This paper is intended as a guide to building insurance risk (loss) models. A typical model for insurance risk, the so-called collective risk model, treats the aggregate loss as having a compound distribution with two main components: one characterizing the arrival of claims and another...

This research examines if there exists an appealing distribution for jump amplitude in the sense that with this distribution, the stochastic volatility double jump-diffusions (SVJJ) model would potentially have a superior option market fit while keeping a sound balance between reality and...

This paper introduces a multivariate pure-jump Lévy process which allows for skewness and excess kurtosis of single asset returns and for asymptotic tail dependence in the multivariate setting. It is termed Variance Compound Gamma (VCG). The novelty of my approach is that, by applying a...

This paper introduces a multivariate pure-jump Lévy process which allows for skewness and excess kurtosis of single asset returns and for asymptotic tail dependence in the multivariate setting. It is termed Variance Compound Gamma (VCG). The novelty of my approach is that, by applying a...

According to IFRS 9, an Entity shall assess - by performing a quantitative assessment - the relevance of the modification of the time value of money element, i.e. the modification of the interest that can be observed, e.g. in all the instruments whose underlying interest rate tenors are...

We present a stochastic simulation model for estimating forward-looking corporate probability of default and loss given default. We formulate the model in a discrete time frame, apply capital-budgeting techniques to define the relationships that identify the default condition, and solve the...

Markov chain Monte Carlo (MCMC) methods have an important role in solving high dimensionality stochastic problems characterized by computational complexity. Given their critical importance, there is need for network and security risk management research to relate the MCMC quantitative...

We present a stochastic simulation forecasting model to stress-test banks' capital adequacy and to estimate probability of infringement of regulatory capital ratios and default probability. The stochastic methodology proposed is based on a simplified reduced model that provides a manageable...

We describe a Markov chain Monte Carlo method to approximately simulate high dimensional Gaussian vectors whose covariance matrix is easy to compute. The standard Monte Carlo method is based on the Cholesky decomposition, which is performed in cubic time and quadratic storage cost in the...