Litigators, Money

Finance And Law: The Pros And Cons Of Monte Carlo Simulations In Valuation

For attorneys, understanding Monte Carlo simulations and their pros and cons can be an important advantage in business cases.

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A roulette wheel (by Ralf Roletschek via Wikimedia)

A roulette wheel (by Ralf Roletschek via Wikimedia)

Monte Carlo simulation is one of the most important tools in finance, economics, and a wide array of other fields today. The technique was first used by scientists working on the atom bomb; it was named for Monte Carlo, the Monaco resort town renowned for its casinos. Monte Carlo simulations are essentially a method of creating prices for assets based on an average of hundreds or even thousands of hypothetical scenarios. The technique is particularly valuable and relevant when dealing with hard-to-price assets or assets where there are a range of very distinct possible outcomes.

For attorneys, understanding Monte Carlo simulations and their pros and cons can be an important advantage in business cases. In particular, valuation matters related to patents, start-up firms, and esoteric investment securities all are sure to benefit from a carefully implemented Monte Carlo analysis.

The Pros of Monte Carlo Analysis

A Monte Carlo simulation is literally a computerized mathematical technique that creates hypothetical outcomes for use in quantitative analysis and decision-making. The technique is used by professionals in disparate fields such as finance, project management, energy, manufacturing, engineering, research and development, insurance, oil and gas, transportation, and the environment.

Using a Monte Carlo simulation furnishes the decision-maker with a range of possible outcomes and the probabilities they will occur for any choice of action. It shows the extreme possibilities along with all possible consequences for middle-of-the-road decisions. In that way it is extremely useful for attorneys in court who want to argue about the relative risk or likelihood of an outcome.

Monte Carlo analysis has several advantages over other methods of evaluating risk or valuation of assets.

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  • Probabilistic results – Monte Carlo simulations show not only what could happen, but how likely each outcome is. This can be very beneficial for attorneys when arguing about hypothetical situations including the damage caused in a business dispute such as a patent infringement.
  • Graphical results – Monte Carlo simulations make it easy to create graphical aids that show the range of possible outcomes in a scenario. These can be very beneficial in many courtroom settings.
  • Sensitivity and Scenario analysis – Monte Carlo simulations make it easy to examine what would have happened under circumstances that vary slightly from reality. What would have happened to company XYZ if they had not been harmed by a competitor’s actions? Monte Carlo simulations offer an answer to that question.

The Cons of Monte Carlo Analysis

For all of the benefits of Monte Carlo analysis, a shrewd attorney can also call the court’s attention to the assumptions underlying the simulation when needed. Monte Carlo analysis is ultimately a statistical exercise and that means that it requires making assumptions. Those assumptions may be reasonable or unreasonable – it depends on the circumstances.

  • Distribution assumptions – Monte Carlo simulations are built around a specific type of statistical distribution. Use the right distribution and your results are valid, use the wrong one and the results are meaningless. In a recent case I was involved in as an expert witness, the distributional assumptions underlying a Monte Carlo simulation offered a key opportunity to dispute the argument of the opposition counsel.
  • Input assumptions – Monte Carlo simulations are only as good as the inputs they start with. A simulation might be used to evaluate the value of a start-up company for instance, but that requires making generalizations around the success of the firm at various points in the future. Selection of the inputs related to the probability of that success is a key issue that determines the usefulness of the simulation.
  • Formula assumptions – Monte Carlo simulations are built around mathematical formulas that drive the end values. Sometimes those formulas are straightforward and undeniable, but in many cases they are not. Many pre-packaged Monte Carlo simulation software programs have formulas built in to aid the user in getting quick results. These software packages are critically limited because those formulas are often used incorrectly – the software becomes a form of black box that people lean on too heavily while failing to truly understand the underlying process that generates the results. Again, this creates an opportunity for a lawyer faced with an opposing counsel that is relying on such simulations

At the end of the day, there is little doubt that Monte Carlo simulations are a great tool. In many cases they are the only way to realistically value some assets or assess risks in some situations. Still, it is incumbent on attorneys to understand how to either validate or undermine these tools in court.

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(Anyone interested in discussing this week’s column may email me at M.McDonald@MorningInvestmentsCT.com or MMcDonald8@Fairfield.edu.)

Michael McDonald is an assistant professor of finance at Fairfield University in Connecticut. He holds a PhD in finance. Michael consults extensively with organizations ranging from Fortune 500 companies to start-up businesses on financial matters through Morning Investments Consulting. Michael has served as an expert witness in legal disputes, and is an arbitrator with the Financial Industry National Regulatory Authority (FINRA). Michael can be reached at M.McDonald@MorningInvestmentsCT.com.

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