Copula Based Monte Carlo Integration in Financial Problems

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Copula Based Monte Carlo Integration in Financial Problems

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Sancetta, A.

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Alessio Sancetta

Abstract

A computational technique that transform integrals over RK, or some of its subsets, into the hypercube [0, 1]K can be exploited in order to solve integrals via Monte Carlo integration without the need to simulate from the original distribution; all that is needed is to simulate iid uniform [0, 1] pseudo random variables. In particular the technique arises from the copula representation of multivariate distributions and the use of the marginal quantile function of the data. The procedure is further simplified if the quantile function has closed form. Several financial applications are considered in order to highlight the scope of this numerical technique for financial problems

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Paper provided by Faculty of Economics, University of Cambridge in its series Cambridge Working Papers in Economics with number 0506.

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Length: 34
Date of creation: Jan 2005
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Handle: RePEc:cam:camdae:0506

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Find related papers by JEL classification:
C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Statistical Simulation Methods
G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
G12 - Financial Economics - - General Financial Markets - - - Asset Pricing

This paper has been announced in the following NEP Reports:

NEP-ALL-2005-02-01 (All new papers)
NEP-CMP-2005-02-01 (Computational Economics)
NEP-ECM-2005-02-01 (Econometrics)
NEP-FIN-2005-02-01 (Finance)

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Other versions:
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Other versions:
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