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Black-Scholes Model

ESPP Valuation Tools

Binomial Model

Volatility Tool

Forfeiture & Expected Life Tool

Management Tool

Services Package

Private Company Package

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We provide two models to meet the specific needs of our customers. Each model has certain features and advantages that make it more suitable for some companies.

The Black-Scholes model (more precisely modified Black-Scholes-Merton for company-issued stock options) is the original stock valuation model that many companies have used in the past. This model is a good baseline for companies that have not yet gone public or companies with very stable stock prices. It is simple and is based on a well-established formula. (Note, for ESPP plans, we also provide a customized Black-Scholes model to value ESPP grants) But this simplicity tends to generate a high valuation for companies with more volatile stock prices. In these cases, the Binomial Lattice model is more appropriate.

The Binomial Lattice model takes a more complex approach and considers stock movement over time with both up and down stock volatility outcomes and calculated valuations. All of the outcomes that result in a potential option exercise are individually present-valued and averaged to produce a more precise valuation.

Both the Binomial Lattice and the Black-Scholes models take a set of assumptions (each model uses a slightly different mix of assumptions) that the user must determine is reasonable for their individual stock and these inputs affect the valuation outcome. But there the similarity ends.

The Binomial Lattice method is more computationally intensive and generates a large data set of possible outcomes (Dynamic) based on the inputs. Whereas the Black-Scholes model simply produces a single valuation (Static) number from a straight-forward formula.

According to ASC 718 (formerly FAS123r), you may use a number of potential models for new option grants but any change in model must be "more effective" than the alternative model. Moreover, you must use the new model on all grants created after the change. Therefore, care should be taken to select the correct model.

Please see the below table for example scenerios that tend to favor one model over the other.

Key Feature
Target Companies Pre-public and public companies and companies with stable trading ranges. Larger companies and companies with more volatile stock prices.
Model Characteristics Static Inputs and a simple result with a single output. Inputs are used to generate a set of outcomes that are averaged to create a valuation.
Volatility and Dividend Yield can Vary over the Life of the Grant No, these assumptions are fixed. Yes, the Volatility and Dividend yield assumptions may be varied to accomodate expectations.
Complexity Simple, easy-to-implement formula. Complex, data-intensive with many nodes.
Stock Behavior Volatility The stock is assumed to increase by the specified volatility. The stock is modeled assuming but increasing and decreasing stock price.
Expected Life Application The BSM model uses the expected life to value the options. Longer expected life inputs typically result in higher valuations. The expected life is an output based on the modeled behavior of the grant. Computing historical expected life may help support the BL conclusion.

If you have any further questions, contact our sales support team at and we will do our best to find the right product for your needs.



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