Copula Based Monte Carlo Integration in Financial Problems
AbstractA 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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Bibliographic InfoPaper provided by Faculty of Economics, University of Cambridge in its series Cambridge Working Papers in Economics with number 0506.
Date of creation: Jan 2005
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Copula; Martingale; Monte Carlo Integral; Quantile Transform; Utility Function.;
Other versions of this item:
- Alessio Sancetta, 2004. "Copula Based Monte Carlo Integration in Financial Problems," Working Papers, Warwick Business School, Finance Group wp04-02, Warwick Business School, Finance Group.
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
- G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
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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