American Option Pricing Using Simulation and Regression: Numerical Convergence Results

DOI10.1007/978-1-4614-3433-7_5zbMath1296.91287OpenAlexW1585146667MaRDI QIDQ2920953

Lars Stentoft

Publication date: 29 September 2014

Published in: Topics in Numerical Methods for Finance (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-1-4614-3433-7_5

Mathematics Subject Classification ID

Numerical methods (including Monte Carlo methods) (91G60) Monte Carlo methods (65C05) Derivative securities (option pricing, hedging, etc.) (91G20)

Related Items (5)

American Option Pricing Using Simulation and Regression: Numerical Convergence Results ⋮ A Comparison Between Different Numerical Schemes for the Valuation of Unit-Linked Contracts Embedding a Surrender Option ⋮ Fair dynamic valuation of insurance liabilities: a loss averse convex hedging approach ⋮ Fair dynamic valuation of insurance liabilities: merging actuarial judgement with market- and time-consistency ⋮ Fair dynamic valuation of insurance liabilities via convex hedging

Cites Work

• The longstaff-Schwartz algorithm for Lévy models: results on fast and slow convergence
• Assessing the least squares Monte-Carlo approach to American option valuation
• On the pricing of American options
• Valuation of the early-exercise price for options using simulations and nonparametric regression
• Pricing American-style securities using simulation
• On the robustness of least-squares Monte Carlo (LSM) for pricing American derivatives
• An analysis of a least squares regression method for American option pricing
• Number of paths versus number of basis functions in American option pricing
• American Option Pricing Using Simulation and Regression: Numerical Convergence Results
• Valuing American Options by Simulation: A Simple Least-Squares Approach
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