We propose how deep neural networks can be used to calibrate the parameters of Stochastic-Volatility Jump-Diffusion (SVJD) models to historical asset return time series. 1-Dimensional Convolutional Neural Networks (1D-CNN) are used for that purpose. The accuracy of the deep learning approach is...

We investigate valuation of derivatives with payoff defined as a nonlinear though close to linear function of tradable underlying assets. Interest rate derivatives involving Libor or swap rates in arrears, i.e. rates paid at wrong time, are a typical example. It is generally tempting to replace...

The paper proposes an application of the survival time analysis methodology to estimations of the Loss Given Default (LGD) parameter. The main advantage of the survival analysis approach compared to classical regression methods is that it allows exploiting partial recovery data. The model is...

The paper proposes a new method to estimate correlation of account level Basle II Loss Given Default (LGD). The correlation determines the probability distribution of portfolio level LGD in the context of a copula model which is used to stress the LGD parameter as well as to estimate the LGD...

The goal of the Basle II regulatory formula is to model the unexpected loss on a loan portfolio. The regulatory formula is based on an asymptotic portfolio unexpected default rate estimation that is multiplied by an estimate of the loss given default parameter. This simplification leads to a...

The credit valuation adjustment (CVA) of OTC derivatives is an important part of the Basel III credit risk capital requirements and current accounting rules. Its calculation is not an easy task - not only it is necessary to model the future value of the derivative, but also the probability of...

Market value of derivatives after crisis requires discounting with interest rates that take into account the credit risk of the involved counterparties of the trade. The increase of credit risk is evidenced by the presence of basis swap spreads. Using one curve to both estimating the forward...

The paper proposes an application of the survival time analysis methodology to estimations of the Loss Given Default (LGD) parameter. The main advantage of the survival analysis approach compared to classical regression methods is that it allows exploiting partial recovery data. The model is...

The Basle II parameter called Loss Given Default (LGD) aims to estimate the expected losses on not yet defaulted accounts in the case of default. Banks firstly need to collect historical recovery data, discount the recovery income and cost cash flow to the time of default, and calculate...

The paper provides an overview of the Exposure at Default (EAD) definition, requirements, and estimation methods as set by the Basel II regulation. A new methodology connected to the intensity of default modeling is proposed. The numerical examples show that various estimation techniques may...