive Monte Carlo methods are recent variance reduction techniques. In this...
This paper describes, analyzes and evaluates an algorithm for estimating portfolio loss probabilitie...
This paper proposes and evaluates variance reduction techniques for efficient estimation of portfoli...
This paper proposes and evaluates variance reduction techniques for efficient estimation of portfoli...
In this article we present a new variance reduction technique for estimating the Value-at-Risk (VaR)...
Monte Carlo simulation is one of the commonly used methods for risk estimation on financial markets,...
[[abstract]]Importance sampling is a powerful variance reduction technique for rare event simulation...
[[abstract]]Many empirical studies suggest that the distribution of risk factors has heavy tails. On...
Abstract. The authors discuss the approximation of Value at Risk (VaR) and other quantities relevant...
Copyright © 2013 Qiang Zhao et al. This is an open access article distributed under the Creative Com...
Present work deals with the portfolio selection problem using mean-risk models where analysed risk m...
Thesis (Ph.D.)--Boston University PLEASE NOTE: Boston University Libraries did not receive an Autho...
The problem of the asymmetric behaviour and fat tails of portfolios of credit risky corporate assets...
Monte Carlo variance reduction methods have attracted significant interest due to the continuous dem...
Value-at-risk (VaR) and conditional value-at-risk (CVaR) are two widely used risk measures of large ...
International audienceAdaptive Monte Carlo methods are recent variance reduction techniques. In this...
This paper describes, analyzes and evaluates an algorithm for estimating portfolio loss probabilitie...
This paper proposes and evaluates variance reduction techniques for efficient estimation of portfoli...
This paper proposes and evaluates variance reduction techniques for efficient estimation of portfoli...
In this article we present a new variance reduction technique for estimating the Value-at-Risk (VaR)...
Monte Carlo simulation is one of the commonly used methods for risk estimation on financial markets,...
[[abstract]]Importance sampling is a powerful variance reduction technique for rare event simulation...
[[abstract]]Many empirical studies suggest that the distribution of risk factors has heavy tails. On...
Abstract. The authors discuss the approximation of Value at Risk (VaR) and other quantities relevant...
Copyright © 2013 Qiang Zhao et al. This is an open access article distributed under the Creative Com...
Present work deals with the portfolio selection problem using mean-risk models where analysed risk m...
Thesis (Ph.D.)--Boston University PLEASE NOTE: Boston University Libraries did not receive an Autho...
The problem of the asymmetric behaviour and fat tails of portfolios of credit risky corporate assets...
Monte Carlo variance reduction methods have attracted significant interest due to the continuous dem...
Value-at-risk (VaR) and conditional value-at-risk (CVaR) are two widely used risk measures of large ...
International audienceAdaptive Monte Carlo methods are recent variance reduction techniques. In this...