Simulation discounted cash flow valuation for internet companies

Abstract

Discounted cash flow (DCF) is the most accepted approach for company valuation. It is well grounded in theory and practice. However, the DCF approach, which is commonly used for traditional companies valuation, presents a number of serious weaknesses within the Internet companies’ context. One of these weaknesses is tackling the uncertainty that characterize future cash flows of these companies. Specifically DCF assumes that future cash flow streams are highly predictable. The effects of uncertainty are therefore tackled implicitly by discounting the expected value of the cash flows at a risk-adjusted interest rate. However, under uncertainty, future cash flows of these companies can no longer be characterized by a single value but rather by a range of values of its possible consequences. This paper looks at the way in which uncertainty can be incorporated into the traditional DCF approach so that the latter, which is otherwise conceptually sound, becomes relevant. This is done by recognizing that the DCF input variables are uncertain and will have a probability distribution pertaining to each of them. Thus by utilizing a probability-based valuation model (using Monte Carlo Simulation) it is possible to incorporate uncertainty into the analysis and address the shortcomings of the current model. The MC simulation assigns a range of values in order to cope with uncertainty underlies each key cash flow variable. The process leads to a probability distribution of the valuation criterion used, giving investors a quantitative measure of risk involved.