The Small Investor’s [Only] Advantage – And How To Capture It
Take a moment to study the second most interesting chart you’ll see this week.
This scattershot pattern shows the relationship over a four-year period between the annualized Return (the gain in value on an investment portfolio) and the level of Risk (the volatility or variability of that value over time) for 800 different computer-generated combinations of seven asset classes: U.S. large-company stocks, U.S. small-company stocks, European stocks, Japanese stocks, Pacific Rim stocks, precious metals stocks, and five-year Treasurys. These are simulations, but we can say with confidence that any real portfolio composed of these asset classes, for this time period, would lie somewhere within this field. [The chart is adapted from The Intelligent Asset Allocator, by William Bernstein (McGraw-Hill, 2001), p. 56.]
It seems a triumph of randomness. Classic Finance Theory holds that higher Returns are associated with higher Risk. But here the outcomes are spread out all over the Risk/Return space. Risk and Return are uncorrelated. One portfolio may have three times the Risk of another, for the same Return – or twice the Return for the same Risk.
A similar chart of the real-world performance of 82 large corporate pension funds shows that simulation and reality are not so different.
It is not only pension funds that struggle. Active Management in general has a dismal record. Only about a third of fund managers beat the market average in a given year. Only 10% or so can beat randomness 2 years in a row. 5-year and 15-year performance – worse. Dart-throwing would do better (truly, but that’s another story).
How Can You Compete?
So what hope is there for the ordinary investor? How can an amateur compete against the professionals? — those fittest survivors of the intense Darwinian environment we call “Wall Street” (to include Stamford, Conn., and Chicago, and London, and all the other hedge-fund rookeries). The pros have the experience, the technology, the capital, access to top quality research and the best management talent money can hire. They work this game all day, every day. So if they still struggle against the random nature of the market, how can the ordinary investor ever hope to win?
But the pattern is not quite random. A hidden signal – of particular relevance precisely for the non-professional – lurks in noise.
For there is a hint of structure in the simulation results. The outcomes crowd slightly towards the “west/northwest.” Finance theorists draw a line along this left edge, called the “Efficient Frontier” – where the best Risk/Return trade-offs are to be found.
The goal of portfolio construction can be simply stated: How can we move toward this frontier? Any portfolio mix that does not lie on the Frontier is suboptimal, and the farther it is from the Frontier, the worse it is.
The Simple Answer: Time
Now — here is the most interesting chart you will see all week.
This is a “rerun” of the same simulation, with the same selection of assets – but the time frame has been extended — from 4 years to 20 years.
This change clarifies the structure of the “portfolio risk/return space” in three ways:
- The Efficient Frontier is much more sharply defined.
- The entire Frontier has moved outwards, upwards, towards the Northwest quadrant. The return and risk parameters are both improved. In fact, almost all of the portfolios show improved performance — lower Risk and higher Return.
- All the portfolios have moved closer to the Frontier. The differences among them are greatly reduced. This reduces the need to worry about the specific mix, since all of them now exhibit performance more or less equally close to the optimum.
More extraordinary still: almost all the 20-year portfolios outperform even the best 4-year portfolios. The gain from extending the investment time horizon is much more powerful, and more stable, than the traditional (and overrated) benefit of conventional diversification.
Quantifying the Gains
Another study quantified this performance advantage. Portfolios tracking the S&P 500 index were created with holding times ranging from 1 year to 25 years, starting in each year over the period from 1928 to 2015. Performance improved steadily with longer holding times. For example, the average of all portfolios held for 20 years exhibited an annualized return 100 basis points higher than the average of portfolios based on a 5-year holding period.
A 1% per annum improvement is striking – given that the investment universe is the same, and is very broad (essentially the whole market). And of course the compounding effect is much more significant. The chart below shows the increase in portfolio value that comes from simply lengthening the holding time. For example, a portfolio held for 20 years beats a concatenation of four 5-year portfolios – in other words, a scenario where the portfolio is cashed out and reinvested every five years, four times in succession. The 20-year portfolio value ends up almost 21% higher than the chain of four 5-year portfolios.
Of course, even 5-years may seem like an atypically long holding period in the context of actual market practices. If we compare a series of 1-year portfolios – investing in the S&P index for one year, cashing out, and reinvesting each year for twenty years – with a single 20-year holding period, the longer scenario is 32% higher at the end of the 20 years and 45% higher after 25 years. And this does not take into account transaction costs, which are obviously much higher for the rinse-and-repeat year-by-year scenario.
This is not alpha – there is no selection process to sort for winners and losers. But it is not really conventional beta, either. It cannot really be characterized as a risk factor. It is a source of enhanced returns that sits on top of the market beta (so to speak).
In any case, this is the advantage — the only advantage, but a decisive one — that retail investors enjoy. It is an advantage that the professionals cannot exploit. They have trouble extending the investment horizon more than a couple years. Fund managers have their investors, with varying levels of patience, few of whom are willing to wait decades for their payoff. Funds have to report regularly, and a few bad periods can drive redemptions (investor withdrawals), management turnover, strategy shifts and fund closures. They are forced to play the shorter game. And of course if they use leverage, or hedges with short positions, their ability to hang in for the long run is further compromised.
Time-averaging is the equalizer for retail investors. Think of it this way: the professionals are forced to search for the best outcome from among those in the Risk/Return space depicted in the short-term chart. The individual investor can be satisfied with an average outcome from among those in the long-term chart — and yet still beat the best of the pros. Instead of emulating them, small investors should simply commit, truly, to the long-term perspective — and let the inherent structure of the market process do the rest.