Summary

  • We often hear trend following being referred to as “market timing”
  • In all active strategies, timing is an important concept
  • Market timing is a distinct process whereby investors try to predict the future
  • Momentum is reactionary, not predictive, and is therefore no more a form of market timing than value investing is

Trend following investment strategies seek to invest in positive trending assets and avoid those with negative trends.

In doing so, trend followers seek to participate in market growth while avoiding significant bear markets.

This can cause some investors to ask us, “are you trying to pick tops and bottoms?  Are you trying to time the market?”

First, let’s consider value investing.  The primary concept behind value investing is that a share of stock represents ownership of a company.  Therefore, prudent investing requires financial analysis to determine what the company is worth and therefore what the intrinsic value of a single share is.  When the market price is at a significant discount to that intrinsic value, it is an attractive purchase to a value investor.

Time plays a critical role in this process.  A value investor makes their purchase at a very specific point in time: when a stock is trading at a significant discount to intrinsic value.  Not before and not after.  The timing of the purchase is important.

Yet would anyone consider value investing to be market timing?

Of course not.  Nothing in the value process is trying to call tops or bottoms.

Now let’s consider trend following.  A trend follower is going to use a model to estimate the underlying trend in the stock price.  A simple example would be a simple moving average.  When the trend is positive, the trend follower is invested; when the trend is negative, the trend follower is not.

While the rules are different, much like a value investor the rules tell the trend investor when to buy and sell.

But just because the rules dictate when does not mean it is market timing.

The distinction between market timing and any other form of active investing is in prediction.

Consider the value investor again.  Their rules tell them when to buy and sell, but they say nothing about how long they may hold a position.  Nor do they try to predict when the stock will be attractive to purchase in the future.  They simply wait for the opportune moment.

This is the same with trend followers.  The trend signals signal a change in investment behavior, but they say nothing about how long the trend follower should expect the trend to persist.  The trend follower is not calling tops and bottoms – she is simply reacting to changes in price action.  By definition, a trend follower will buy or sell after at top or bottom has formed.

We believe the best metaphor to explain the difference is one about a stoplight.

A market timer will try to predict when the light will change.  If they see a green light, they may start braking, predicting that the light will turn red.  Or if they pull up at a red, they might try to “jump” the light and guess when it is going to turn green.

A trend follower will simply pull up at the light and act accordingly.  If the light is green, the trend follower will go through.  If the light is red, the trend follower will wait for it to turn green.  No predicting, just reacting.

Corey is co-founder and Chief Investment Officer of Newfound Research, a quantitative asset manager offering a suite of separately managed accounts and mutual funds. At Newfound, Corey is responsible for portfolio management, investment research, strategy development, and communication of the firm's views to clients.

Prior to offering asset management services, Newfound licensed research from the quantitative investment models developed by Corey. At peak, this research helped steer the tactical allocation decisions for upwards of $10bn.

Corey is a frequent speaker on industry panels and contributes to ETF.com, ETF Trends, and Forbes.com’s Great Speculations blog. He was named a 2014 ETF All Star by ETF.com.

Corey holds a Master of Science in Computational Finance from Carnegie Mellon University and a Bachelor of Science in Computer Science, cum laude, from Cornell University.

You can connect with Corey on LinkedIn or Twitter.