Quantitative Model Exploits Market Inefficiencies for Above-Benchmark Returns

Acadian Asset Management (part of OM Asset Management) identifies inefficiencies in the pricing of securities to guide its investment decisions. “Investors make certain systemic behavioral errors in the way they make investment decisions,” Acadian CIO John Chisholm explains, “[w]e measure . . . the payoff associated with that error.” For example, a stretch of strong earnings tends to drive up stock price even when continued growth is unlikely. This is one reason that cheap companies (in terms of price-to-earnings) tend to generate higher returns over time than more expensive companies. Acadian uses this and other “factors” of a stock to predict the return associate with a stock in the near future.

The process involves an aggregation of common metrics (like price-to-book ratio) into a “price to intrinsic value” factor.  The raw value is compared to peers to produce a standard-deviation-based score, which is then evaluated over time to provide both historical and forward-looking data. For each firm, Acadian feeds in the various factor scores to produce “the forward-looking piece: How do we expect these different characteristics to do in the future?” From there, the data goes into an optimizer that trades off attractiveness versus transition costs and risk.  Chisholm explains, “That’s ultimate how we determine what to buy and sell in portfolios we manage.”

It appears the approach has worked. The firm’s largest fund, the Emerging Markets Equity strategy, returned 2% over its benchmark annually from 1994 through June 30, 2015.  It’s $1 billion Global All-Country Equity strategy has returned 1% over benchmark from 2003 to June 30, 2015.