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Dynamic Initial Margin via Chebyshev Tensors

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  • Ignacio Ruiz
  • Mariano Zeron

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 (\cite{Zhu Chan}) and Deep Neural Nets (\cite{DNNs IM}).

Suggested Citation

  • Ignacio Ruiz & Mariano Zeron, 2018. "Dynamic Initial Margin via Chebyshev Tensors," Papers 1808.08221, arXiv.org, revised Mar 2020.
    • Handle: RePEc:arx:papers:1808.08221
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    References listed on IDEAS

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    1. Maximilian Ga{ss} & Kathrin Glau & Mirco Mahlstedt & Maximilian Mair, 2015. "Chebyshev Interpolation for Parametric Option Pricing," Papers 1505.04648, arXiv.org, revised Jul 2016.
    2. Caspers, Peter & Giltinan, Paul & Lichters, Roland & Nowaczyk, Nikolai, 2017. "Forecasting initial margin requirements: A model evaluation," Journal of Risk Management in Financial Institutions, Henry Stewart Publications, vol. 10(4), pages 365-394, October.
    3. Moran, Lee & Wilkens, Sascha, 2017. "Capturing initial margin in counterparty risk calculations," Journal of Risk Management in Financial Institutions, Henry Stewart Publications, vol. 10(2), pages 118-129, April.
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