Thursday, July 22, 2021

Speculations: Trend Following

In futures almost everyone who makes directional bets ends up being a trend-follower. As the futures markets became less opaque and computers got faster and faster the opportunities in spreads and option combination trades became smaller and smaller leading to more focus on the outrights.

Which led to a very rapid understanding of just what leverage means. Taking copper as an example, the CME contract covers 25,000 pounds. With the last trade at $4.3205 the trader has control over ~$108,000 of the red stuff. For maybe a 7% initial margin deposit.

You simply can't afford even a 3% move against you in the underlying. So as they say: The trend is your friend.

Until the bend at the end.

A note on our source: Verdad Advisers attempts to replicate private-equity type returns by applying leverage to publicly traded equities, mainly mid-caps, the sweet spot of the PE crowd. They seem to have a pretty good understanding of the risk of leverage although this piece does not address that profoundly important issue but rather focuses on timing. For more on reducing drawdowns see after the jump.

From Verdad, July 19:

Trend Following
Risk Reduction and Return Impacts

Quantitative researchers studying markets have found in paper after paper that historical price trends seem to offer information about future returns: specifically, assets that have been going up often continue to go up and assets that are going down often continue to go down. Practitioners most commonly use trend following to reduce drawdowns, though there are some that argue that trend following also improves returns.

Yet this finding is somewhat uncomfortable. The idea that we should buy when prices are higher and sell when prices are lower seems to defy economic intuition. And relying on historical price patterns to make investment decisions seems either too simple to not have been arbitraged away or too close to pseudoscience to be implementable.

We wanted to study trend following for ourselves to attempt to reconcile the academic literature with our skepticism. Assessing trend following is difficult because there are so many different ways to define when an asset is rising or when it is falling. Without a standard for measuring trend––a necessary precondition for assessing its strategic value––much of the rigor in such an analysis is lost. So we must first choose a standard to determine the trend of an asset, then determine the effectiveness of a trend-following strategy across a wide range of asset classes.

We started by looking at how trend following would have performed out of sample on a set of individual assets. There are multiple ways to define trend, and these approaches generally yield similar results. We chose to use autoregressive (AR) and moving average (MA) models that measure the strength of mean reversion and trend in recent monthly returns to forecast the next month’s return. Our first step was to train an ARMA model on each asset using in-sample data before Dec 31, 1999. This gave us a trend-following predictor that was specific to each asset. Our second step was to test these predictors on new data from Jan 2000 to Dec 2020 to see how well they would have performed out of sample. We looked at how trend following impacted both returns and drawdowns.


Trend-following’s impact on returns is inconsistent when tested over the last 20 years. Recent research has suggested that more frequent reversals of trend have decreased the returns of trend following. Fewer extended periods of trend lead to lower returns. Our findings are not an indictment of trend-following strategies, but they do suggest, unsurprisingly, that a simple, rigid approach with monthly data is not sufficient to create a successful strategy.

But the simple approach does highlight very clearly that trend following’s real advantage is in reducing drawdowns. The improvement in drawdowns is both more consistent and more significant: trend following improved drawdowns in the asset classes we studied by an average of 9.5 percentage points. As a risk signal, it works very well, especially for assets that tend to trend. Take large growth as an example. Below we have plotted the sell signals for large growth over the past 20 years....


On measures of volatility, keeping in mind that volatility does not equal risk unless your margin clerk forces you to sell at the bottom, see:

"The Equation that Will Change Finance"
Questions America Wants Answered: Is Semi-Variance A Better Measure of Risk?
"Is semi-variance a more useful measure of downside risk than standard deviation?"
We didn't post 'When Volatility Is Suppressed' a couple weeks ago just because the cat video channel was down...
When Volatility Is Suppressed
Stock Market Prices Do Not Follow Random Walks 

Or as Fama/French put it:

Is semi-variance a more useful measure of downside risk than standard deviation? My clients aren't worried about market surges, they're worried about market crashes....

...Let's now examine whether you really believe what you say about your client's tastes. In our (academic) terms, your statements imply that your clients are risk neutral on the upside but risk averse on the downside. If this is the case, the semi-variance, which ignores upside risk, is probably a better single measure of risk than the variance, but the conclusion is subject to the caveats above about the skewness of return distributions for longer return horizons....