All

What are you looking for?

All
Projects
Results
Organizations

Quick search

  • Projects supported by TA ČR
  • Excellent projects
  • Projects with the highest public support
  • Current projects

Smart search

  • That is how I find a specific +word
  • That is how I leave the -word out of the results
  • “That is how I can find the whole phrase”

Acceleration of multi-factor Merton model Monte Carlo simulation via Importance Sampling and GPU parallelization

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F16%3A86098980" target="_blank" >RIV/61989100:27240/16:86098980 - isvavai.cz</a>

  • Alternative codes found

    RIV/61989100:27740/16:86098980

  • Result on the web

    <a href="http://dx.doi.org/10.1201/b21348-19" target="_blank" >http://dx.doi.org/10.1201/b21348-19</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1201/b21348-19" target="_blank" >10.1201/b21348-19</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Acceleration of multi-factor Merton model Monte Carlo simulation via Importance Sampling and GPU parallelization

  • Original language description

    Credit risk refers to the risk of losses due to unexpected credit events, as a default of a counterparty. The modelling and controlling of credit risk is a very important topic within banks. Very popular and frequently used tools for modelling credit risk are multi-factor Merton models. Practical implementation of these models requires time-consuming Monte Carlo (MC) simulations, which significantly limits their usability in daily credit risk calculation. In this paper we present acceleration techniques of Merton model Monte Carlo simulations, concretely parallel GPU implementation and Importance Sampling (IS) employment. As the importance sampling distribution we choose the Gaussian mixture model and for calculating the IS shifted probability distribution we use the Cross-Entropy (CE) method. The speed-up results are demonstrated using portfolio Value at Risk (VaR) and Expected Shortfall (ES) calculation.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    BB - Applied statistics, operational research

  • OECD FORD branch

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2016

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Applied Mathematics in Engineering and Reliability : proceedings of the 1st International Conference on Applied Mathematics in Engineering and Reliability : Ho Chi Minh City, Vietnam, 4-6 May 2016

  • ISBN

    978-1-138-02928-6

  • ISSN

  • e-ISSN

  • Number of pages

    12

  • Pages from-to

    107-118

  • Publisher name

    CRC PRESS-TAYLOR &amp; FRANCIS GROUP

  • Place of publication

    London

  • Event location

    Ho Či Minovo Město

  • Event date

    May 4, 2016

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000387432400015