We develop two neo-classical methods for function approximations, the generalized stochastic sampling (gSS) and the functional tensor train (fTT) methods, that are high-performing alternatives to generic deep neural networks (DNNs) currently routinely proposed for function approximations in...

We analyze the effects of the financial crisis in credit valuation adjustments (CVA's). Following the arbitrage-free valuation framework presented in Brigo et al. (2009), we consider a model with stochastic Gaussian interest rates and CIR++ default intensities. Departing from previous...

This paper proposes the use of analytical approximations to price an heterogeneous basket option combining commodity prices, foreign currencies and zero-coupon bonds. The performance of three moment matching approximations is examined: inverse gamma, Edgeworth expansion around the lognormal and...

We derive a closed-form expression for the bilateral credit valuation adjustment of a credit default swap in presence of simultaneous defaults. We develop our analysis under a default intensity model specified by a class of three-dimensional subordinators, allowing for default dependence through...

We derive a closed-form expression for the bilateral credit valuation adjustment of a credit default swap in presence of simultaneous defaults. We develop our analysis under a default intensity model specified by a class of three-dimensional subordinators, allowing for default dependence through...

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...

Chen and Shen (2003) argue that it is possible to improve the Least Squares Monte Carlo Method (LSMC) of Longstaff and Schwartz (2001) to value American options by removing the least squares regression module. This would make not only faster but also more accurate. We demonstrate, using a large...

Mean reversion, stochastic volatility, convenience yield and presence of jump clustering are well documented salient features of commodity markets, where Asian options are very popular. We propose a model which takes into account all these stylized features. We first state our model under the...

The Implicit Function Theorem, or IFT, is a powerful tool for calculating derivatives of functions that solve inverse, i.e. calibration, problems prevalent in financial applications. It is commonly believed that a degree of manual intervention is required to enable financial code to take...

This paper explores Artificial Neural Network (ANN) as a model-free solution for a calibration algorithm of option pricing models. We construct ANNs to calibrate parameters for two well-known GARCH-type option pricing models: Duan’s GARCH and the classical tempered stable GARCH that...