LOCALIZED MONTE CARLO ALGORITHM TO COMPUTE PRICES OF PATH DEPENDENT OPTIONS ON TREES

Sebastian E. Ferrando () and Ariel J. Bernal ()
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Sebastian E. Ferrando: Department of Mathematics, Physics and Computer Science, Ryerson University, 350 Victoria St., Toronto, Ontario M5B 2K3, Canada
Ariel J. Bernal: Department of Computer Science, Caece University, Olavarria 2464, Mar del Plata 7600, Argentina

International Journal of Theoretical and Applied Finance (IJTAF), 2005, vol. 08, issue 05, 553-574

Abstract: A new simulation based algorithm to approximate prices of path dependent European options is introduced. The algorithm is defined for tree-like approximations to the underlying process and makes extensive use of structural properties of the discrete approximation. We indicate the advantages of the new algorithm in comparison to standard Monte Carlo algorithms. In particular, we prove a probabilistic error bound that compares the quality of both approximations. The algorithm is of general applicability and, for a large class of options, it has the same computational complexity as Monte Carlo.

Keywords: Exotic options; Monte Carlo; binomial trees (search for similar items in EconPapers)
Date: 2005
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DOI: 10.1142/S0219024905003177

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