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Estimating the counterparty risk exposure by using the Brownian motion local time

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In recent years, the counterparty credit risk measure, namely the default risk in over-the-counter (OTC) derivatives contracts, has received great attention by banking regulators, specifically within the frameworks of Basel II and Basel III. More explicitly, to obtain the related risk figures, one is first obliged to compute intermediate output functionals related to the mark-to-market position at a given time no exceeding a positive and finite time horizon. The latter implies an enormous amount of computational effort is needed, with related highly time consuming procedures to be carried out, turning out into significant costs. To overcome the latter issue, we propose a smart exploitation of the properties of the (local) time spent by the Brownian motion close to a given value.
Rocznik
Strony
435--447
Opis fizyczny
Bibliogr. 37 poz., tab., wykr.
Twórcy
autor
  • IMT Lucca/Iason Ltd/Numerix LLC, Piazza S. Francesco 19, 55100 Lucca (LU), Via Torino 2, 20123 Milan, Italy
autor
  • Department of Computer Science, University of Verona, Strada le Grazie 15, 37134 Verona (VR), Italy
autor
  • Unicredit Group, Tower A, Piazza Gae Aulenti, 3, 20154 Milan, Italy
autor
  • Department of Economics, University of Verona, Via Cantarane 24, 30129 Verona (VR), Italy
Bibliografia
  • [1] Antonov, A., Issakov, S. and Mechkov, S. (2015). Backward induction for future values, Risk.net, Numerix research paper, http://www.risk.net/derivatives/2387384/backward-inductionfuture-values.
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  • [7] Borodin, A. and Salminen, P. (2002). Handbook of Brownian Motion: Facts and Formulae, 2nd Edn., Birkh¨auser, Basel.
  • [8] Brigo, D., Morini, M. and Pallavicini, A. (2013). Counterparty Credit Risk, Collateral and Funding: With Pricing Cases for All Asset Classes, Wiley, Chichester.
  • [9] Brydges, D., Van Der Hofstad, R. and Konig, W. (2007). Joint density for the local times of continuous-time Markov chains, The Annals of Probability 35(4): 1307–1332.
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  • [12] Callegaro, G. and Sagna, A. (2013). An application to credit risk of a hybrid Monte Carlo optimal quantization method, Journal of Computational Finance 16(4): 123–156.
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  • [30] Liu, Q. (2015). Calculation of credit valuation adjustment based on least square Monte Carlo methods, Mathematical Problems in Engineering 2015, Article ID: 959312, DOI: 10.1155/2015/959312.
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Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-39089bd9-0611-40cb-b983-bb2e5cdafac8
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