Michaud Takes On Portfolio Optimization's Sacred Cows

May 11, 2009

Investment shop wrestles with ways to update the work of Nobel Prize winner Harry Markowitz.

 

Dick Michaud earned his doctorial degree in mathematics and statistics by writing a thesis on optimization techniques for computer-aided design applications.

Once he entered the workforce, however, the young scientist decided to apply his research in optimization strategies to a different field. Specifically, Michaud decided to delve into complaints that standard techniques didn't provide good results in the world of high finance.

His research led to the 1999 launch of New Frontier Advisors. The investment shop, which was founded by Michaud and two partners, had about $1 billion in assets under management entering 2009. Its managers run portfolios using a novel optimization strategy Michaud and his son, Robert Michaud, developed called "Resampled Efficiency." 

What Optimizers Try To Do

The origins of this strategy are detailed in his book, "Efficient Investment Management," first published by Harvard Business Press in 1989. 

Michaud says that his research represents an update of the pioneering efforts by Harry Markowitz, the Noble Prize-winning economist, commonly known as the "Father of Modern Portfolio Theory." 

As described by the Nobel committee, Markowitz's great breakthrough was figuring out "how wealth can be optimally invested in assets which differ in regard to their expected return and risk, and thereby also how risks can be reduced."

In other words, Markowitz focused on the link between the risk of an asset, its potential return and the correlation it had with other assets. He created early portfolio optimization algorithms that used estimates of the risk and return of different asset classes to build theoretically "optimal" portfolios.

For his part, Michaud considers his work as an enhancement of Markowitz's research. "Theoretically, [Markowitz's optimization techniques] work very well. But keep in mind, his main optimization theories were formed 50 years ago," added Michaud.

The next-generation optimization analyst found that with the reams of economic- and market-related data available these days, computers tend to accept too many numbers that don't relate well to one another. 

"Computers take everything so literally," said Michaud. "For example, when you type in an index return of 10.1%, it reads that number as being quite different than 10%. Of course, you and I realize that in a practical sense, there's hardly any difference at all."

To overcome that problem, he borrowed a mathematical technique used by optimizers in other fields called resampling, which is based on a specific type of Monte Carlo simulation. At its core, this resampling technique allows optimizers to consider and incorporate the possibility that the statistical inputs entered into an optimization model are wrong.

Simply put, resampling allows managers to assign a greater range of probabilities to various outcomes. The goal is to produce a more realistic portfolio based on a more realistic efficient frontier.  

"We're basically using investment data in a more natural way for computers to handle," said Michaud.

What That Means For A Portfolio Today

New Frontier uses exchange-traded funds in its portfolios. They're built for different parts of the efficient frontier and referred to as strategic portfolios. "We don't try to forecast. Using various statistical techniques and the latest information, we try to determine the best relationships between different asset classes to get more effective risk-return profiles," said Michaud.

That means not taking big bets in sector- or country-specific stock ETFs. The process doesn't deviate much from fixed-income benchmarks in terms of maturities and sectors, either.

"We're basically using the power of optimization technologies and rebalancing techniques to add to long-term returns for portfolios," said Michaud.

Within that context, the firm's Treasury portfolios are currently tending toward overweighted positions in midrange maturities rather than short or long term. In corporate fixed-income funds, its portfolios are slanted to shorter-term maturities.

 

 

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