We put forward a Merton-type multi-factor portfolio model for assessing banks’ contributions to systemic risk. This model accounts for the major drivers of banks’ systemic relevance: size, default risk and correlation of banks’ assets as a proxy for interconnectedness. We measure systemic...

The computation of various risk metrics is essential to the quantitative risk management of variable annuity guaranteed benefits. The current market practice of Monte Carlo simulation often requires intensive computations, which can be very costly for insurance companies to implement and take so...

We put forward a framework for measuring systemic risk and attributing it to individual banks. Systemic risk is measured as the expected loss to depositors and investors when a low-probability systemic event occurs. The risk contributions are calculated based on derivatives of the systemic risk...

Value-at-Risk bounds for aggregated risks have been derived in the literature in settings where besides the marginal distributions of the individual risk factors one-sided bounds for the joint distribution respectively the copula of the risks are available. In applications it turns out that...

We put forward a Merton-type multi-factor portfolio model for assessing banks' contributions to systemic risk. This model accounts for the major drivers of banks' systemic relevance: size, default risk and correlation of banks' assets as a proxy for interconnectedness. We measure systemic risk...

In a context of an ever-changing regulatory environment over the last years, Banks have witnessed the draft and publication of several regulatory guidelines and requirements in order to frame and structure their internal Risk Management.Among these guidelines, one has been specifically designed...

We present four numerical methods to compute the Value-at-Risk and Expected Shortfall risk measure values of portfolios with financial options. The numerical methods are based on either wavelets or Fourier cosine approximations and belong to the class of Fourier inversion methods. We show that...

Factor modeling is a popular strategy to induce sparsity in multivariate models as they scale to higher dimensions. We develop Bayesian inference for a recently proposed latent factor copula model, which utilizes a pair copula construction to couple the variables with the latent factor. We use...

The present article deals with intra-horizon risk in models with jumps. Our general understanding of intra-horizon risk is along the lines of the approach taken in [BRSW04], [Ro08], [BMK09], [BP10], and [LV19]. In particular, we believe that quantifying market risk by strictly relying on...