Function-approximation-based importance sampling for pricing american options

Proceedings - Winter Simulation Conference

Volumn 1, Issue , 2004, Pages 604-611

  Bolia, Nomesh ^a   Juneja, Sandeep ^a   Glasserman, Paul ^b  

^a TATA INSTITUTE OF FUNDAMENTAL RESEARCH   (India)

^b Columbia Business School ^*  (United States)

Author keywords

[No Author keywords available]

Indexed keywords

FUNCTION APPROXIMATION; OPTION PRICE; UPPER BOUNDS; ZERO-VARIANCE MEASURE;

APPROXIMATION THEORY; COMPUTER SIMULATION; ESTIMATION; FUNCTIONS; MONTE CARLO METHODS; PROBLEM SOLVING;

FINANCE;

EID: 17744374522     PISSN: 08917736     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (11)

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4. Glasserman, P. 2004. Monte Carlo Methods in Financial Engineering. Springer-Verlag, New York.
5. Glynn, P.W. and D.L. Iglehart. 1989. Importance Sampling for Stochastic Simulations. Management Science 35, 1367-1392.
6. Haugh, M. B. and L. Kogan. 2004. Pricing American Options: A Duality Approach. Operations Research 52-2, 258-270.
7. Jamshidian, F. 2003. Minimax Optimality of Bermudan and American Claims and their Monte-Carlo Upper Bound Approximation. Preprint.
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10. Longstaff, F. A., and E. S. Schwanz. 2001. Valuing American Options by Simulation: A Simple Least-Squares Approach, Review of Financial Studies 14, 113-147.
11. Tsitsiklis, J., and B. Van Roy. 2001. Regression Methods for Pricing Complex American-Style Options. IEEE Transactions on Neural Networks 12, 694-703.