Black Scholes Model

(redirected from Black-Scholes Model)

Black Scholes Model

A model for mathematically pricing options. The model takes into account the strike price, the time until the expiration date, the price of the underlying asset, and the standard deviation of the underlying asset's return. The model assumes that the option can only be exercised on the expiration date, that it will provide a risk-free return, and that the volatility of the underlying asset will remain constant throughout the life of the contract. The calculation is slightly different for calls and puts. See also: Option Adjusted Spread, Option Pricing Curve.
References in periodicals archive ?
Also, the total number of conditional shares is expected maximally to amount to 90,500 shares, corresponding to a value of maximum DKK27m calculated under the Black-Scholes model.
He covers models on finite probability spaces, utility maximization under transaction costs: the case of finite omega, growth-optimal portfolio in the Black-Scholes model, general duality theory, local duality theory, portfolio optimization under transaction costs, shadow price process, and a case study of fractional Brownian motion.
Pindyck (1984) then applied option pricing to a renewable resource in property rights appraisals and, later in the same year, Shaffer (1984) reported on valuation of long-term timber cutting contracts using the Black-Scholes model.
T]) under the CAM model (solid curve) and the Black-Scholes model (dotted curve).
After the proposition of Black and Scholes options valuation model, Dan Galai (1977) conducted one of the first tests of market efficiency by identifying mispriced options using Black-Scholes model on Chicago Board of Options Exchange (CBOE).
Taking China Guodian warrants for example, we will use the new model presented in this paper and Black-scholes model to reprice the warrants and obtain the error between theoretical and empirical price to reflect the rationality of the model proposed.
This happens through the common use of volatility measures in pricing assets, such as the Capital Asset Pricing Model and the Black-Scholes Model, that depend on market sentiment and prevailing opinion to construct a perceived 'objective' measure of asset riskiness.
It was a Chicago-based secretive grain futures trading firm and an early adopter of the Black-Scholes model.
His topics include the Black-Scholes model, measures of risk and performance, Levy models, copulas and applications, and filtering.
The Black-Scholes model and the Cox, Ross and Rubinstein binomial models are the primary pricing models.
Meissner and Kawano [17] train four types of artificial neural networks (multilayer perceptron, radial basis functions network, probabilistic and generalized regression neural networks) for forecasting the implied volatility of prices for ten high-tech stocks using as inputs the same data required for the Black-Scholes model; Meissner and Kawano [17] find that the performance of multilayer perceptrons is significantly better than the Black-Scholes model.
In the standard Black-Scholes model, the risk position at time [X.