2 citations · 3 across the 4 of their papers we have counts for
4 papers · 1 filter
Analytic expressions for the output evolution of a deep neural network
Anastasia Borovykh
We present a novel methodology based on a Taylor expansion of the network output for obtaining analytical expressions for the expected value of the network weights and output under…
Efficient Computation of Various Valuation Adjustments Under Local Lévy Models
Anastasia Borovykh, Andrea Pascucci, Cornelis W. Oosterlee
Various valuation adjustments, or XVAs, can be written in terms of non-linear PIDEs equivalent to FBSDEs. In this paper we develop a Fourier-based method for solving FBSDEs in orde…
A neural network-based framework for financial model calibration
Shuaiqiang Liu, Anastasia Borovykh, Lech A. Grzelak +1
A data-driven approach called CaNN (Calibration Neural Network) is proposed to calibrate financial asset price models using an Artificial Neural Network (ANN). Determining optimal…
Generalisation in fully-connected neural networks for time series forecasting
Anastasia Borovykh, Cornelis W. Oosterlee, Sander M. Bohte
In this paper we study the generalization capabilities of fully-connected neural networks trained in the context of time series forecasting. Time series do not satisfy the typical…