Maximum Relative Drawdown measures the largest percentage drop of the price process on a given time interval. Recently, Maximum Relative Drawdown has become more popular as an alternative measure of risk. In contrast to the Value at Risk measure, it captures the path property of the price process. In this article, we propose a partial differential equation approach to determine the theoretical ...

Incorporating the Poisson jumps and exchange rate risk, this paper provides an analytical VaR to manage market risk of international portfolios over the subprime mortgage crisis. There are some properties in the model. First, different from past studies in portfolios valued only in one currency, this model considers portfolios not only with jumps but also with exchange rate risk, that is vital ...

Risks faced by traders from price movements are sometimes magni¿ed by the actions of other traders. Risk management systems which neglect this feature may give a seriously misleading picture of the true risks. The hazards arising from this potential blindspot are at their most dangerous when the prevailing conventional wisdom lulls traders into a false sense of security on the attractivenss of ...

We propose an extension of the CPPI method, which is based on conditional floors. In this framework, we examine in particular the margin based strategies. This method allows to keep part of the past gains and to protect the portfolio value against future high drawdowns of the financial market. However, as for the standard CPPI method, the investor can benefit from potential market rises. To con...

Related to the current discussion of value-at-risk-based capital allocation and performance management (RAPM) for managing bank capital, a risk theoretical RAPM-approach for propertylliability-insurance companies is presented. The paper discusses several central issues of a RAPM-approach: Virtual risk adjusted capital (VRAC) on the company level, return on risk adjusted capital (RORAC), risk ba...

The ν-support vector classification (ν-SVC) algorithm was shown to work well and provide intuitive interpretations, e.g., the parameter ν roughly specifies the fraction of support vectors. Although ν corresponds to a fraction, it cannot take the entire range between 0 and 1 in its original form. This problem was settled by a non-convex extension of ν-SVC and the extended method was experimental...

In this paper, we prove an exponential rate of convergence result for a common estimator of conditional value-at-risk for bounded random variables. The bound on optimistic deviations is tighter while the bound on pessimistic deviations is more general and applies to a broader class of convex risk measures. © 2007 Elsevier B.V. All rights reserved.

Value at risk (VaR) is the standard measure of market risk used by financial institutions. Interpreting the VaR as the quantile of future portfolio values conditional on current information, the conditional autoregressive value at risk (CAViaR) model specifies the evolution of the quantile over time using an autoregressive process and estimates the parameters with regression quantiles. Utilizin...

The concept of coherent risk measure was introduced in Artzner et al. (1999). They listed some properties, called axioms of ‘coherence’, that any good risk measure should possess, and studied the (non-)coherence of widely-used risk measure such as Value-atRisk (VaR) and expected shortfall (also known as tail conditional expectation or tail VaR). Kusuoka (2001) introduced two additional axioms c...

Genet ic algor ithms (GAs) continue to receive increased attention as general-p ur pos e met hods for search and optimization . GAs are attrac t ive for search in complex spaces where the fun ction al relati onsh ips between paramet ers and ob jective function values are of unknown , arb itrary mat hemati cal charac te r. Desp ite t heir generally robust character, typical GAs are known to fare...