Making Monte Carlo Work

The National Association of Securities Dealers (NASD) has lifted the ban on Monte Carlo simulation tools. Although the investment analysis tools have been used by registered investment advisers (RIAs) for more than a decade, brokers were barred from using them until only weeks ago, when an official change to NASD Rule 2210 (d)(1)(d), which prohibited member firms from making "predictions or projections regarding investments or investment strategies," took effect on Feb. 14. The recent change allows member firms to use Monte Carlo simulation to show the likelihood of various investment outcomes as long as they comply with NASD's disclosure and suitability requirements.

Commonwealth Financial Network, a Waltham, Mass.-based independent broker-dealer, is just one of the many member firms that plan to take advantage of the new amendment. According to John Blood, vice president and director of investments at Commonwealth Financial, the firm is presently preparing to roll out a Monte Carlo simulation tool to its advisers. "We have a proprietary portfolio analysis tool that we've built that doesn't currently have Monte Carlo simulation built into it, but it's something that we're looking to add by the second quarter of this year," he says.

Industry experts are uncertain about the impact of the rule change. Blood believes that Monte Carlo will significantly enhance the interaction between brokers and clients, allowing brokers to "open up the discussion with the client about the range of possible outcomes that they're going to be looking at."

But Pamela Brewster, a senior analyst at Boston, Mass.-based Celent Communications, believes the adoption of the tool among broker-dealers will be moderate at best. "There's still a long way to go to move the broker's mind-set from being transaction-oriented to planning-oriented," she says. "In particular, Monte Carlo is a somewhat sophisticated tool and it will be interesting to see if brokers have the patience to really go through this exercise with clients."

Monte Carlo 101

The methods behind Monte Carlo date back to the late 1940s, when scientists at the Los Alamos National Laboratory programmed their early computers to create random combinations of known variables to simulate the range of possible nuclear explosions. Monte Carlo simulation selects variable values at random to model real-life situations, so the scientists nicknamed the program Monte Carlo, after the city's famous roulette wheels, which operate in a similarly random fashion. By the late '90s Monte Carlo simulation became widely popular among RIAs, who used the technique to develop financial plans. Monte Carlo simulation is used to show investors the hundreds of possible future outcomes for a portfolio based on past market actions or hypothetical events. "Monte Carlo is a relatively old technique," explains Mike Henkel, president of Ibbotson Associates, a Chicago-based research firm that offers the software. "In general, it allows users to look at how the risks and rewards of an investment might play out for a particular investor's goals and objectives."

The premise behind Monte Carlo simulation is purely mathematical, and with the proper inputs and equations, it can even be done on an Excel spreadsheet. The main advantages of Monte Carlo software applications are the speed at which they arrive at calculations and their ability to summarize the data. "Obviously, looking at two thousand futures is a bit mind-boggling," says Henkel. "Most Monte Carlo pieces today can summarize those futures. For example, with an investment of X dollars, 90 percent of the time at the end of a 20-year horizon you'll have $75 or higher, or there's a 10 percent chance you'll have $3 million at the end of a 20-year horizon after sending your kids to college, buying a house in the country, etc. The range of those upsides and downsides give investors real, concrete numbers as to risk."

Rules of Adoption

For Commonwealth Financial Network, the selling point of Monte Carlo simulation is its ability to show investors the impact of investment decisions in terms that they can understand. "The way I picture Monte Carlo simulation being most valuable isn't focusing on what the expected return is going to be or what the best possible outcome is going to be; it's setting up a plan - showing a client how their investments are allocated and what they might expect going forward based on what the markets have done historically," explains Commonwealth's Blood. "I think focusing on the downside helps in managing clients' expectations."

Commonwealth is (as of press time) considering three Monte Carlo simulation providers, though Blood declines to name them. He adds that since there are hardly any distinguishing characteristics between the Monte Carlo software applications currently on the market, the effectiveness of a tool relies heavily on a firm's individual needs. "Because this [Monte Carlo tool] is going to be integrated with a tool that we have built in-house, we need somebody who's going to be flexible in terms of integrating it into our system. So from our standpoint, it's really compatibility of the software and being able to plug right into this existing system that we have," he says.

Ensuring Compliance

Integration may ensure effectiveness, but it doesn't ensure compliance. Because the quality of the tool's outputs are dependent on the quality of the assumptions, "Blindly taking the tool and using it is a recipe for potential compliance disaster," warns Ibbotson's Henkel. After all, he adds, "The NASD isn't judging the tool on whether it's a good one or a bad one; they're just judging if it's compliant with the NASD's regulations for disclosure and suitability."

In order to avoid a future lawsuit by a dissatisfied investor, it may ultimately be up to the brokers themselves to understand the assumptions, review the outputs and ask critical questions (see sidebar below). Additionally, to ensure firmwide compliance, Celent's Brewster suggests that broker-dealer firms form clear guidelines for the use of Monte Carlo simulations, as well as certain parameters for the inputs used based on client suitability. She also suggests that Monte Carlo simulations should not be used in isolation, but rather grouped with other risk-return calculation techniques such as randomized historical returns.

"The education piece of the Monte Carlo simulation tool is probably the most important, because it's really a case of garbage in, garbage out," adds Commonwealth Financial's Blood. "We're going to make sure as we roll this out that we do go through the education and really give folks an understanding of the importance of the inputs to the model."

Key Questions for Monte Carlo Users

1. Do I agree with the assumptions of this tool?

2. Are these assumptions consistent with my firm's forecast?

3. Can I defend or justify that assumptions used within the tool were prudent and relevant to the investor?

4. Does the output cover the appropriate upside and risks inherent in any investment?

5. Do the projections mislead the investor in any way?