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An Extension of Least Squares Monte Carlo Simulation for Multi-options Problems
http://www.erasmusenergy.com/articles/75/1/An-Extension-of-Least-Squares-Monte-Carlo-Simulation-for-Multi-options-Problems/Page1.html
Andrea Gamba

Research fields:

Real options and the valuation of managerial flexibility.

Capital structure, agency problems, and investment decisions.

Numerical methods for derivatives valuation

Structural estimation of real options

 
By Andrea Gamba
Published on 10/11/2007
 
Keywords:
Published in:
Publication year: 2002

This paper provides a valuation algorithm based on Monte Carlo simulation for valuing a wide set of capital budgeting problems with many embedded real options dependent on many state variables. Along the lines of Gamba and Trigeorgis (2002b), we decompose a complex real option problem with many options into a set of simple options, properly taking into account deviations from value additivity due to interaction and strategical interdependence of the embedded real options, as noted by Trigeorgis (1993). The valuation approach presented in this paper is alternative to the general switching approach for valuing complex option problems (see Kulatilaka and Trigeorgis (1994) and Kulatilaka (1995)). The numerical algorithm presented in this paper is based on simulation, and extends the LSM approach presented in Longstaff and Schwartz (2001) to a multi-options setting in order to implement the modular valuation approach introduced in Gamba and Trigeorgis (2002). We provide also an array of numerical results to show he convergence of the algorithm and a few real life capital budgeting problems, including the extension of Schwartz and Moon (2000,2001) for valuing growth companies, to see how they can be tackled using our approach.

An Extension of Least Squares Monte Carlo Simulation for Multi-options Problems

This paper provides a valuation algorithm based on Monte Carlo simulation for valuing a wide set of capital budgeting problems with many embedded real options dependent on many state variables. Along the lines of Gamba and Trigeorgis (2002b), we decompose a complex real option problem with many options into a set of simple options, properly taking into account deviations from value additivity due to interaction and strategical interdependence of the embedded real options, as noted by Trigeorgis (1993). The valuation approach presented in this paper is alternative to the general switching approach for valuing complex option problems (see Kulatilaka and Trigeorgis (1994) and Kulatilaka (1995)). The numerical algorithm presented in this paper is based on simulation, and extends the LSM approach presented in Longstaff and Schwartz (2001) to a multi-options setting in order to implement the modular valuation approach introduced in Gamba and Trigeorgis (2002). We provide also an array of numerical results to show he convergence of the algorithm and a few real life capital budgeting problems, including the extension of Schwartz and Moon (2000,2001) for valuing growth companies, to see how they can be tackled using our approach.