Journal of Economic Dynamics and Control · 1997 · 637 citations · 44 references
BusinessEconomicsFinanceAsset PricingFinancial EconomicsQuantitative FinanceAsset Pricing EmpiricsAsset Return ModelingMonte Carlo MethodsMonte Carlo SimulationNumerical Methods In FinanceSimulation MethodsConfidence Interval ConstructionConfidence Interval EstimationEarly Exercise BehaviorError BoundsError Bounds EstimationMonte Carlo PricingSecurities FinanceState Variables
We develop a simulation algorithm for estimating the prices of American-style securities, i.e., securities with opportunities for early exercise. Our algorithm provides both point estimates and error bounds for the true security price. It generates two estimates, one biased high and one biased low, both asymptotically unbiased and converging to the true price. Combining the two estimators yields a confidence interval for the true price. The proposed algorithm is especially attractive (compared with lattice and finite-difference methods) when there are multiple state variables and a small number of exercise opportunities. Preliminary computational evidence is given.
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Eduardo S. Schwartz, Avinash Dixit, Robert S. Pindyck · The Journal of Finance · 1994 · 9.9K citations
Option pricing: A simplified approach
John C. Cox, Stephen A. Ross, Mark Rubinstein · Journal of Financial Economics · 1979 · 6.2K citations
Simulation modeling and analysis
Journal of Manufacturing Systems · 1999 · 3.8K citations
Business, Computational Engineering, Systems Engineering +11