Trend Following for Safe Investing
I’m sure you’ll agree that more and more conversations with clients focus on their concern about a major correction coming soon. They have a very real fear of the market and its future direction. The deep wounds from 2008 and the “Lost Decade” for stocks in the 2000s have caused them to look for better investments.
Many investors are simply fed up with the status quo and are approaching their advisors about alternative strategies. One of particular interest is “trend following.”
What Is Trend Following?
According to Wikipedia, it’s an investment strategy based on the technical analysis of market prices rather than the fundamental strengths of companies. In one analogy, the market behaves just like the waves of an ocean; a surfer riding a wave has no more control over it than an investor riding a trend. Surfers simply take advantage of forces that already exist for their benefit.
Trend followers do not try to predict the future, any more than surfers try to create waves. The first job of a trend follower is to determine whether a trend actually exists or is substantial enough to take advantage of. Trend followers use different techniques to determine the trend. While there is no right or wrong way to do this, some techniques are more effective than others, just as some techniques are more effective in other investment methods.
This is kind of a “duh” statement, but important to understand: Trend following only works when there is a trend. Every investing technique has opportune moments in time to work, and this one is no different. When that surfer shows up at the beach and there are no waves—or worse, just little ripples—the surfer is going to have a tough day, wading in the water doing nothing. Poor waves are the worst, since the surfer will spend a lot of energy for little effect.
One argument against trend following is that you need to wait for a trend to actually exist before you identify it, so investors miss a lot of the move before they actually enter the trade. The worst are very short-term trends. Little “ripples” create havoc for a simple strategy. As the market starts rising, investors may identify the trend and then enter when the market reverses. They exit when the trend has broken, buying high and selling low, taking a loss when the general market might have been flat. Trendless time periods can dramatically affect performance in this investing strategy, though a more sophisticated system is robust enough to minimize the impact.
Because investors in this strategy are not predicting the future, they will never enter at the absolute bottom or exit at the absolute top. The goal is to catch the bulk of the trend (our personal goal is to catch 90% of the move up and miss 90% of the move down).
The Trend Is Your Friend
The beauty of trend following is that it doesn’t require you to suffer through large drawdowns, which is the primary reason it makes so much sense to the average investor. It’s not about capturing profit so much as the strategy’s uncanny ability to control risk and preserve capital … safe investing.
To me, it’s to be used as a safety measure. It is about keeping our client funds safe in extreme times. Let’s face it, risk control is why our clients hire us. They expect that we will be there in volatile times to protect them. The market corrects on average two to three times a year, with sharp corrections of 20% or more every two to three years. Protecting our clients’ base is a very clear goal in these cases.
By not taking part in the declines, we have been able to outperform the market with a 153% return against the S&P 500, returning 8% over the past five years. So while a buy-and-hold strategy has been steadily chugging along to get a client back to breakeven, a trend following strategy missed the large drop and since then has been taking part in the gains.
By controlling risk, you outperform over time. It is an odd concept to wrestle with, that taking a defensive role actually creates more alpha.
So how does a trend follower determine when a trend is here? A surfer scans the horizon for an incoming wave and uses his or her knowledge of what a good wave looks like when deciding whether to ride the next one. In the same way, trend following uses historical precedent.
Past Performance doesn’t imply future performance
Now, before you get all up in arms, saying, “Just because it happened in the past doesn’t mean it will happen in the future,” remember that our entire thought process as a civilization is based on using historical precedent to predict a future outcome. In fact, our brains are even oriented to think this way. If a baby cries, he gets the attention of his mom, so he cries more often. He has learned by analyzing history that crying gets him what he wants.
Statistics is, “the practice of collecting and analyzing numerical data in large quantities.” It offers a way to study history and see the likelihood that one outcome will happen again in the future. The goal of statisticians is to find out what “the norm” looks like, and through that analysis they can predict the odds something will happen again.
Most of our society is designed around statistics. Traffic laws are based on them. Airplane manufacturers use historical studies to find the best materials to keep planes in the air. College admissions are based on the SATs. Even the IRS uses statistics to analyze income tax returns, looking for those with a high probability of fraudulent information. Historical analysis/statistics are used literally everywhere to gain a valuable insight into what might happen in the future based on the past.
Trend following is no different from fundamental analysis in this regard. All successful strategies use historical analysis. If you think about it, fundamental analysts have developed systems that use specific ratios that, “based on history,” have high success rates. I realize I am oversimplifying, but a low PE company implies that its stock is undervalued, and the odds are good that buying stock at that point will result in a profit.
The reality is that all systems perform ideally in certain environments and are less ideal in others. Trend following is good at avoiding the extremes. When markets are trendless, of course, this strategy does not perform as well as traditional techniques. One style is not necessarily better than the other, just better at specific moments. A combination of both approaches offers the best of both worlds: minimizing loss during declines and maximizing gains in trendless or trending markets.
The Perils Of Data Fitting
The problem with using historical analysis for anything is related to “data fitting.” This occurs when an assumption is made about the future outcome based on past precedent without a large enough sample. If you flip a quarter 10 times and it shows up heads nine times, you could suggest there is a 90% chance the next flip will come back heads. But we all see the problem there.
Because making assumptions using small data sets poses a significant problem, to get around this issue a good analyst will start with a theory and test it. If the theory holds up, he or she will test it further with larger and larger data sets. To me, a strategy, regardless of its technique, is successful only if it is consistent and performs as it is expected to across all time periods.
When marketing any investment strategy to prospective clients, it is imperative that the client get an accurate assessment of how it will perform over time. By showing only specific periods of time (data fitting), advisors might imply better performance than what will actually occur. Picking a handful of very selective charts that omit negative performance only hurts your firm over time.
That means keeping customers happy starts with setting their expectations correctly on Day One, making certain your analysis covers a large enough time spectrum to account for all market anomalies.
In our case, we have tested our systems through the past 40 years, seeing the performance through extreme periods like the hyperinflation of the 1970s, the dramatic declines in October 1987, the dot-com bubble, etc. The goal was to identify the times that the model did not perform as expected, and be able to give potential customers an expectation of their future performance. Testing through 40 years was not easy, but a good strategy uses enough data to identify those times the system performs well and when it doesn’t. That way you can provide full disclosure to your clients and guarantee their long-term satisfaction with the plan.
A Probabilities Game
Statistics do not guarantee success, but the more analysis performed, the more likely the future outcome will be as expected. Historical precedent puts the odds in your favor. And that’s what it is all about—using empirical data to increase your probabilities of success.
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