We have all heard the timeless adage “Cut your losses, let your winners run”, which forms the central tenet of Trend Following.
Proverbs travel through generations and their origins get lost, so I was quite interested when I found out about an 1838 book, The Great Metropolis, Vol II by James Grant, tracing back the saying to eighteenth century British economist and trader David Ricardo (I actually thought that this legendary trading maxim was introduced by Jesse Livermore in Reminiscences of a Stock Operator).
The actual wording was:
“Cut short your losses,” – Let your profits run on”
and further description can be found in the book:
It does seem that smart traders were already using trend following principles as far back as a few centuries ago.
I did find out about this book thanks to a very interesting paper by Stig Ostgaard: On the Nature and Origins of Trend Following, which retraces the early history of trend following, from Ricardo all the way to trend following pioneer Richard Donchian. Well worth a read in my opinion.
More History, and Correlation
Another very good and interesting document I came across recently is a presentation by Trend Following Wizard Liz Cheval, which can be found on her EMC Capital CTA website.
The presentation is called “Let’s get negative: Correlation and the case for Managed Futures” and is divided in two parts.
The first part is also historical. First using the Nasdaq as an example, it describes market manias (a.k.a. supersized trends) and why they are bound to repeat (Investment Psychology). The main concepts are:
- Chrono-centricity: Each generation believes they are on the cusp of history and what is happening to them is so important that it will impact the world deeply and permanently and that this is the beginning of a new era (as experienced during the internet boom, which actually generated very similar reactions to the telegraph, as per the book The Victorian Internet).
- Short financial memory: In A short history of financial euphoria, John K. Galbraith explains that non-stop cycles of boom and bust are bound to repeat due to the brevity of financial collective memory: every 20 years, we collectively forget what has happened in the last 20 years.
- Inability to predict: using after-the-fact “funny” examples of prediction quotes, Cheval shows that we cannot rely on experts and analysts to make reliable forecasts. One such is, then IBM Chairman, Thomas J. Watson declaring in 1943: “I think there is world market for about five computers”
The presentation then moves on to second part: mathematics of correlation/diversification.
There is nothing revolutionary new: talking about Markowitz and the Modern Portfolio Theory, Cheval shows that you can put a more risky asset in a portfolio and improve its risk-adjusted return. The following chart taken from the presentation, shows how adding the blue “ugly curve” to the green “beautiful” one does improve its return and eliminate its volatility as per the orange curve (the two equity curves were engineered and do not represent actual assets).
The interesting point is that it is possible to improve performance by adding curve “blue”, an asset with negative geometric average return (but with positive arithmetic return). Intuitively, most people would tend to think that curve “blue” is a “dud” and can in no way improve performance. Cheval likens this curve to Managed Futures, which she compares to the “investment ugly sister” (high drawdowns, volatility, etc.) that can actually greatly improve an investor’s diversified portfolio, thanks to their low to negative correlation and positive returns.
The discussion and clarification on correlation is interesting. Everybody (myself included) must be falling prey to some misconceptions/mis-uses of correlation in everyday language. Common language has it that two things are correlated if they “move together” and anti-correlated if they “move opposite to each other”.
As such most investors would probably think that the “ideal” asset would be one negatively correlated during an equity bear market and positively correlated during a bull market (ie the best of both worlds). Not quite.
As Liz Cheval puts it – in plain simple English but correct definition:
Correlation is a numerical measure of the tendency for two assets to concurrently under-perform or over-perform their average returns by the same number of standard deviations.
So, not “moving together, or opposite to each other”, but rather away from their averages in the same, or opposite direction (in their respective magnitude).
Meaning that an asset can be strongly negatively correlated (even perfectly at -1) to another one, with both being in a bull market as illustrated by this plot of two equity curves, which concludes this article: