IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1911.10948.html
   My bibliography  Save this paper

Denting the FRTB IMA computational challenge via Orthogonal Chebyshev Sliding Technique

Author

Listed:
  • Mariano Zeron-Medina Laris
  • Ignacio Ruiz

Abstract

In this paper we introduce a new technique based on high-dimensional Chebyshev Tensors that we call \emph{Orthogonal Chebyshev Sliding Technique}. We implemented this technique inside the systems of a tier-one bank, and used it to approximate Front Office pricing functions in order to reduce the substantial computational burden associated with the capital calculation as specified by FRTB IMA. In all cases, the computational burden reductions obtained were of more than $90\%$, while keeping high degrees of accuracy, the latter obtained as a result of the mathematical properties enjoyed by Chebyshev Tensors.

Suggested Citation

  • Mariano Zeron-Medina Laris & Ignacio Ruiz, 2019. "Denting the FRTB IMA computational challenge via Orthogonal Chebyshev Sliding Technique," Papers 1911.10948, arXiv.org, revised Dec 2020.
    • Handle: RePEc:arx:papers:1911.10948
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1911.10948
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mariano Zeron Medina Laris & Ignacio Ruiz, 2018. "Chebyshev Methods for Ultra-efficient Risk Calculations," Papers 1805.00898, arXiv.org.
    2. Maximilian Gaß & Kathrin Glau & Mirco Mahlstedt & Maximilian Mair, 2018. "Chebyshev interpolation for parametric option pricing," Finance and Stochastics, Springer, vol. 22(3), pages 701-731, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Andrea Maran & Andrea Pallavicini & Stefano Scoleri, 2021. "Chebyshev Greeks: Smoothing Gamma without Bias," Papers 2106.12431, arXiv.org.
    2. Mariano Zeron & Ignacio Ruiz, 2020. "Tensoring volatility calibration," Papers 2012.07440, arXiv.org, revised Dec 2020.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Grzelak, Lech A., 2022. "Sparse grid method for highly efficient computation of exposures for xVA," Applied Mathematics and Computation, Elsevier, vol. 434(C).
    2. Mariano Zeron & Ignacio Ruiz, 2020. "Dynamic sensitivities and Initial Margin via Chebyshev Tensors," Papers 2011.04544, arXiv.org.
    3. Lech A. Grzelak, 2021. "Sparse Grid Method for Highly Efficient Computation of Exposures for xVA," Papers 2104.14319, arXiv.org, revised May 2022.
    4. Andrea Maran & Andrea Pallavicini & Stefano Scoleri, 2021. "Chebyshev Greeks: Smoothing Gamma without Bias," Papers 2106.12431, arXiv.org.
    5. Kathrin Glau & Ricardo Pachon & Christian Potz, 2019. "Speed-up credit exposure calculations for pricing and risk management," Papers 1912.01280, arXiv.org.
    6. Kathrin Glau & Daniel Kressner & Francesco Statti, 2019. "Low-rank tensor approximation for Chebyshev interpolation in parametric option pricing," Papers 1902.04367, arXiv.org.
    7. Shuaiqiang Liu & Lech A. Grzelak & Cornelis W. Oosterlee, 2022. "The Seven-League Scheme: Deep Learning for Large Time Step Monte Carlo Simulations of Stochastic Differential Equations," Risks, MDPI, vol. 10(3), pages 1-27, February.
    8. Kathrin Glau & Ricardo Pachon & Christian Potz, 2019. "Fast Calculation of Credit Exposures for Barrier and Bermudan options using Chebyshev interpolation," Papers 1905.00238, arXiv.org.
    9. Darrold Cordes & Shahram Latifi & Gregory M. Morrison, 2022. "Systematic literature review of the performance characteristics of Chebyshev polynomials in machine learning applications for economic forecasting in low-income communities in sub-Saharan Africa," SN Business & Economics, Springer, vol. 2(12), pages 1-33, December.
    10. Mariano Zeron & Ignacio Ruiz, 2020. "Tensoring volatility calibration," Papers 2012.07440, arXiv.org, revised Dec 2020.
    11. Kathrin Glau & Mirco Mahlstedt & Christian Potz, 2018. "A new approach for American option pricing: The Dynamic Chebyshev method," Papers 1806.05579, arXiv.org.
    12. M. Khasi & J. Rashidinia, 2024. "A Bilinear Pseudo-spectral Method for Solving Two-asset European and American Pricing Options," Computational Economics, Springer;Society for Computational Economics, vol. 63(2), pages 893-918, February.
    13. Tat Lung Chan & Nicholas Hale, 2018. "Hedging and Pricing European-type, Early-Exercise and Discrete Barrier Options using Algorithm for the Convolution of Legendre Series," Papers 1811.09257, arXiv.org, revised May 2019.
    14. Damien Ackerer & Damir Filipović, 2020. "Linear credit risk models," Finance and Stochastics, Springer, vol. 24(1), pages 169-214, January.
    15. Griselda Deelstra & Lech A. Grzelak & Felix L. Wolf, 2022. "Accelerated Computations of Sensitivities for xVA," Papers 2211.17026, arXiv.org, revised Jan 2024.
    16. Leonardo Perotti & Lech A. Grzelak, 2022. "On Pricing of Discrete Asian and Lookback Options under the Heston Model," Papers 2211.03638, arXiv.org, revised Feb 2024.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:1911.10948. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.