Efficiently calibrating agent-based models (ABMs) to real data is an open challenge. This paper explicitly tackles parameter space exploration and calibration of ABMs by combining machine-learning and intelligent iterative sampling. The proposed approach "learns" a fast surrogate meta-model...

We introduce a financially constrained production framework in which heterogeneous firms and banks entertain multiple credit connections. The parameters of credit market interaction are estimated from real data in order to reproduce a set of empirical regularities of the Japanese credit market....

In this article, the Universal Approximation Theorem of Artificial Neural Networks (ANNs) is applied to the SABR stochastic volatility model in order to construct highly efficient representations. Initially, the SABR approximation of Hagan et al. [2002] is considered, then a more accurate...

This paper uses deep learning to value derivatives. The approach is broadly applicable, and we use a call option on a basket of stocks as an example. We show that the deep learning model is accurate and very fast, capable of producing valuations a million times faster than traditional models. We...

A major concern about the use of simulation models regards their relationship with the empirical data. The identification of a suitable indicator quantifying the distance between the model and the data would help and guide model selection and output validation. This paper proposes the use of a...

After Lehman default (credit crisis 2007), practitioners considered the default risk as a major risk. The regulators pushed the industry to use collateral in order to reduce the risk. In this new world, we want to see how this new considerations affect the theory related to the Partial...

Funding Valuation Adjustment (FVA) has been introduced as the CVA and DVA after the default of Lehman Brother. After the subprime crisis, the basis spread was not negligible anymore, credit and liquidity risk became the first concern. In addition, regulators put in place reforms, which associate...

After Lehman default and the Euro Crisis (crisis which started mid-2007), the industry started to consider the funding risk as a major risk. The practitioners began to charge for their funding cost. In this stressed context, the FVA has been the subject of intense debate, even its definition is...

Backtesting stock market investment strategies is fraught with danger – for example, overfitting. The signal to noise ratio in stock markets is so low that overfitting is inevitable. Simulation offers a means of assessing and compensating for the dangers. It is not obvious at first how...