Optimal Number of Trials for Monte Carlo Simulation

Download the full Special Report: Optimal Number of Monte Carlo Simulation Trials

Traditional valuation approaches such as Option Pricing Method or Probability-Weighted Expected Return Method may not be adequate in providing fair value estimation for hard-to-value financial instruments that require distribution assumptions on multiple input parameters. In such cases, a numerical method such as a Monte Carlo simulation is often used. The Monte Carlo simulation is a computerized algorithmic procedure that outputs a wide range of values – typically unknown probability distribution – by simulating one or multiple input parameters via known probability distributions.

Corporate finance and accounting professionals, attorneys and auditors may find distinct advantages in understanding the functionality of Monte Carlo simulations. This approach is often used by valuation professionals when developing an analysis for startup firms, companies holding complex securities or other hard-to-value assets.

VRC’s special report provides an in-depth discussion about this algorithmic procedure that outputs a wide range of values. For a deeper discussion, contact a member of VRC’s Complex Instruments Group.