paper analyzes the impact of model complexity on the valuation of project financed investments along two dimensions: The NPV distribution and the expected default probability of the project. Model complexity is separated in forecast and simulation complexity. Thereby, we aim to identify elements...

In the ideal Black-Scholes world, financial time series are assumed 1) stationary (time homogeneous) and 2) having conditionally normal distribution given the past. These two assumptions have been widely-used in many methods such as the RiskMetrics, one risk management method considered as...

Over recent years, study on risk management has been prompted by the Basel committee for regular banking supervisory. There are however limitations of some widely-used risk management methods that either calculate risk measures under the Gaussian distributional assumption or involve numerical...

Risk management technology applied to high dimensional portfolios needs simple and fast methods for calculation of Value-at-Risk (VaR). The multivariate normal framework provides a simple off-the-shelf methodology but lacks the heavy tailed distributional properties that are observed in data. A...

In this paper we propose the GHADA risk management model that is based on the generalized hyperbolic (GH) distribution and on a nonparametric adaptive methodology. Compared to the normal distribution, the GH distribution possesses semi-heavy tails and represents the financial risk factors more...

We perform a general equilibrium analysis in a complete markets economy whenthe dividend follows a jump-diffusion process with stochastic volatility. Agents haveCRRA utility, but differ with respect to their degree of risk aversion. The keyoutput of our analysis is the structure of the...

In this paper we perform a general equilibrium analysis when the dividend followsa jump-diffusion process with stochastic volatility, where both the dividend itselfand its volatility can jump. We work in a complete markets economy and assumethat agents have CRRA utility, but can differ with...

Since trading cannot take place continuously, the optimal portfolio calculated ina continuous-time model cannot be held, but the investor has to implement thecontinuous-time strategy in discrete time. This leads to the question how severe theresulting discretization error is. We analyze this...

This paper analyzes the properties of and the differences between derivative pricingmodels that include stochastic volatility or stochastic jumps or both of these riskfactors. The focus is on the pricing of European options. In a first step, we discussthe impact of the parameters in stochastic...

The vast majority of approaches to risk management, hedging, or portfolio planningassume that some model is given. However, under model risk, the true data gener-ating process is not known. The focus of this paper is on problems related to thehedging of derivative contracts. We explain the main...