Dynamic Initial Margin via Chebyshev Tensors

2018/08/24 by Ignacio Ruiz, Ruiz, Ignacio, M. Zeron +1
Economics, Econometrics and Finance · Computer Science · #Monetary Policy and Economic Impact #Stochastic processes and financial applications #Computational Physics and Python Applications

paper · pdf · doi:10.48550/arxiv.1808.08221

Abstract

We present two methods, based on Chebyshev tensors, to compute dynamic sensitivities of financial instruments within a Monte Carlo simulation. These methods are implemented and run in a Monte Carlo engine to compute Dynamic Initial Margin as defined by ISDA (SIMM). We show that the levels of accuracy, speed and implementation efforts obtained, compared to the benchmark (DIM obtained calling pricing functions such as are found in risk engines), are better than those obtained by alternative methods presented in the literature, such as regressions (\citeZhu Chan) and Deep Neural Nets (\citeDNNs IM).

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