In this paper we study a classical option-based portfolio strategy which minimizes the Value-at-Risk of the hedged position in a continuous time, regime-switching jump-diffusion market, by using Fourier Transform methods. However, the analysis of this hedging strategy, as well as the computational technique for its implementation, is fairly general, i.e. it can be applied to any dynamical model...

A new approach for cost-sensitive classification is proposed. We extend the framework of cost-sensitive learning to mitigate risks of huge costs occurring with low probabilities, and propose an algorithm that achieves this goal. Instead of minimizing the expected cost commonly used in cost-sensitive learning, our algorithm minimizes expected shortfall, a.k.a. conditional value-at-risk, known as...

Value-at-risk (VaR) has become the standard criterion for assessing risk in the financial industry. Given the widespread usage of VaR, it becomes increasingly important to study the effects of VaR-based risk management on the prices of stocks and options. We solve a continuous-time asset pricing model, based on Lucas (1978) and Basak and Shapiro (2001), to investigate these effects. We find tha...

We investigate why spreads on corporate bonds are so much larger than expected losses from default. Systematic factors make very little contribution to spreads, even if higher moments or downside effects are taken into account. Instead we find that sizes of spreads are strongly related to idiosyncratic-risk factors: not only to idiosyncratic equity volatility, but even more to idiosyncratic bon...

Risk adjusted performance measurement for a portfolio involves calculating the risk contribution of each single asset. We show that there is only one definition for the risk contributions which is suitable for performance measurement, namely as derivative of the underlying risk measure in direction of the considered asset weight. We also compute the derivatives for some popular risk measures in...

A two-sided Weibull is developed to model the conditional financial return distribution, for the purpose of forecasting Value at Risk (VaR) and conditional VaR. A range of conditional return distributions are combined with four volatility specifications to forecast tail risk in four international markets, two exchange rates and one individual asset series, over a four year forecast period that ...

We propose a new approach to portfolio optimization by separating asset return distributions into positive and negative half-spaces. The approach minimizes a so-called Partitioned Value-atRisk (PVaR) measure by using half-space statistical information. Using simulated and real data, the PVaR approach generates better risk-return tradeoffs in the optimal portfolios when compared to Markowitz mea...

In this paper we will observe a class of convex measures of risk whose values depend on the random variable only up to the λ-quantile for some given constant λ ∈ (0, 1]. For this class of convex risk measures, the assumption of the Fatou property can be weakened and we provide the robust representation theorem via convex duality method. As an example, the Weighted Value-of-Risk, which includes ...

Risk management through marginal rebalancing is important for institutional investors due to the size of their portfolios. We consider the problem of improving marginally portfolio VaR and CVaR through a marginal change in the portfolio return characteristics. We study the relative significance of standard deviation, mean, tail thickness, and skewness in a parametric setting assuming a Student’...

This paper evaluates the data from the recent financial crisis to examine the risk spillover effects of financial markets value at risk (VaR), which captures the extreme behavior of an asset, is considered a measure of risk in an asset or in a market. We hypothesize that an extreme downside movement of returns in a market measured by a VaR has negative effects on other markets, causing a simila...