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Hybrid Monte Carlo methods in credit risk management
-
Lucia Del Chicca
and
Gerhard Larcher
Published/Copyright:
October 18, 2014
Abstract
In this paper we analyze and compare the use of Monte Carlo, quasi-Monte Carlo and hybrid Monte Carlo methods in the credit risk management system “Credit Metrics” by J. P. Morgan. We show that hybrid sequences, used suitably for simulations, perform better, in many relevant situations, than pure Monte Carlo and pure quasi-Monte Carlo methods, and they only rarely perform worse than these methods.
MSC: 65C05
Funding source: Austrian Science Fund (FWF)
Award Identifier / Grant number: Project F5507-N26
The authors would like to thank Isabel Pirsic for some fruitful discussions about implementations of very high dimensional Niederreiter point set.
Received: 2014-3-18
Accepted: 2014-10-7
Published Online: 2014-10-18
Published in Print: 2014-12-1
© 2014 by De Gruyter
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- Frontmatter
- A numerical scheme based on semi-static hedging strategy
- A martingale approach to estimating confidence band with censored data
- Hybrid Monte Carlo methods in credit risk management
- Uncertainty quantification of world population growth: A self-similar PDF model
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Articles in the same Issue
- Frontmatter
- A numerical scheme based on semi-static hedging strategy
- A martingale approach to estimating confidence band with censored data
- Hybrid Monte Carlo methods in credit risk management
- Uncertainty quantification of world population growth: A self-similar PDF model
- Stochastic polynomial chaos based algorithm for solving PDEs with random coefficients
