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Nonlinear Pricing Schedule - Nonlinear pricing is a pricing schedule in which quantity and total price are not mapped to each other in a strictly linear fashion [2] Affine Pricing - An affine pricing schedule consists of both a fixed cost and a cost per unit. Using the same notation as above, T(q) = k + pq, where k is a constant cost. [3]
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 ...
Cost-plus pricing is a pricing strategy by which the selling price of a product is determined by adding a specific fixed percentage (a "markup") to the product's unit cost. Essentially, the markup percentage is a method of generating a particular desired rate of return. [1] [2] An alternative pricing method is value-based pricing. [3]
The Black model (sometimes known as the Black-76 model) is a variant of the Black–Scholes option pricing model. Its primary applications are for pricing options on future contracts, bond options, interest rate cap and floors, and swaptions. It was first presented in a paper written by Fischer Black in 1976.
For the models used to simulate the interest-rate see further under Short-rate model; "to create realistic interest rate simulations" Multi-factor short-rate models are sometimes employed. [6] To apply simulation here, the analyst must first "calibrate" the model parameters, such that bond prices produced by the model best fit observed market ...
See Asset pricing for a listing of the various models here. As regards (2), the implementation, the most common approaches are: Closed form, analytic models: the most basic of these are the Black–Scholes formula and the Black model. Lattice models (Trees): Binomial options pricing model; Trinomial tree; Monte Carlo methods for option pricing
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Formal estimation model: The quantification step is based on mechanical processes, e.g., the use of a formula derived from historical data. Combination-based estimation: The quantification step is based on a judgmental and mechanical combination of estimates from different sources. Below are examples of estimation approaches within each category.