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...

Uncertain random variables provide a tool to deal with phenomena in which uncertainty and randomness simultaneously exist. This paper proposes a concept of value-at-risk to quantify the risk of an uncertain random system. In addition, a value-at-risk theorem is proved in order to calculate the value-at-risk, and is applied to series systems, parallel system, k -out-ofn system, standby system, a...

Investors use different approaches to select optimal portfolio. so, Optimal investment choices according to return can be interpreted in different models. The traditional approach to allocate portfolio selection called a mean - variance explains. Another approach is Markov chain. Markov chain is a random process without memory. This means that the conditional probability distribution of the nex...

K e y w o r d s: Family of Sign RCA Models, Value at Risk, backtesting, loss function.

Steven Morrison Steven [email protected] A common definition of an insurer’s economic capital requirements is based around a 1-year Value at Risk (VaR) metric. This defines capital requirements in terms of some tail percentile (typically the 99.5th percentile) of the market-consistent value of the insurer’s balance sheet in 1 year’s time. The problem of estimating such a metric naturally le...