The number of complex investment strategies available to investors has never been greater. But most investors are probably still best served by a few simple, market-cap-weighted index funds.
One of the pre-eminent reasons for the popularity of index-tracking funds revolves around the notion of market efficiency--the idea that the market quickly and accurately incorporates all available information about a public company into its stock price. This all-knowing market mechanism makes it difficult to identify stocks that are mispriced, so the logical conclusion is that you should simply own the index and take advantage of the market's long-term aggregate growth. This is a mostly valid argument (there are times when the all-knowing market can be a bit of a know-nothing), and one that I would largely agree with. But the rationale for using a market-cap-weighted index fund goes beyond market efficiency.
The fact that so many varied asset classes and strategies have been democratised might be viewed as a boon for investors. That may be true--to a certain extent. Those who are willing to take the time to perform the necessary due diligence and accept the risks that come with these strategies could benefit. But opening the flood gates also creates an additional burden for many, myself included. We now have to cope with the problem of comprehending these strategies, some of which are far from simple. In some respects, it has never been more difficult to be an investor.
Complex strategies tend to have a lot of moving parts working together to produce the desired performance. Systems with a large number of components are exposed to a larger number of failure points, thus increasing the probability that the system will break down. Daniel Kahneman and Amos Tversky addressed this concept in their paper "Judgment under Uncertainty: Heuristics and Biases": [1]
"A complex system, such as a nuclear reactor or the human body, will malfunction if any of its essential components fails. Even when the likelihood of failure in each component is slight, the probability of an overall failure can be high if many components are involved."
Mathematically, the probability of a system (or investment strategy) failing is much higher than the probability of any of its individual parts failing. This is because the odds associated with individual component failure actually compound when they are brought together, thus increasing the chance of the overall system failing. A failure of any single part can bring a larger system to its knees. Therefore, more moving parts in an investment strategy will only increase the likelihood of poor performance. We have seen countless examples of complicated strategies that have either failed to produce better performance or flamed out in catastrophic fashion (portfolio insurance, collateralised debt obligations, and so on).
Simplicity tends to trump complexity. Along these lines, Bloomberg published an insightful article about Bill Abt, the manager of endowment funds for Carthage College in Kenosha, Wisconsin. According to the article:
"He doesn't dabble in the fanciest Silicon Valley venture capital funds, hedge funds, or the latest computer-driven brainchildren of Ivy League physicists and mathematicians. … At Carthage, Abt's approach was more pedestrian: mostly low-cost, market-tracking index funds from Vanguard Group, the same funds used by legions of do-it-yourself individual investors."
Abt's track record was impressive to say the least. He beat Harvard's endowment by 1.8% annually over the 10 years through June 2017. And his 6.2% annualised return over that span bested 90% of his peers. This isn't the first story of its type to make the news in recent years. Warren Buffett's bet with Ted Seides--that Vanguard 500 Index (VFIAX, listed in the U.S.) would beat a fund of hedge funds--is another well-known take on the same theme: simple beats complicated.
But Abt's story instills another lesson about managing more-complicated investment strategies. His competitors, the managers at other endowments, are supposed to be the all-star teams of investment managers. They are highly educated and well connected. They're the ones who should understand complicated strategies better than anyone and be capable of exploiting their knowledge. If they can't beat a portfolio of simple index funds, what chance do we have?
Another reason these complicated investment strategies fail is they tend to charge higher fees. It’s simple arithmetic that expenses directly eat into investment returns. Cutting expenses is an evergreen and persistent benefit, a guarantee of sorts. It isn't derived from historic data. It exists regardless of how a strategy or the broader market performs, representing a rare certitude in an industry that is riddled with uncertainty.
Expense ratios are a direct way of looking at costs. Implicit costs, such as those involved with trading, are less obvious but no less important. A fund's turnover ratio is a good proxy for the implicit costs associated with implementing a strategy. Lower turnover means less trading activity in a given fund, which directly translates into fewer trading costs. Market-cap-weighted index-tracking funds tend to have very low turnover. Low fees and low turnover are central to the thesis that cap-weighted indexes will be among the top-performing strategies in their respective Morningstar Categories. The less you spend the more is left to compound. It's not a theory, it's a mathematical inevitability.
The concept of Occam's razor is a fitting way to summarise my perspective: When two or more choices are available, often the simpler solution leads to better results. Sticking with a simple investment approach means it is less likely to fall apart, making it more robust than one that is complicated. Minimising costs, both implicit and explicit, is a straightforward mathematical advantage. Plain-vanilla index-tracking funds are the most obvious way to capture these two characteristics, and that's where I'm placing my bets.
[1] Kahneman, D. and Tversky, A. 1974. "Judgment under Uncertainty: Heuristics and Biases." Science. Vol. 185, No. 4157. P. 1124.
