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Pricing Financial Instruments: The Finite Difference Method
Curt Randall,Domingo Tavella +1 more
TLDR
The Pricing Equations. as mentioned in this paper and the Finite-difference method are the most commonly used methods for finite difference methods in the literature, and they can be found in:Abstract:
The Pricing Equations. Analysis of Finite Difference Methods. Special Issues. Coordinate Transformations. Numerical Examples. Index.read more
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A new predictor-corrector scheme for valuing American puts
Song-Ping Zhu,Jin Zhang +1 more
TL;DR: The results of the numerical examples suggest that the proposed predictor–corrector finite difference scheme can be used as an accurate and efficient method even for pricing other types of financial derivative with American-style exercise.
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New insights on testing the efficiency of methods of pricing and hedging American options
TL;DR: A comparison of the best methods (lattice based numerical methods and an approximation of the American Premium analytical procedure) known in literature are provided along with some key methodological remarks.
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Finite Difference Method for the Black–Scholes Equation Without Boundary Conditions
TL;DR: An accurate and efficient finite difference method for solving the Black–Scholes (BS) equation without boundary conditions which does not use a far-field boundary condition to solve the BS equation numerically.
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A computational method to price with transaction costs under the nonlinear Black–Scholes model
TL;DR: An implicit time–stepping method is applied with quadratical accuracy to price a nonlinear volatility model that leads to sparse matrices of second order of convergence after a special semi–discretization.
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A general continuous time Markov chain approximation for multi-asset option pricing with systems of correlated diffusions
TL;DR: A general methodology for modeling and pricing financial derivatives which depend on systems of stochastic diffusion processes is developed with a general decorrelation procedure, which enables simple and efficient approximation of the driving processes by univariate CTMC approximations.