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THE DISMAL SCIENCE REMAINS DISMAL

WHEN HRISTOS DOUCOULIAGOS was a young economist in the mid-1990s, he got interested in all the ways economics was wrong about itself—bias, underpowered research, statistical shenanigans. Nobody wanted to hear it. “I’d go to seminars and people would say, ‘You’ll never get this published,’” Doucouliagos, now at Deakin University in Australia, says. “They’d say, ‘this is bordering on libel.’”

Now, though? “The norms have changed,” Doucouliagos says. “People are interested in this, and interested in the science.” He should know—he’s one of the reasons why. In the October issue of the prestigious Economic Journal, a paper he co-authored is the centerpiece among a half-dozen papers on the topic of economics’ own private replication crisis, a variation of the one hitting disciplines from psychology to chemistry to neuroscience.

More here – Wired

How to beat the bookies by turning their odds against them

Mathematicians had already developed bookie-beating models that attempt to predict sporting outcomes, but they are hard to devise and don’t perform consistently. So Lisandro Kaunitz at the University of Tokyo and his colleagues tried a more direct approach: using the bookmakers’ odds against them.

The team studied data on nearly half a million football matches and the associated odds offered by 32 bookmakers between January 2005 and June 2015. For every game, the trio looked for odds that might yield a better return than the average offered by bookies – say, 5 to 1 versus a mean of 2 to 1.

Mean odds of 2 to 1 suggest the bookies collectively think this reflects fair odds for that outcome. But 5 to 1 offers higher returns should the outcome materialise. The team used the historical data to work out the optimal distance from the mean odds – the one that would give a positive payout for the largest number of games.

In a simulation, their strategy made a return of 3.5 per cent – beating random bets, which resulted in a loss of 3.32 per cent.

So the trio decided to try it in the real world. They developed an online tool to apply their odds-averaging formula to upcoming football matches. For five months, they placed $50 bets around 30 times a week.

It worked. The team made a profit of $957.50, or an 8.5 per cent return (arxiv.org/abs/1710.02824).

More here – New Scientist

The Ways We Con Ourselves

I support a particular hospital charity that each year or so runs a home lottery and every year I enter. To date I have won a digital camera, an iPod, an Apple TV, a tonne of chocolate, wine (brilliant for a non drinker but good for presents) and a host of other goodies. In fact I have never had a time when I have entered and not won something. Whilst my expectancy is not quite positive its not bad. If I were a newsagency that sold lottery tickets and I had this many winning entries bought via my store people would be clambering over me thinking there was something special about my store. One of the things we ignore in life is that we are subject to the same harsh statistics as everyone else – we have what I call the myth of individual specialness. Our basic narcisssim leads us to believe that the laws that apply to the universe don’t really apply to us, as a result we spend a lot of time fooling ourselves into think there is something special or magical about what we do.

My capacity to win this particular lottery has nothing to do with me other than the fact that I enter, I am simply subject to the laws of large numbers as is everyone else. If you get enough people doing the same thing over a long period time then the probable drifts into the realm of the inevitable. It is no wonder some people win the lottery twice. But because we are such poor natural statisticians this seems like magic to us and we ascribe some special quality to ourselves and this is apparently a well known phenomena in both lottery winners and those who have inherited wealth. They believe that something divine about themselves means that they were meant to win – they cannot accept that it was blind luck. My wife has a friend who received a very large inheritance from her parents, she has now divorced herself from all her friends of many decades because she believes that there is something superior about herself other than being the lucky  product of the sperm sprint derby that we all undergo. Sometimes you land in the right spot and sometimes you dont.

The central issue here is that even in trading we are subject to the ruthlessness of statistics and this ruthlessness is often at odds with our own emotional endurance. For example if you have a system with a positive expectancy this means that on average and over time your system will make money. But note there are two presumptive phrases involved in this definition – on average and over time. You need to have the resilience to ride out the times when the system is not making money. When traders first encounter the notion of expectancy they assume that is means that every trade they take will make $X and are surprised when this does not happen. All trading systems will experience runs of losses, this is the natural order of things and you can experiment with this for yourself by looking at a coin toss simulator. If you click here you can see how streaks of either heads or tails form – this is a good example of what can happen in trading systems.

Despite trading being a basic exercise in statistics at its core it is an exercise in resilience because we have to find ways of dealing with brutality of statistics and even when we know our system is sound it is still hard to take a continual series of losses. Inevitably we come back to the notion of courage as a central tenet in the success of any trader.

Gamblers, Scientists and the Mysterious Hot Hand

IN the opening act of Tom Stoppard’s play “Rosencrantz and Guildenstern Are Dead,” the two characters are passing the time by betting on the outcome of a coin toss. Guildenstern retrieves a gold piece from his bag and flips it in the air. “Heads,” Rosencrantz announces as he adds the coin to his growing collection.

Guil, as he’s called for short, flips another coin. Heads. And another. Heads again. Seventy-seven heads later, as his satchel becomes emptier and emptier, he wonders: Has there been a breakdown in the laws of probability? Are supernatural forces intervening? Have he and his friend become stuck in time, reliving the same random coin flip again and again?

Eighty-five heads, 89… Surely his losing streak is about to end.

Psychologists who study how the human mind responds to randomness call this the gambler’s fallacy — the belief that on some cosmic plane a run of bad luck creates an imbalance that must ultimately be corrected, a pressure that must be relieved. After several bad rolls, surely the dice are primed to land in a more advantageous way.

The opposite of that is the hot-hand fallacy — the belief that winning streaks, whether in basketball or coin tossing, have a tendency to continue, as if propelled by their own momentum. Both misconceptions are reflections of the brain’s wired-in rejection of the power that randomness holds over our lives. Look deep enough, we instinctively believe, and we may uncover a hidden order.

More here – The New York Times

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

General Advice Warning

The Trading Game Pty Ltd (ACN: 099 576 253) is an AFSL holder (Licence no: 468163). This information is correct at the time of publishing and may not be reproduced without formal permission. It is of a general nature and does not take into account your objectives, financial situation or needs. Before acting on any of the information you should consider its appropriateness, having regard to your own objectives, financial situation and needs.