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The Order Of Things Matters

Every now and again I get sent a magic trading system complete with equity curve, generally these are some sort of magic system someone is flogging that promises massive returns and never has a drawdown. They are the sort of quit your job with $10,000 and intra-day trade FX and make $10,000 per week. If you have been around markets long enough you will have seen this sort of thing – I have to give them some credit because at least they include and equity curve as opposed to simply quoting some mythical average return like fund managers do. Equity curves do convey a lot of information – they tell you about the trajectory of funds that have been invested. You can get a sense of how bumpy the journey might be and whether you could stomach the trip. However, the thing they do not tell you is the role of luck in achieving those particular returns. The returns a trading system generates and in turn its equity curve are uniquely sensitive to luck – not so much in the sense that the trader may have gotten lucky and run into the largest bull market in history which is entirely possible. But rather they are completely dependent upon the order in which the returns where generated.

To give you a simple example of this consider the chart below. In this chart I map the value of $1 invested in the All Ordinaries and $1 invested in the All Ordinaries but with the returns reversed so the return for 2015 becomes the return for 1900 and so on.

True Vs Reversed

I have plotted these on a log scale so you can get a sense of the journey – you can instantly see how simply reversing the returns changes the track of the curve. The reversed values lag behind the true values for 2/3 of the time, it lags for the first 30 odd years, catches up and then begins to lag again from the mid 1970s’. The true returns have a terminal value of $437,097.87 whereas the reversed values top out at $420,087.87. Simply changing the order costs the system $16,941.77

The same is true small changes in return – in the true return the years 1985 and 1986 were power years. They were the high point of the 1980’s bull run in terms of absolute returns with a return of 44% and 52% respectively but in looking at returns the question needs to be asked as to what the curve would look like if these were just average years of 9% return. Traders tend to spend too much time thinking about all the ways it is going to go right but very little time is spent on what could go wrong.

Expanded

The true values have the same terminal value of $437,097.87 wheres the changing of 1985/86 to average years drops the return to  $264,251.37 – a difference of $172,846.50. Whilst this does make for an interesting through experiment it also has practical implications. Trend following systems are built upon the outlier years – this is what generates their returns. If you miss these outliers then your returns over time will be ordinary. Traders do have a habit of missing these years simply because they are either caught in someone else’s narrative and miss market moves, they dont believe the move when it happens because they have a preconceived view of how much an instrument/position is worth or they are caught by the limiting belief that you can never go broke taking a profit. I lost count of people in the mid 1990’s who thought that COH was overvalued at $3.00. Granted its path to $157 has not been linear but its move to $45 was as close as you can get. This move is gone forever for such traders and will never return.

The same situation applies to the random reordering of returns. The chart below is the true returns compare to a randomly reordered sample of the same returns.

Random

The randomly reordered returns show almost a century of relative under performance including a substantial initial drawdown. So when you look at an equity dont take it as gospel, think  of the ways in which the journey could have changed with a few simple alterations or slip ups along the way. The overall aim of any form of system design is to produce a system that is incredibly robust and which shows profitability over a wide range of conditions and events.  In trading you need a little luck but you do not want to be dependent upon it.

A Man in a Hurry: Claude Shannon’s New York Years

….English philosopher George Henry Lewes once observed that “genius is rarely able to give an account of its own processes.” This seems to have been true of Shannon, who could neither explain himself to others, nor cared to. In his work life, he preferred solitude and kept his professional associations to a minimum. Robert Fano, a later collaborator of Shannon, said, “He was not someone who would listen to other people about what to work on.” One mark of this, some observed, was how few of Shannon’s papers were coauthored……

More here – IEEE Spectrum

 

Paradoxes of Probability and Other Statistical Strangeness

You don’t have to wait long to see a headline proclaiming that some food or behaviour is associated with either an increased or a decreased health risk, or often both. How can it be that seemingly rigorous scientific studies can produce opposite conclusions?

Nowadays, researchers can access a wealth of software packages that can readily analyse data and output the results of complex statistical tests. While these are powerful resources, they also open the door to people without a full statistical understanding to misunderstand some of the subtleties within a dataset and to draw wildly incorrect conclusions.

Here are a few common statistical fallacies and paradoxes and how they can lead to results that are counterintuitive and, in many cases, simply wrong.

More here – Quillette

The Reality of Statistics

I snipped this table from Business Insider – it shows the likelihood of various sorts of maladies befalling the average American. Apart from the appalling statistic for gun violence my guess is that it is roughly transferable to Australia.

threat

It highlights the profound disconnect between true risk as expressed as a number that is harsh and immutable and our perception of risk. Granted our perception of risk is amped up by Politicians who wish to distract us and news outlet who simply want to shock us. As an example here is a surprise poll you can spring on people at parties. Get them to name the most deadly animal in Australia – this is a particularly fun exercise to play with foreigners who believe that everything that walks, crawls, flies or swims in this country is out to kill them. The answer to the question is surprisingly horses between 2000 and 2010 there were 77 horse related deaths, in a distant second behind horses were cows with 33 deaths for the same period. Ask yourself the question when was the last time you heard a public service announcement warning you to be vigilant about horses – my guess is never.

The point here is our perception of risk is not the reality of risk and this is true in trading. In trading we bring a veritable cornucopia of vague ideas about risk to the table. Yet in reality none of them are real. For example I know traders who will not invest because of the coming crash – I might add this crash has apparently been coming for about a decade. Granted they might be right one day but nobody ever got rich by waiting for that one day to appear. And this is the point of the lesson, accept risk and play or dont accept risk and dont play.

The Bayesian Trap

The last two minutes is particularly useful about updating internal beliefs.

 


 

A Basic Misunderstanding

The chart below is from a site called Spurious Correlations, it takes seemingly disparate facts and matches them together to create the illusion of a positive correlation. It is a simple and effective way of illustrating the problem of mistaking causation for correlation which is constant problem in the way people both think and view data.

correlation

If you were to take this at face value you would accept that there is a link between the number of films that Nicholas Cage has appeared in and the number of people who drowned by falling into a pool. You could even stretch the data a little and suggest that these drownings were not an accident and anyone who had even seen a Nicholas Cage film would nod sagely in agreement. Now consider the chart below which looks at significant historical events and the rise of the Dow.

This rather imposing looking chart is the centrepiece of an article titled The Dow’s tumultuous 120-year history, in one chart which appears on the MarketWatch site.  The article boldly claims the following –

At its simplest, the chart proves once again that over the long term, the stock market always rises because “intelligence, creativity, and innovation always trump fear,” according to Kacher.

No it doesnt – this is mistaking causation and correlation. What the chart shows is the profound upward bias of the Dow and this is the driving force of the index moving higher. This is an example of survivor bias nothing more. The original Dow components were as follows

Dow

It is obvious that these components would change over time and that this change would drag the index higher as non performing or irrelevant issues were moved out. The notion that it is innovation that is moving the market higher is not true and can be illustrated by the simple fact that Apple arguably the most innovative technology company of recent times was only added to the index in 2015. Google whose technology permeates everyday life and Amazon who have revolutionized retailing are nowhere to be seen. The Dow has remained technology light since its inception – if technology and creativity were the drivers of the market then these new companies would be added to the index very quickly.

It is quite a simple matter to generate events stick them on a chart and say they have some significance but simply saying it doesn’t make it true. As I explored last week news and significant events tends to have a complex relationship with an index and the question of does news move markets has been answered in the negative.

The article then goes onto make the bold claim –

 Investing is more challenging than brain surgery,” Kacher told MarketWatch.

I will leave others to ponder the idiocy of this last quote.

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.

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