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A quantization approach to the counterparty credit exposure estimation

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  • Bonollo, Michele
  • Di Persio, Luca
  • Oliva, Immacolata

Abstract

During recent years the counterparty risk field has received a growing attention because of the Basel Accord, which asks banks to fulfill finer conditions concerning counterparty credit exposures arising from banks’ derivatives, securities financing transactions, default and downgrade risks characterizing the Over The Counter derivatives market, etc. Consequently, the development of effective and more accurate measures of risk have been pushed, particularly focusing on the estimate of the future fair value of derivatives with respect to prescribed time horizon and fixed grid of time buckets. Common methods, used to treat the latter scenario, are mainly based on ad hoc implementations of the Monte Carlo approach, characterized by a high computational cost, being strongly dependent on the number of considered assets. This is why many financial players moved to more effective and time saving technologies, e.g., based on grid computing and Graphics Processing Units (GPU) capabilities. In the present paper we exploit an alternative approach based on different algorithmic strategies by showing how to implement the quantization technique to derive accurate estimate for both pricing and volatility values. Our approach turns out to produce sharp results for the counterparty risk evaluation, with great computational benefits if compared to the Monte Carlo approach.

Suggested Citation

  • Bonollo, Michele & Di Persio, Luca & Oliva, Immacolata, 2020. "A quantization approach to the counterparty credit exposure estimation," International Review of Economics & Finance, Elsevier, vol. 70(C), pages 335-356.
    • Handle: RePEc:eee:reveco:v:70:y:2020:i:c:p:335-356
    DOI: 10.1016/j.iref.2020.08.005
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    References listed on IDEAS

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    6. Heston, Steven L, 1993. "A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options," The Review of Financial Studies, Society for Financial Studies, vol. 6(2), pages 327-343.
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    Cited by:

    1. Michele Bonollo & Luca Di Persio & Luca Mammi & Immacolata Oliva, 2017. "Estimating the Counterparty Risk Exposure by using the Brownian Motion Local Time," Papers 1704.03244, arXiv.org.
    2. Erdinc Akyildirim & Alper A. Hekimoglu & Ahmet Sensoy & Frank J. Fabozzi, 2023. "Extending the Merton model with applications to credit value adjustment," Annals of Operations Research, Springer, vol. 326(1), pages 27-65, July.

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    More about this item

    Keywords

    Quantization; Counterparty credit risk; Expected positive exposure; European option;
    All these keywords.

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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