Answers and example for geometric Brownian motion (GBM):
The real simulation of a GBM uses the real drift a. The price at future time t is given by:
The risk-neutral simulation of a GBM uses the risk-neutral drift a’ = r - d . The price at t is:
The chart below illustrates the difference of risk-neutral and real simulation by showing two sample paths for each type of simulation:
Note in the chart that the paths are parallel, and the risk neutral one is a risk premium lower than real sample path. This issue is because the risk neutral drift is equivalent to subtract a risk premium from the drift (see Trigeorgis' textbook, 1996, p.102):
Where l is the underlying asset market premium of risk in the sense that r = a + d = r + ls, (r = risk-adjusted discount rate for the underlying asset).
Suppose a real options problem can approximately be represented by an European type call option (for additional discussion of this example, see the Monte Carlo page, section on European real options).
The first step is to simulate risk-neutral sample paths for the underlying
asset (project value or commodity price) and take the cross-section distribution
at the expiration T. You get the risk neutral distribution for the
underlying asset.
The figure below illustrates:
With the risk-neutral distribution of the project value V at the
expiration (T), you can apply the options thinking: rational managers will
exercise the option only if get positive expected values:
F (T)= max. (NPV, 0). This asymetric risk-neutral
distribution for the European-type real options at T displaces the expected
value to the higher value and represents the active management of real options.
The current value of the real options in this case is just to take the
present value using the risk-free discount rate. The figure below shows this
process.
For the underlying asset, you get the same value:
For the option/derivative, the same is not true:
Risk-neutral valuation is based on the absence of arbitrage, portfolio replication (complete market).