Gregory Forsythe is a professional stock-picker with a rigorous system. He’s got numbers that reflect business operations of companies, numbers that indicate stock market trends and investor sentiment.
But what he doesn’t have is the phone numbers of the companies he tracks.
Investors have recoiled from revelations about stock analysts who shill for companies instead of protecting investors.
The Wall Street Journal reported this month that Jack Grubman, the celebrity telecommunications analyst at Salomon Smith Barney, participated in management decisions at failed telecom giant Global Crossing, a big step over the line of fiduciary responsibility.
Earlier, Merrill Lynch agreed to pay $100 million to settle charges that included double-speak by analysts who recommended stocks to the public based solely on investment banking fees, not investment judgment.
With the clay feet of stock analysts at investment banks exposed, interest in the detached style of stock-picking known as quantitative analysis has re-emerged.
Pure quant managers pick stocks based on publicly available numbers and computer-driven analysis of the numbers.”Getting information from [corporate] management is slow and inefficient,” says Forsythe, Chicago-based senior vice president and director of equity research at Schwab Equity Analytics, the unit of Charles Schwab that recently unveiled a system for ranking stocks by letter grades, A through F.
“We can update data for 24 important variables for 3,500 companies simultaneously every weekend. You can’t do that manually.”
Time and money spent assessing the credibility and skill of corporate management through personal contacts may be time and money wasted, even if the fund manager or analyst is appropriately skeptical and detached, he said.
“If management is good, if they have integrity and all those things, it will show up in the numbers,” Forsythe said. “I don’t consider myself a psychoanalyst. People can be sincerely wrong.”
Pat Dorsey, director of stock analysis at Chicago-based investment researcher Morningstar, said there is no evidence that quantitative analysis is more rewarding than hands-on fundamental analysis or that so-called “quant shops” necessarily offer a cheaper approach to stock-picking.
For example, the Bogle Small Cap Growth Fund, a strong-performing mutual fund based on quantitative stock-picking carries a 1.35 percent expense ratio, about the same as the 1.34 percent expense ratio at the strong-performing William Blair Small Cap Growth Fund. The Blair firm has built its brand name based on bottom-up, intimate coverage of small and medium-size companies.
But even Chicago-based William Blair & Co. is promoting a quantitative stock selection screen, called the “Blair quality model,” which crunches eight factors and ranks 1,000 stocks from 1 to 10.
“We’re still the furthest thing from a quant shop that you can find,” said Michelle Seitz, head of investment management at Blair.
Nonetheless, “we have a client base that reads the newspapers, watches television and is suspicious.”
In that vein, quantitative analysis today represents the investment firm version of trust but verify. Unfortunately, pristine objectivity doesn’t guarantee you’ll be any richer.
But with bullish momentum purged from the overall stock market, investor appetite has increased for logical, objective rationales in picking stocks.
“We don’t see our quality model as a stock selection adviser all the time, but we know it tends to work in a tougher environment,” said George Greig, investment strategist at William Blair.
Indeed, the heyday of quantitative stock-picking began in 1974, amid a severe stock market downturn, recalled Ted Aronson of Philadelphia-based Aronson and Partners, a quantitative stock-picking firm. Large-capitalization stocks lost 34 percent that year, according to Ibbotson Associates.
“Twenty-eight years ago, being a quant really meant something,” Aronson said. “There was a chance that sheer computer power could produce excess returns.”
Now, every investor–amateur and professional–can own a personal computer with greater number-crunching power than the quant elites of the 1970s could dream of.
New federal regulations barring selective disclosure of material information by companies make it harder for stock-pickers, quants and non-quants, to gain an edge obtaining critical numbers before competitors.
As the ill-fated quant firm Long Term Capital Management demonstrated in 1999, the most complex and sophisticated number crunching system will be imitated if it works, thereby destroying its effectiveness.
As a result, numerical factors and systems that predict investment results evolve. The most venerable quant factors, which are earnings forecast revisions by stock analysts and earnings surprises posted by companies, still work, but their value declined as the data became more widely distributed and more manipulated by corporate managers, Aronson said.
John Bogle of the Bogle Small Cap Value Fund said the current vogue is to compare cash returns from operations with net income presented through generally accepted accounting principles, under the general theme of “quality of earnings.”
Blair’s “quality model” screens stocks according to eight factors based on five-year performance data, including cash flow. The goal is to select companies with consistent earnings growth and cash-generating ability, Greig said.
Forsythe, whose LaSalle Street firm, Chicago Investment Analytics, was acquired by Schwab in November 2000, employs a 24-factor computer model that includes relative stock price changes and other indicators of market sentiment as well as statistics from company financial statements.
The best-performing Chicago quant shop of late is little-known Callard Asset Management, which starts with only two factors in its basic formula–inflation and tax rates–in ranking 4,000 stocks.
According to Investars.com, which tracks the performance of equity research firms, Callard’s stock ranking, from strong “buy” to strong “sell,” would have produced the best one-year return of researchers tracking at least 500 stocks–9.8 percent through Thursday, compared with a loss of 4.5 percent for stocks ranked by Merrill Lynch.
Chuck Callard says the long-term investment returns on corporations as a whole are most influenced by the trends in inflation and taxes.
“Then we take the industry sectors–the name of the game is one group competing against another” for capital and the favor of investors, Callard said.
As firms compete for capital, optimism prompts investors to demand less returns (pay more) for some industry groups and companies than others. It’s a sort of zero-sum game, with potential winners and losers constantly changing, based on inflation-adjusted cash returns on investment.
“Few firms stay at the top for more than three or four years; Wal-Mart is an exception,” Callard said. “Competition drives a company back to the average.”
Quantitative stock-picking systems offered by Schwab, Blair, Callard and others are aimed at long-term investors.
In its effort to compete with the giant Wall Street investment banks, Schwab is grabbing talent wherever it finds it. Chicago-based Bridgeportfolio.com makes Callard portfolios available to Schwab customers; Blair is in Schwab’s stable of multimanager “MarketMasters” funds.
“Even the dyed-in-the-wool, seat-of-the-pants stock-pickers are using quantitative techniques,” Bogle said.
The enormous amount of information available via the Internet, including key financial ratios and even word searches that extract warning signs from the footnotes in financial statements, has popularized systematic research, even if investment decisions are visceral.
“We may have different factors, but the idea is the same–to make judgments about how you use the data,” said Ricardo Bekin, chief investment officer at Callard.
But Aronson, a nearly 30-year veteran of quantitative analysis, said that in the end what really counts is not high-tech stock research and selection but high-tech trading execution to keep investment costs as low as possible.
