Utilizarea opțiunilor în evaluarea datoriilor corporative riscante
So, whereas in a DCF valuation the most likely or average or scenario specific cash flows are discounted, here the "flexible and staged nature" of the investment is modelledand hence "all" potential payoffs are considered.
See further under Real options valuation. The difference between the two valuations is the "value of flexibility" inherent in the project. The two most common tools are Decision Tree Analysis DTA  and Real options valuation ROV ;  they may often be used interchangeably: DTA values flexibility by incorporating possible events or states and consequent management decisions.
For example, a company would build a factory given that demand for its product exceeded a certain level during the pilot-phase, and outsource production otherwise. In turn, given further demand, it would similarly expand the factory, and maintain it otherwise. In a DCF model, by contrast, there is no "branching" — each scenario must be modelled separately.
In the decision treeeach management decision in response to an "event" generates a "branch" or "path" which the company could follow; the probabilities of each event are determined or specified by management. Once utilizarea opțiunilor în evaluarea datoriilor corporative riscante tree is constructed: 1 "all" possible events and their resultant paths are visible to management; 2 given this "knowledge" of the events that could follow, utilizarea opțiunilor în evaluarea datoriilor corporative riscante assuming rational decision makingmanagement chooses the branches i.
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See Decision theory Choice under uncertainty. ROV is usually used when the value of a project is contingent on the value of some other asset or underlying variable. For example, the viability of a mining project is contingent on the price of gold ; if the price is too low, management will abandon the mining rightsif sufficiently high, management will develop the ore body.
Again, a DCF valuation would capture only one of these outcomes.
Here: 1 using financial option theory as a framework, the decision to be taken is identified as corresponding to either a call option or a put option ; 2 an appropriate valuation technique is then employed — usually a variant on the Binomial options model or a bespoke simulation modelwhile Black Scholes type formulae are used less often; see Contingent claim valuation.
Real options in corporate finance were first discussed by Stewart Myers in ; viewing corporate strategy as a series of options was originally per Timothy Luehrmanin the late s. See also Option pricing approaches under Business valuation.
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Further information: Sensitivity analysisScenario planningMonte Carlo methods in financeand Valuation using discounted cash flows § Determine equity value Given the uncertainty inherent in project forecasting and valuation,   analysts will wish to assess the sensitivity of project NPV to the various inputs i.
In a typical sensitivity analysis the analyst will vary one key factor while holding all other inputs constant, ceteris paribus. For example, the analyst will determine NPV at various growth rates in annual revenue as specified usually at set increments, e.
Often, several variables may be of interest, and their various combinations produce a "value- surface ",  or even a "value- space ", where NPV is then a function of several variables.
See also Stress testing.
Using a related technique, analysts also run scenario based forecasts of NPV. Here, a scenario comprises a particular outcome for economy-wide, "global" factors câștigați în siguranță pe internet for the productexchange ratescommodity pricesetc As an example, the analyst may specify various revenue growth scenarios e.
Note that for scenario based analysis, the various combinations of inputs must be internally consistent see discussion at Financial modelingwhereas for the sensitivity approach these need not be so. An application of this methodology is to determine an " unbiased " NPV, where management determines a subjective probability for each scenario — the NPV for the project utilizarea opțiunilor în evaluarea datoriilor corporative riscante then the probability-weighted average of the various scenarios; see First Chicago Method.
See also rNPVwhere cash flows, as opposed to scenarios, are probability-weighted.
A further advancement which "overcomes the limitations of sensitivity and scenario analyses by examining the effects of all possible combinations of variables and their realizations"  is to construct stochastic  or probabilistic financial models — as opposed to the traditional static and deterministic models as above.
This method was introduced to finance by David B. Hertz inalthough it has only recently become common: today analysts are even able to run simulations in spreadsheet based DCF models, typically using a risk-analysis add-insuch as Risk or Crystal Ball.
Here, the cash flow components that are heavily impacted by uncertainty are simulated, mathematically reflecting their "random characteristics".
In contrast to the scenario approach above, the simulation produces several thousand random but possible outcomes, or trials, "covering all conceivable real world contingencies in proportion to their likelihood;"  see Monte Carlo Simulation versus "What If" Scenarios. The output is then a histogram of project NPV, and the average NPV of the potential investment — as well as its volatility and other sensitivities — is then observed.
This histogram provides information not visible from the static DCF: for example, it allows for an estimate of the probability that a project has a net present value greater than zero or any other value.
Types of real options[ edit ] Simple Examples Investment This simple example shows the relevance of the real option to delay investment and wait for further information, and is adapted from "Investment Example". Consider a firm that has the option to invest in a new factory. It can invest this year or next year. The question is: when should the firm invest? If the firm invests this year, it has an income stream earlier.
Continuing the above example: instead of assigning three discrete values to revenue growth, and to the other relevant variables, the analyst would assign an appropriate probability distribution to each variable commonly triangular or betaand, where possible, specify the observed or supposed correlation between the variables.