13 june 2019


This article also appeared on Forbes.com

Stocks can deliver strong long-term investment returns. The DJIA, for example, has averaged a 7.3% annual price increase since 1900. But people invest for much shorter time spans, where returns are hugely unpredictable. In any given year, the DJIA return is four times more likely to be less than half or more than double its long-term average than to fall within that range.

Such high volatility turns investing into a stomach-churning rollercoaster, and investors respond with unhealthy responses that sabotage their results. To prevent them, they should concentrate on avoiding the onset of stress rather than on learning how to deal with it.

It is well known that people dislike losses much more acutely than they enjoy gains. That’s a big reason why, after a big loss, they dump stocks and stay away well past the end of the rout. A big recovery will have to take place before they feel safe enough to return, and by then much of the upside will have already happened.

Experts keep telling people to ignore their emotions. This sounds like good advice, but it is unrealistic. People cannot be expected to stay calm while their savings fall by 50% or 60%, as during the worst moments of the Financial Crisis, without feeling an intense need to act.

A better approach is to acknowledge that those emotions will come up, and find ways to prevent them from being triggered. Reducing portfolio volatility is a good way to keep people invested, improve their long-term chances of success and in some cases outperform the market.

To see why, imagine that the market goes down 50% and then up 100%. That means that $100 invested in the market first falls to $50 and then climbs back to $100, so the sequence just breaks even.

Now imagine an investment that cuts all market returns in half. That investment first will lose 25% (half of 50%) and then gain 50% (half of 100%). This means that $100 first will fall to $75 and then climb to $112.50. Such investment has a positive return even when the market goes nowhere, and it was more likely to prevent the urge to sell at the bottom when the loss was most painful.

Capturing just half of market returns, however, does not work too well in long-term rallies. When you limit volatility, you give up a portion of the upside to avoid the full brunt of a severe downturn. But if the downturn does not materialize for a long time, you may start to feel that you are paying too much for insurance you don’t use.

This emotional response, sometimes called greed, also affects returns negatively. It tends to show up during long market rallies. Professor Charles Kindleberger summed it up well in a famous sentence in his book Manias, Panics and Crashes:

​"there is nothing so disturbing to one’s well-being and judgment as to see a friend get rich."

Aggressive investors who maximize exposure will outperform investors who are more prudent during a market rally. Late in the bull cycle, cautious investors who feel that they are missing out will dismantle safeguards in the hope of catching up. This stage is often called “euphoria.” It rarely ends well.

One way of mitigating that particular urge is to improve portfolio performance during up markets. Along with reducing losses during down markets, this combination is the Holy Grail of investing: Maximizing the up-capture and minimizing the down-capture.

It is virtually impossible for investment strategies that focus on a narrow asset class (such as value stocks, growth stocks, large caps, small caps, etc.) to achieve that goal. The fortunes of a single asset class strategy are tied to its ups and downs. That’s why diversification is a common way of reducing volatility, as it combines assets that are not expected to go up and down at the same time.

But common diversification strategies do not always work. One example is that S&P sectors behave quite independently during normal markets, and mixing them in a portfolio will make it look “diversified.” But they will all fall together when the market crashes, and a portfolio made up with these sectors will suffer as if it wasn't diversified at all.

Some strategies tackle static diversification problems by trying to respond to changes in the market cycle – i.e. by increasing or decreasing exposure to the overall market at different times.

Tactical Allocation (TA) strategies, for instance, focus specifically on that goal and seem to be successful at smoothing out returns. They even outperform the market by reducing volatility as in the example given earlier.

The average performance of TA mutual funds tracked by Morningstar shows that the category goes up less than the market during rallies and down less during bear markets. For example, between the peak of the dot-com boom of March 2000 through August 2011, TA funds returned more than 30% while the S&P 500 broke even, achieving this by reducing both positive and negative returns.

As the rally continued after 2011, however, TA funds fell behind. Lowering volatility can be very effective at preventing the urge to cut losses at inappropriate times, but it leads to underperformance during long rallies that can be hard to swallow.

Some TA funds, of course, perform better than others, so it may be possible to find a few that improve results on the way up, but accurately predicting which ones will outperform their peers is impossible.

A search for the appropriate fund, however, can be narrowed by the type of process used to achieve objectives. One major distinction is between those that make investment decisions based on “fundamental” or qualitative factors, and those that focus on establishing quantitative rules upon which those decisions are made.

A paper co-authored by Nobel laureate Daniel Kahneman (of Thinking Fast And Slow fame) compares both types of decision making and concludes that expert opinions are less reliable than rules-based analysis.

According to the study,

"experts can be strongly influenced by irrelevant factors such as personal mood, time since the decision-makers last meal, or the weather."

Not only similarly-trained experts give entirely different answers to the same question, but they even contradict their own prior answers. This should be obvious to anyone who watches financial news TV.

The paper suggests that decision results can be improved by the implementation of hard rules:

"It has long been known that predictions and decisions generated by simple statistical algorithms are often more accurate than those made by experts, even when the experts have access to more information than the formulas use. It is less well known that the key advantage of algorithms is that they are noise-free: Unlike humans, a formula will always return the same output for any given input. Superior consistency allows even simple and imperfect algorithms to achieve greater accuracy than human professionals."

If the authors are correct, rules-based strategies should be preferred to “high conviction”, investment-committee-led strategies, which one would suspect are subject to the same biases that affect all humans.

Human emotions are powerful and can be very destructive when it comes to investing. Ignoring them is a fool’s errand, as they usually prevail. A better approach is to prevent them from being triggered in the first place. Tactical Allocation processes can be very useful at this because they focus on lowering volatility and thus prevent the onset of fear. But they must also strive to improve upside returns to prevent other destructive emotions from arising – greed.

The process by which all this is achieved matters. A rules-based Tactical approach that lowers volatility and tackles diversification dynamically may be the best way of dealing with the old problem of emotions in investing. Investors who do the homework to find out what process is the best for them may be well rewarded.