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Does News Move Markets….Sort Of…Maybe…Well No Actually

I was chatting the other day with someone who was having trouble with their trading system. Their approach was based on trading news events. Such a plan is predicated on the notion that news events move markets in certain ways and whilst this movement might not be wholly predictable it will at least generate some form of activity. Such a trading system has a single giant assumption – that news and news related events move price. If this maxim does not hold up then the system is a bust.

It has been sometime since I looked at this question and I had a vague recollection of research done in the 1980’s that looked at this question and found that news as a source of trading ideas was a bust. So armed with the dimmest of memories I went looking through my archive and found what I was looking for. David Cutler, James Poterba and Lawrence Summers produced a working paper titled What Moves Stock Prices for the Department of Economics at MIT in 1988. This paper looked at the 50 largest single day moves in the US market since World War Two – I have included the events from the original monograph below.

Event 3

If you take a cursory look at the events above you could argue that news events do move markets. However, there is a glitch in that some movements defy explanation – there is simply no event that can be seen as a casual trigger for a market move. Cutler et al stated that news events could really only be useful as an agent for movement in about half of all cases of the variance in stock price movement and in my world half is a fluke.

The interesting side issue with the work of Cutler et al is that it puts another hole in the Efficient Market Hypothesis because stock price movements according to the EMH reflect the assessment of investors to new information. If markets move without the the addition of new information to the system then something else is happening that is not explained by the EMH. And it seems in the case of broad brush analysis as performed by Cutler that prices move without any significant input.

This initial work has been expanded upon by Ray Fair at Yale University who looked at outsized movements in the S&P500 futures contract. This new work had much greater granularity to it in that it looked at five minute data, something that would have been difficult in the original work by Cutler and crew simply because the available technology would not have allowed it. Fair compared what he defined as big movements with news items emanating from the Dow Jones News Service, Associated Press and New York Times. The upshot of this investigation seemed to be that the majority of large events have no news based driver. They were only able to attribute a news item to 69 of the 1159 big moves that were examined. Recent  flash crashes seem to support this notion of significant market moves  occurring without a notional driver.

So we come back to the original assumption that news events drive markets and that these moves offer opportunities that can be traded. It would seem on the evidence available that this notion is false.

Nothing To See Here

With a free afternoon I decided to look at the individual performance of stocks that make up the ASX 200 since the beginning of the year. What I did was assume that you invested $1.00 into each on the first trading day of the year and then see what their current valuation was. The table below maps them from highest to lowest.

table

It doesnt take a genius to work out that you will get a spectrum of values ranging from the very good – BGA to the very bad – ISD. The count is mildly positive with 109 stocks being at breakeven or above for the period. You can get a better sense of the distribution by looking at the frequency distribution of values below.

table 2

As you would expect there is a fat hump in the middles and two reasonably even tails. Some did really well, some did really badly and most didnt really do much However, this once again raises the question of the value of this sort of analysis and I would say outside of curiosity there is none. But it passed the afternoon and satisfied my curiosity.

How Things Have Changed

The change in the relative size of world markets over the past century. You will note that the Australian market has shrink significantly.

size

Source – Credit Suisse Global Investment Reurns Yearbook 2017

Momentum overpowers value investing in Aussie market

This piece in the AFR is currently doing the rounds with various people trumpeting that this is what they do so they are a genius. To be fair without actually seeing the original Morgan Stanley report or understanding what they did any comparison between different methodologies is profoundly limited in its utility.

 

Where Is The Money?

One of the frustrating things about being a trend follower is that it takes time to overcome the inertia of a new system, particularly if that system is based upon slightly longer time periods such as weekly data. Part of the frustration that traders encounter is based upon the simple mechanics of how systems work. A system that is correctly designed takes its losses quickly and allows its profitable trades to simply roll along. This results in the system instantly going into drawdown and it is this drawdown that causes traders to develop friction with their system. This friction often leads to tinkering as they attempt to force the system to give them something it cannot give. This is exacerbated in times of a flat market – you cannot force returns from a market. The All Ords of late has not really been a stand out performer as can be seen from the chart below the market has been slowly grinding its way up in a broad channel.

Ords

With this in mind I thought I would look at the yearly returns for the various stocks within the All Ords – so I found some data on their percentage returns and stuck it into a frequency histogram to see what the performance of individual stocks looked like.

Frequency

I have a arranged the data into a serious of blocks and did a count of the number that fell into that category. I also calculated the average performance of the group which for this period stood at 17.09%. However, if I drop out the 200% and above outliers this average value falls to 13.04%. As you might have guessed the majority of values cluster around the mean with a long right handed tail. This sort of distribution is common with stocks since we have unlimited upside but limited downside – a stock cannot decline more than 100%. Our psychology dictates that we are instantly drawn to the right hand side of the chart and the extreme outliers that occurred over the past year. And as traders these are the sort of trades that we hope ours might evolve into. However, in doing so we ignore that left hand side of the chart. The majority of stocks (60%) have below average performance. You may assume as a trend follower that this is not an issue since you would avoid these large losses and poor performance by the use of stops but that ignores the reality of the actual trading process. As a mechanical trader you will not incur these losses but you will burn time wading through these non performing stocks before you hit the ones that do perform. You waste time, a little bit of money and a lot of patience dealing with this mediocre performance.

My anecdotal experience has been that trading returns are made up of a lot of modest returns and a tiny handful of trades that do very well but to get to the ones that do very well you have to crank through a reasonable number of trades and you have to keep going. This is where the notion of emotional resilience comes into its own in trading and the ability not to tinker with the system hoping that it will generate these sorts of trades. Systems dont actually generate these sorts of trades – the market does so you cannot actually build a system with the preconceived notion that it will find you trades that generate a 500% return. What the system does do is generate a population of trades, most of which will be duds and hopefully a few large winners. But in the beginning all trades look the same.

 

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.

Once Upon A Time

Sometimes I feel sorry for traders/investors who need to construct a narrative as part of their investment process. Whilst you are cocooned inside your own delusional story you would never know whether your story is the right one and is the one the market has chosen. As an example consider the year to date moves of various indices from around the world.

Index Performance YTD

As might be expected there are a range of performances but what is interesting to me is that if you look at the US markets in isolation you see something interesting. The Russell 3000 and S&P500 are doing better than the benchmark index. This positive performance seems quite obvious when you drop in the performance of the VIX – the so called fear index.

Index Performance_VIX

The VIX has had a somewhat precipitous drop since the beginning of the year. As such the narrative could go volatility (uncertainty) has leaked out of the system therefore investors feel more comfortable with equities. Sounds reasonable, however, there is always someone who will spoil a good story. Consider the chart below  is of the ETF GLD and the Dow since the US election in November. GLD tracks the spot price of gold so it serves as a useful proxy.

Dow_GLD Since Election

Throughout November the gap in performance between the Dow and GLD widened – this would fit our existing narrative of the market being more settled therefore there is no need to set in place a hedge via gold. However , this story starts to change as Trumps profound lack of suitability as President  becomes obvious and the performance gap narrows. If we shrink the time frame down to YTD only then the Trump idiot premium widens.

Dow GLD YTD

All of a sudden we have a wrinkle in our narrative. The original narrative was uncertainty has left the system, investors are happy and buying equities but hang on the performance of gold which is traditionally seen as a hedge instrument is improving. WTF is going on?

This is the issue with narratives they are simply stories designed to make us feel better about our decisions as such they are equal parts post-dictive error, self justification  and comfort food. Hence, they are largely meaningless.

 

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