This paper examines a new approach for credit risk optimization. The model is based on the Conditional Value-at-Risk (CVaR) risk measure, the expected loss exceeding Value-at-Risk. CVaR is also known as Mean Excess, Mean Shortfall, or Tail VaR. This model can simultaneously adjust all positions in a portfolio of financial instruments in order to minimize CVaR subject to trading and return const...

We propose a new method for mitigating risk in routing hazardous materials (hazmat), based on the conditional value-at-risk (CVaR) measure on time-dependent vehicular networks. The CVaR models are shown to be flexible and suitable for hazmat transportation that can be solved efficiently. This paper extends the previous research by considering CVaR for hazmat transportation in the case where acc...

We propose a sample average approximation (SAA) method for stochastic programming problems involving an expected value constraint. Such problems arise, for example, in portfolio selection with constraints on conditional value-at-risk (CVaR). Our contributions include an analysis of the convergence rate and a statistical validation scheme for the proposed SAA method. Computational results using ...

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One attractive candidate as standard risk metric is Conditional Value at Risk (CVaR), which has a lot of advantages compared with Value at Risk (VaR). In this paper, I study CVaR as an objective function in a series of optimization problems. I compare the CPU time of the linear programming approach proposed in [14] with that of the fast gradient descent method [5] when increasing the number of ...

Value-at-risk (VaR) and conditional value-at-risk (CVaR) are popular risk measures from academic, industrial and regulatory perspectives. The problem of minimizing CVaR is theoretically known to be of a Neyman–Pearson type binary solution. We add a constraint on expected return to investigate the mean-CVaR portfolio selection problem in a dynamic setting: the investor is faced with a Markowitz ...

Recognizing the drawbacks of Value-at-Risk (VaR), researchers have advocated the use of Conditional Value-at-Risk (CVaR). However, the current popularity of VaR and Stress Testing (ST) among bank regulators raises the question of whether a risk management system based on both VaR and ST constraints is an effective alternative to a system based on CVaR. We show that when the VaR and ST bounds ar...

In this paper, we propose the stochastic programming (SP) model with risk measure conditional value at risk (CVaR) for investing stocks in Taiwan stock market. In each period of investment, 200 scenarios are generated for solving SP, and the CVaR is utilized to manage the risk. The experiment interval starts from 2005/1/1 and ends on 2013/12/31, which has totally 2235 trading periods. The exper...

In this paper we assess the partial hedging problems by formulating hedging strategies that minimize conditional value-at-risk (CVaR) of the portfolio loss under stochastic interest rate environment. The combination of stochastic interest and CVaR hedging method makes the valuing approach more complex than the existing model with constant interest rate. We take up two issues in searching the op...

Value at Risk (VaR) is an important issue for banks since its adoption as a primary risk metric in the Basel Accords and the requirement that it is calculated on a daily basis. VaR calculates maximum expected losses over a given time period at a given tolerance level. Conditional Value at Risk (CVaR) measures extreme risk. It calculates the risk beyond VaR. Relative industry risk measurement is...