S&P-Beating; UAM Analytic Lets the Computer Do the Thinking

Harindra de Silva, who invests $59 million of other people’s money, buys about 120 stocks a year. He doesn’t talk to chief executives, visit companies or listen to analysts.

Instead, the 39-year-old co-manager of the UAM Analytic Enhanced Equity fund in Los Angeles relies on a computer program to forecast stocks’ short-term returns based on 70 variables, including the ratio of companies’ cash flow to share price, price-to-earnings ratios and exposure to foreign currency fluctuations.

He is a “quant”--a money manager who uses so-called quantitative analysis that relies exclusively on hard data to pick stocks rather than subjective human judgment.

“I’m buying characteristics, not companies,” said De Silva, a native of Sri Lanka who joined the fund in October 1996.

De Silva is one of the growing number of portfolio managers who rely on computer models in their quest to beat the Standard & Poor’s 500 index--a benchmark that in recent years has bettered about three out of four money managers.

His strategy appears to be working. The fund, rated five stars by fund-tracker Morningstar Inc., has had an average annual return of about 32% over the last three years. It’s up 9% this year, compared with a 5.1% total return for the S&P; 500 through Friday.

As more investors have bought in, the fund’s assets have swelled more than eightfold from $7 million in 1997.

“There’s definitely a trend toward using quantitative technology in fund management,” De Silva said. What’s more, “the trend in quantitative funds is to focus on multiple characteristics instead of just one or two,” he said.

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Overall, however, the success of such quantitative funds is mixed. Fidelity’s quantitative offering, the Technoquant Growth fund, for instance, lagged the S&P; by 10 percentage points last year, although it’s up 7.3% so far this year.

Although many money managers use computer models to help pick stocks, few are as reliant on a machine as De Silva is.

De Silva argues that stock-picking techniques that involve subjective measures such as meeting with management are irrelevant because they’re “already reflected in the statistics.”

The key is to determine which factors are most relevant to gauging market sentiment about a stock at a given point in time, he said. He rebalances his variables during the first week of every month and has broken with this schedule only once--when the Russian stock market crashed, setting off a global market rout, in mid-August 1998.

Only four or five variables have a significant impact on the market in a given month, De Silva said, and they can change weekly. He programs his computer to favor those variables when picking stocks.

Right now, his biggest holdings include General Electric, Microsoft, Citigroup and Wal-Mart Stores.

But the computer isn’t always right, of course. For example, De Silva says his computer told him that Coca-Cola, which the portfolio holds now, was a good buy last month because it sells most of its soft drinks overseas and a weakening dollar will make them less expensive, all other things being equal.

“The benefit of this model is that we can look at many aspects of a company,” he said. “Coke has a lot of things that will help it if the dollar weakens, but many things that will hurt it in terms of the business model.”

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So far, Coke’s shares remain in a sharp downtrend.

A ratio of a company’s cash flow to its stock price was another indicator that De Silva’s computer emphasized last month.

Cash flow measures company performance by excluding noncash charges and other expenses from the earnings the business is generating. It’s arguably a better tool than measures such as the price-to-earnings ratio because companies can manipulate their earnings figures.

Cash flow, on the other hand, “is hard to manage,” De Silva said. Over the last six months in particular, “cash flow and stock price returns have been highly correlated,” he said.

His computer has singled out Southland power utility Edison International as likely to perform well in the near future based on cash flow.

De Silva developed his theories while working on his doctorate in finance at UC Irvine. Based on his computer program, which he tweaks to accommodate new variables, he buys and sells stocks once a month.

The UAM Analytic fund is unique among quantitative portfolios because its turnover is extremely high--about 300% annually--and because the stocks it owns tend to be drawn from the S&P; 500.

“It’s doing what a lot of quantitative funds do,” said Russ Kinnel, a senior fund analyst at Morningstar. “But it’s special because of that turnover.”

The high turnover rate means the fund can generate heavy capital gains that must be distributed to shareholders. So Kinnel says it’s best owned in a tax-sheltered account.

“It’s a decent fund, but you wouldn’t want to be taxable, given that environment,” Kinnel said.

The fund has a minimum investment of $2,500. Annual management fees total about 1% of assets.

For more information, the fund can be contacted at (877) 826-5465, or at https://www.uam.com.