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A Century of Evidence on Trend Following

AQR recently updated its paper A Century of Evidence on Trend Following and whilst the updated hasn’t changed the basic conclusion of earlier versions it is worth unpacking some of the main point of the paper.

The paper in its introduction makes an immensely important point that is lost on most –

As an investment style, trend following has existed for a very long time. Some 200 years ago, the classical economist David Ricardo’s imperative to “cut short your losses” and “let your profits run on” suggests an attention to trends. A century later, the legendary trader Jesse Livermore stated explicitly that the “big money was not in the individual fluctuations but in … sizing up the entire market and its trend.”

The thing I always find fascinating about trading, markets and people is that everyone is trying to reinvent the wheel. I understand this compulsion after all a new wheel sells but the basic technology of trend following and trading in general is as seen above centuries old. Yet these simple ideas somehow go by the wayside. Granted our own psychology gets in the way of following Ricardo’s simple missive of letting our profits run and cutting our losses short as we find being in the action more compelling than actually trading correctly. But even professionals have trouble following this rule as evidenced by the number of institutions who hold stocks as they grind their way into the ground.

In assembling the material for this paper AQR looked at the monthly returns for some 67 markets which were made up of four major asset classes – 29 commodities, 11 equity indices, 15 bond markets and 12 currency pairs. Which is no mean feat when you are going back a century. The results of this analysis can be summed up in few charts. To test the notion of trend following they adopted a simple strategy consisting of a 1- month, 3-month, and 12-month momentum strategy for each market. In this instance momentum does not refer to an indicator but rather price movement.  A long position was taken if the pat return over the look back period was positive, conversely a short position was taken if the return over the look back period was negative.

It’s a simple if it’s going up buy it, if it’s going down sell it strategy.

Position sizing was volatility based and the portfolios were rescaled monthly to make certain that the portfolio hit an annualised volatility target of 10%. Fees and charges were included in the testing.

Take home points

Trend following was profitable in every decade since 1880 as shown in the table below.

Exhibit 1

Trend following beats traditional 60/40 portfolios. The chart below looks at drawdowns during periods of financial stress. As can be seen trend following does very well during these periods. The authors posit that this occurs because of the simple ability of trend following to point themselves in the direction of the prevailing trend as dictated by Livermore’s dictum of deciding what the overall trend is.

Drawdowns

Trend following produces outsized gains when markets are moving. In developing a trading system traders often simply look at the overall return of the system and if it is positive then they are happy. However, of equal importance is how those returns are derived. It has been my experience that the majority of returns are generated in a cluster of individual returns, that is the entire portfolio doesn’t do well but rather pockets of the portfolio do extremely well and drag the average up. In trading you want a strategy that produces outliers when the opportunity exists – you have to be a pig when the opportunity to be a pig presents itself.

smile

The chart above illustrates this phenomena – the chart looks a little complex but it is only measuring two things. The performance of the US stock market on the horizontal axis and the performance of the momentum strategy on the vertical axis. The green line curving a path through the dots is known as a smile and it shows that trend following produces its best returns when markets are moving.  This harks back to the earlier point of being able to take advantage of market moves when they occur.

Trading is a simple profession since it can be summed up in three ideas. If it is trending up over the time frame you are trading you buy it.If it trending down over the time frame you are trading you sell it. Dont bet the farm. It is hardly rocket science yet despite this our very nature more often than not defeats us despite the evidence that it shouldn’t.

FX YTD Performance

Since I was playing around with YTD performance I thought I would isolate a handful of currency pairs and see how they did and as you can see from below they are a mixed bunch.

Capture

Variations in performance are generally by themselves not that interesting, after all its a market and it depends upon variation for its survival. However, when we get performance data like this we can have a little bit of a look at correlations and link relative performance to correlation. In the table below I have coloured those correlations at +90% or above blue and those at -90%  or above red.

1

As you would expect pairs that have a high positive price correlation also have a high performance correlation. Once we get past the positive correlations my eye is always drawn to the negative correlations. For example EURUSD and USDCAD have almost inverse performance and share a -94% correlation. One goes up the other goes down. The mistake traders often make when they see this sort of thing is to assume that a negative correlation is no correlation when in fact these two instruments are very highly correlated. It just happens that the correlation is negative. Instruments that are not correlated have a correlation approaching 0% such as GBPUSD/EURCAD at -0.2% and EURJPY/EURCAD at 1%. This means that they share a very weak or almost non existent relationship.

Correlations are interesting from an academic perspective but there is a little bit of a problem. It is often assumed that correlations are fixed and whilst they can have a degree of stability over time this is a false assumption. The second problem is their relevance to traders who just take signals as they occur and here their relevance tails off. Granted if you are prudent in your exposure to a given currency then you will find yourself cut off from pursuing certain trades. For example if you had been long EURUSD, AUDUSD and GBPUSD at the same time then you dont have three positions but rather one. This sort of dilemma is something each trader needs to manage within their own trading universe as I dont think there is a hard and fast rule that applies to everyone.

 

YTD Performance

As we sail past the half way point of the year I thought I look in the rear view mirror might be interesting to see how a few select markets have performed. There are no prizes for guessing that the local market has been shit.

ytd

 

GBP Flash Crash Investigation Report

On October 7th 2016 the GBP suffered a minor aneurysm and dropped like a stone for a short period of time as seen below.

GBP_USD 5 Min

The Bank of International Settlements had just released a report into possible reasons for the crash. You can download the full report here.  The executive summary  outlines a constellation of  reasons for the crash –

A number of factors are likely to have contributed to and amplified this market dysfunction. In particular, significant demand to sell sterling to hedge options positions as the currency depreciated appears to have played an important role. The execution of stop-loss orders and the closing-out of positions as the currency traded through key levels may also have had an impact. A media report released shortly after the move began, which would have been interpreted as somewhat sterling-negative, is only likely to have added marginal weight to the move as it did not contain new information. These factors appear to have contributed to the mechanical cessation of trading on the futures exchange and the exhaustion of the limited liquidity on the
primary spot FX trading platform, which encouraged further withdrawal of liquidity by providers reliant on data from those venues.

The presence, outside the currency’s core time zone, of staff less experienced in trading sterling, with lower risk limits and risk appetite, and with less expertise in the suitability of particular algorithms for the prevailing market conditions, appears to have further amplified the movement. Other factors such as ‘fat finger’ errors and potential market abuse cannot be ruled out, but there are little, if any, hard data to substantiate them.

The report is actually an interesting read if only from the perspective of educating traders as to how liquidity can slip even in a market as large as FX due to changing time zones.. The data below gives an interesting insight into how you can have a period of high trading activity combined with relatively low liquidity as markets shift time zones.gbp liquidity

FX Correlations

A question popped up in the Mentor Program that related to what to do when related instruments all gave the same signal, in this instance the culprit was various JPY related pairs. I had not looked at FX correlations for awhile so thought I might stick a few together and see if they told me much of a story. With a bit of dodgy-fu I cobbled together the following table which looks at correlations of JPY related pairs over 1 day, 1 week and 1 month.

All

When looking at correlation we are confronted with two confounding issues. The first, as is obvious from the table above is the time frame over which we look. The shorter the time frame the more we might be prone to simple idiosyncratic shocks appearing in the data. This goes some way to explaining the wild variation i correlations over very sort time frames. As with all things the more data we have the more reliable (sometimes) the conclusions we can draw from what we see.

The second issue is what sort of correlation are we looking at. The correlations above are simple price correlations – do the pairs travel in the same direction over the same time frame. A slightly more sophisticated question question is are the returns from each instrument over various time frames comparable. To answer this question requires that we look at the returns correlations of instruments. The chart below looks at the returns of JPY denominated pairs over a longer time frame.

return correlation

As broad population they each follow a similar trajectory but there are some notable deviations which can probably be attributed to local factors. One of the issues that often catches FX traders is the assumption that because pairs share a currency then their movement should be identical and as we can see this is not quite true. This causes problems for what signals to take and the entire notion of diversification. Diversification is in its simplest form as practiced by the sell side of the industry revolves around things having different names but even things with similar names can be quite different.

The Year That Was.

It is that time of the year when everyone involved in this business looks in the rear vision mirror and attempts to make sense of what happened.  And of course to everyone involved everything is so obvious and predictable. What is worse is that they take this data and attempt to make some form of prediction about the year ahead. Hindsight is all we have and whilst it is the perfect investment tool; we are denied its luxury in the real world. Even looking at a league table of performance of various instruments is somewhat meaningless. However, since they are all the rage below is one such table I quickly knocked up for a few common instruments.

League Table

Part of the problem is that these tables are looked at from the perspective of the buy and hold investor. It is assumed that you simply bought one of everything last year and held onto it and your performance either good or bad is a function of this. However, this is not how trading works. For example the AUD/USD began the year with a 15% gain, which is then gave back and settled into a meandering decline resulting in its ordinary year on year performance. Likewise all the gain in heating oil came in the first half of the year. Conversely, cocoa which turned in a shocker traded in a range for most of the year and then collapsed in October.

Whilst it is twee to say so in trading only the journey counts not the destination, in fact I would go a little bit further and say that even the starting point is irrelevant. As such tables such as the one above whilst vaguely interesting are essentially irrelevant to us.

The Year In Money

Bloomberg have been busy – click the image below to be taken to the full infographic.

2016

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