Fundamental properties of conditional value-at-risk (CVaR), as a measure of risk with significant advantages over value-at-risk (VaR), are derived for loss distributions in finance that can involve discreetness. Such distributions are of particular importance in applications because of the prevalence of models based on scenarios and finite sampling. CVaR is able to quantify dangers beyond VaR a...

By mid 2004, the Basel Committee on Banking Supervision (BCBS) is expected to launch its final recommendations on minimum capital requirements in the banking industry. Although there is the intention to arrive at capital charges which concur with economic intuition, the risk weight formulas proposed by the committee will lack an adequate treatment of concentration risks in credit portfolios. Th...

In extreme value theory, the so-called extreme-value index is a parameter that controls the behavior of a distribution function in its right tail. Knowing this parameter is thus essential to solve many problems related to extreme events. In this paper, the estimation of the extreme-value index is considered in the presence of a random covariate, whether the conditional distribution of the varia...

Conditional Value at Risk (CVaR) is a prominent risk measure that is being used extensively in various domains such as finance. In this work we present a new formula for the gradient of the CVaR in the form of a conditional expectation. Our result is similar to policy gradients in the reinforcement learning literature. Based on this formula, we propose novel sampling-based estimators for the CV...

We consider continuous-time stochastic optimal control problems featuring Conditional Valueat-Risk (CVaR) in the objective. The major difficulty in these problems arises from timeinconsistency, which prevents us from directly using dynamic programming. To resolve this challenge, we convert to an equivalent bilevel optimization problem in which the inner optimization problem is standard stochast...

Recently, a new approach for optimization of Conditional Value-at-Risk (CVaR) was suggested and tested with several applications. For continuous distributions, CVaR is defined as the expected loss exceeding Value-at Risk (VaR). However, generally, CVaR is the weighted average of VaR and losses exceeding VaR. Central to the approach is an optimization technique for calculating VaR and optimizing...