Cayetano, Gea (2006): Valuing a portfolio of dependent RandD projects: a Copula approach.
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Abstract
The aim of this work consists of pricing a real biotechnology firm that is based on a portfolio of several drug development projects at different phases. Duffie and Singleton (1999) formulate a system of n correlated jump mean-reverting intensity equations to capture a portfolio of n entities’ default times. The drawback of their approach is that there are a lot of parameters and we have no enough information so as to estimate all. This is the reason why the copula approach has been very well accepted in recent years as an alternative tool for these situations since we can model the extreme situations (or default in this case) under a dependence framework by selecting those copula functions with a very few number of parameters.
Item Type: | MPRA Paper |
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Original Title: | Valuing a portfolio of dependent RandD projects: a Copula approach |
Language: | English |
Keywords: | Copula, valuation, company, real options |
Subjects: | C - Mathematical and Quantitative Methods > C0 - General > C00 - General |
Item ID: | 8743 |
Depositing User: | Cayetano Gea |
Date Deposited: | 14 May 2008 00:47 |
Last Modified: | 27 Sep 2019 06:27 |
References: | [1] Caperaa and Genest: A nonparametric estimation procedure for bivariate extreme value copulas. Biometrika, Sept. 1997, vol. 84. [2] Chan Chiou: Multivariate Continuous Time Models through copulas (2004). [3] Duffie, D. and K. Singleton (1999): “Simulating Correlated Defaults”, Working Paper, Graduate School of Business, Stanford University. [4] Duffie, D. and K. Singleton (2000): “Simulating Correlated Defaults. A revision”, Working Paper, Graduate School of Business, Stanford University. [5] Devroye, L.: Non uniform random variables generation.Mc Graw Hill. Chapter 10, pages 548-558. [6] Embechts, McNeil and Straumann (1999): Correlation and dependence in risk management. Cambridge University Press. [7] Embrechts, Frey and McNeil (2001): Quantitative Risk Management. Princeton University Press. [8] Frees, E. W. and E. A. Valdez: Understanding relationship using copulas. North American Actuarial Journal. 2(1):1-25 (1998). [9] Genest, Christian: Statistical inference procedure for Archimedean copula models. Journal of American Statistical Association. Vol. 88, September 1993. [10] Kole, Eric: Testing copulas to model financial dependence. Erasmus University, Rotterdam. [11] León and Piñero (2004): Valuation of a biotech company: A real option approach. Cemfi Working Paper 0420. [12]Marshall and Olkin (1988): Families of Multivariate Distributions. Journal of the American Statistical Association. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/8743 |