When it comes to picking an investment manager, it's hard to say what attribute is more important, luck or skill.
A manager's track record often is not long enough to make the call on skill, and even if the work history does span decades, research has shown managers for the most part have a tough time beating the indexes consistently over a long period of time. Even the best managers underperform for a period of time, something I've written about in previous columns.
Investors are flawed when it comes to choosing individual stocks or fund managers. We tend to overestimate our own decision-making abilities and defend our choices even if they turn out to be the wrong ones. We discount data that don't confirm our opinions. We stick with losing managers too long, hoping they'll turn around, or we chase performance by jumping into hot funds too late.
What's more, we tend to rely too heavily on past data to forecast the future. This point was recently the focus of a paper by Elm Partners' James White, Jeff Rosenbluth and Victor Haghani. They posed a hypothetical scenario involving about 100 investment managers, only 15 per cent of whom would beat their benchmarks by 1 percentage point annually after fees. A hypothetical investor allocated 1 per cent of his portfolio to each manager at the outset and gradually moved money to the better performing managers over time. But even after 10 years' worth of data, the investor's return would only have been 0.6 per cent.
Mr. Haghani, a former partner at the defunct hedge fund Long-Term Capital Management, has experienced the hazards of active management over the years. Investors try to time the market and chase performance, in the end costing them more in fees and lost opportunity than they would have paid had they just stuck with a portfolio allocated to reflect the market indexes.
This idea has caught on lately. Investors have been pouring money into passive funds (especially exchange-traded-funds) that track stock indexes on their seemingly unstoppable climb. Most of these indexes are simply portfolios that overweight larger stocks, based on price or market capitalization, using a set of rules. One of the big appeals of passive ETFs is they are very cheap to own, and by using these vehicles investors remove the risk of trying to identify an outperforming manager since investors in index funds will mirror the performance of the market as a whole.
There is a subcategory of passive investing called strategic (or smart) beta. These approaches look at the constituents in an index, and weight the holdings based on well-known risk premia factors – value, size, volatility and momentum. By tilting the index toward the stocks with higher characteristics based on these factors, the goal is to give the strategic beta the potential for slightly better performance and possibly less risk against their market-cap-weighted index cousin.
Then there is a third category that is particularly prevalent in the United States and an area where we have been involved in for a number of years. It uses rules-based strategies to select the top stocks based on their fundamentals and constructing portfolios that have the potential for long-term alpha performance. It is sort of like taking some of the best characteristics of passive – repeatable, consistent and transparent methods – and running investment models with the goal of selecting only the best stocks based on their fundamentals.
Strategies that are systematic have the benefit of removing human emotion from the investment decision process, which is often the biggest obstacle to performance. Computer models designed to buy and sell stocks based on changes in fundamental factors such as valuation ratios, projected sales growth and share prices don't have human bias. They aren't going to stubbornly hold investments that no longer fit the model they are tracking or foolishly chase a hot stock. They can stick to the strategy they were programmed to follow without being tempted to change things around.
It's worth repeating, of course, that investment strategies fall in and out of favour. The value investing approach favoured by such investing giants as Benjamin Graham and Warren Buffett has taken a back-seat to growth and momentum investing lately. But that is also the point of systematic investing. It makes an investor stick with a strategy through ups and downs, recognizing that ultimately things will revert to the middle. Consistency ends up being more valuable than luck or skill in the long run.
Here are some stocks tracked by our models built on the patient and value investing styles of Mr. Buffett and Mr. Graham.
NetEase Inc. (NTES-Q): A Chinese social-media and gaming company with predictable earnings and a 21.7 multiple. It scores well on more than one of our models, including the ones tracking Mr. Buffett and former Fidelity manager Peter Lynch. Its earnings per share growth rate of 32 per cent indicates it has a proven formula for growth.
Biogen (BIIB-Q): This biotech company recently struck a deal with an Irish drug maker to develop a treatment for multiple sclerosis. Its shares also fit our models tracking Mr. Buffett and Mr. Lynch, with consistently higher-than-average return on equity of 20.9 per cent against the average 12 per cent over the past decade.
Signet Jewelers (SIG-N): This diamond and jewellery retailer is in a tough sector but poised to benefit from the holiday shopping season. It scores perfectly on our model tracking Benjamin Graham, with solid EPS growth over the past few years and a moderate multiple of 9.
John Reese is chief executive officer of Validea.com and Validea Capital, the manager of an actively managed ETF. Globe Investor has a distribution agreement with Validea.ca, a premium Canadian stock screen service.
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