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  2. Finite difference methods for option pricing - Wikipedia

    en.wikipedia.org/wiki/Finite_difference_methods...

    Finite difference methods were first applied to option pricing by Eduardo Schwartz in 1977. [2] [3]: 180 In general, finite difference methods are used to price options by approximating the (continuous-time) differential equation that describes how an option price evolves over time by a set of (discrete-time) difference equations. The discrete ...

  3. Finite difference method - Wikipedia

    en.wikipedia.org/wiki/Finite_difference_method

    To use a finite difference method to approximate the solution to a problem, one must first discretize the problem's domain. This is usually done by dividing the domain into a uniform grid (see image). This means that finite-difference methods produce sets of discrete numerical approximations to the derivative, often in a "time-stepping" manner.

  4. Monte Carlo methods for option pricing - Wikipedia

    en.wikipedia.org/wiki/Monte_Carlo_methods_for...

    The first application to option pricing was by Phelim Boyle in 1977 (for European options). In 1996, M. Broadie and P. Glasserman showed how to price Asian options by Monte Carlo. An important development was the introduction in 1996 by Carriere of Monte Carlo methods for options with early exercise features.

  5. Trinomial tree - Wikipedia

    en.wikipedia.org/wiki/Trinomial_Tree

    The trinomial tree is a lattice-based computational model used in financial mathematics to price options. It was developed by Phelim Boyle in 1986. It is an extension of the binomial options pricing model, and is conceptually similar. It can also be shown that the approach is equivalent to the explicit finite difference method for option ...

  6. Monte Carlo methods in finance - Wikipedia

    en.wikipedia.org/wiki/Monte_Carlo_methods_in_finance

    For more than three or four state variables, formulae such as Black–Scholes (i.e. analytic solutions) do not exist, while other numerical methods such as the Binomial options pricing model and finite difference methods face several difficulties and are not practical. In these cases, Monte Carlo methods converge to the solution more quickly ...

  7. Binomial options pricing model - Wikipedia

    en.wikipedia.org/wiki/Binomial_options_pricing_model

    In finance, the binomial options pricing model (BOPM) provides a generalizable numerical method for the valuation of options. Essentially, the model uses a "discrete-time" ( lattice based ) model of the varying price over time of the underlying financial instrument, addressing cases where the closed-form Black–Scholes formula is wanting.

  8. Lattice model (finance) - Wikipedia

    en.wikipedia.org/wiki/Lattice_model_(finance)

    The method is also used for valuing certain exotic options, because of path dependence in the payoff. Traditional Monte Carlo methods for option pricing fail to account for optimal decisions to terminate the derivative by early exercise, [3] but some methods now exist for solving this problem.

  9. Barrier option - Wikipedia

    en.wikipedia.org/wiki/Barrier_option

    A faster approach is to use Finite difference methods for option pricing to diffuse the PDE backwards from the boundary condition (which is the terminal payoff at expiry, plus the condition that the value along the barrier is always 0 at any time). Both explicit finite-differencing methods and the Crank–Nicolson scheme have their advantages.