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Foundational algorithms like Black-Scholes and binomial pricing models and Monte Carlo simulations were just starting to take hold.
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In principle, the "binomial pricing model" allows for adjustments for some of these additional complications.
On the basis of the simulation results, a binomial options pricing model is used to design four interdependent binominal trees and to evaluate a Bermuda-type compound expansion option.
In part of the doctrine (Triantis and Borison, 2001), the binomial option pricing model is considered to be more flexible in allowing the optimal timing of the decision to exercise.
Therefore, a binomial options pricing model may more accurately characterize this investment decision.
The Binomial Option Pricing Model [ 34] may be utilized by firms to assess whether or not to engage in research projects, based on a value maximization approach.
We describe a latency-tolerant parallel algorithm for the multiplicative binomial tree option pricing model.
Relationships between price, use and potential confounding factors were examined using logistic and repeated measures binomial regression models, and approximate magnitudes of associations were assessed with linear regression.
Figure 1 illustrates how the Poisson regression, negative binomial models and Pareto distribution fit the observed data and it is clear that in the two age groups, the negative binomial model fitted the observed data best.
The negative binomial regression model and multinomial logit model were used to analyze trip generation and travel mode, respectively.
Both the American and international boards will allow companies to choose the options pricing model they used, either the traditional Black-Scholes model or the newer binomial model.
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