Abstract
This paper estimates some of the parameters of the Schwartz and Moon (2001)) model using cross-sectional data. Stochastic costs, future financing, capital expenditures and depreciation are taken into account. Some special conditions are also set: the speed of adjustment parameters are equal; the implied half-life of the sales growth process is linked to analyst forecasts; and the risk-adjustment parameter is inferred from the company’s observed stock price beta. The model is illustrated in the valuation of Google, Amazon, eBay, Facebook and Yahoo. The improved model is far superior to the Schwartz and Moon (2001) model.
Highlights
The basic model used in Doffou [1] to price Internet companies or technology companies is an improvement of the Schwartz and Moon [2] model based on real options theory and capital budgeting techniques and shows that uncertainty about some specific variables significantly affects the pricing of technology companies
Because the market price of risk and the volatility of the growth rate in sales are two critical parameters of the model that are not observable, they are inferred from the beta and the volatility of the stock of each technology company
The credit rating of each firm can be inferred from the probabilities of bankruptcy derived from the improved model
Summary
The basic model used in Doffou [1] to price Internet companies or technology companies is an improvement of the Schwartz and Moon [2] model based on real options theory and capital budgeting techniques and shows that uncertainty about some specific variables (the changes in sales and the expected rate of growth in sales) significantly affects the pricing of technology companies. 2015, 3 process with its own volatility that exhibits mean reversion with deterministic trends This stochastic behavior of the variable costs function captures the fact that many technology companies operate at a loss for many years before they are expected to generate profits in the future. The state variables sales, growth rates in sales and variable costs are stochastic while the loss carry-forward, the amount of cash available and the accumulated property, plant and equipment are deterministic and path dependent. This large number of state variables and the complexity of these path dependencies can be accounted for by using a Monte Carlo simulation to solve this model and derive the value of the technology company.
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