Growth and Trend: A Simple, Powerful Technique for Timing the Stock Market | PHILOSOPHICAL ECONOMICS

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Growth and Trend: A Simple, Powerful Technique for Timing the Stock Market

Posted on January 18, 2016 by philosophicalecon@gmail.com

Suppose that you had the magical ability to foresee turns in the business cycle before they happened.  As an investor, what would you do with that ability?  Presumably, you would use it to time the stock market.  You would sell equities in advance of recessions, and buy them back in advance of recoveries.

The following chart shows the hypothetical historical performance of an investment strategy that times the market on perfect knowledge of future recession dates.  The strategy, called "Perfect Recession Timing", switches from equities (the S&P 500) into cash (treasury bills) exactly one month before each recession begins, and from cash back into equities exactly one month before each recession ends (first chart: linear scale; second chart: logarithmic scale):

As you can see, Perfect Recession Timing strongly outperforms the market.  It generates a total return of 12.9% per year, 170 bps higher than the market’s 11.2% .  It experiences annualized volatility of 12.8% , 170 bps less than the market’s 14.5% .  It suffers a maximum drawdown of -27.2% , roughly half of the market’s -51.0% .

In this piece, I’m going to introduce a market timing strategy that will seek to match the performance of Perfect Recession Timing, without relying on knowledge of future recession dates.  That strategy, which I’m going to call "Growth-Trend Timing", works by adding a growth filter to the well-known trend-following strategies tested in the prior piece.  The chart below shows the performance of Growth-Trend Timing in U.S. equities (blue line) alongside the performance of Perfect Recession Timing (red line):

The dotted blue line is Growth-Trend Timing’s outperformance relative to a strategy that buys and holds the market.  In the places where the line ratchets higher, the strategy is exiting the market and re-entering at lower prices, locking in outperformance.  Notice that the line ratchets higher in almost perfect synchrony with the dotted red line, the outperformance of Perfect Recession Timing.  That’s exactly the intent–for Growth-Trend Timing to successfully do what Perfect Recession Timing does, using information that is fully entirely available to investors in the present moment, as opposed to information that will only be available to them in the future, in hindsight.

The piece will consist of three parts:

In the first part, I’m going to construct a series of random models of security prices. I’m going to use the models to rigorously articulate the geometric concepts that determine the performance of trend-following market timing strategies.  In understanding the concepts in this section, we will understand what trend-following strategies have to do in order to be successful.  We will then be able to devise specific strategies to optimize their performance.

In the second part, I’m going to use insights from the first part to explain why trend-following market timing strategies perform well on aggregate indices (e.g., S&P 500, FTSE, Nikkei, etc.), but not on individual stocks (e.g., Disney, BP, Toyota, etc.). Recall that we encountered this puzzling result in the prior piece, and left it unresolved.

In the third part, I’m going to use insights gained from both the first and second parts to build the new strategy: Growth-Trend Timing.  I’m then going to do some simple out-of-sample tests on the new strategy, to illustrate the potential.  More rigorous testing will follow in a subsequent piece.

Before I begin, I’m going to make an important clarification on the topic of "momentum."

Momentum: Two Versions

The market timing strategies that we analyzed in the prior piece (please read it if you haven’t already) are often described as strategies that profit off of the phenomenon of "momentum."  To avoid confusion, we need to distinguish between two different empirical observations related to that phenomenon:

The first is the observation that the trailing annual returns of a security predict its likely returns in the next month.  High trailing annual returns suggest high returns in the next month, low trailing annual returns suggest low returns in the next month. This phenomenon underlies the power of the Fama-French-Asness momentum factor, which sorts the market each month on the basis of prior annual returns.

The second is the observation that when a security exhibits a negative price trend, the security is more likely to suffer a substantial drawdown over the coming periods than when it exhibits a positive trend.  Here, a negative trend is defined as a negative trailing return on some horizon (i.e.,...