A lot of mathematics has been applied to analysing market movements; the room for technical advantage is narrowing fast

(Last Updated On: October 6, 2011)

Outside looking in; have we got it right? Historically a lot of mathematics has been applied to analysing market movements; the room for technical advantage is narrowing fast…

External consultant view – is he right? – your views much appreciated.

‘Algorithmic trading’ covers a multitude of different activities.
Historically a lot of mathematics has been applied to analysing market movements from ‘Elliott waves’ to ‘Fibonacci series and banding’ really all as guides but none really being able to predict with any degree of certainty. So the switch was made to being able to trade either faster or with increasing volume based on the application of computer trading (HFT, LLT etc) helped by the US markets adopting a decimal dollar. Liquidity was immediately improved and because the algo volumes overall were not high percentages it all seemed to work well. Now though we have a high percentage of algo trading and it currently is mainly based on taking small increments out of market movement with very little or no view of any asset value. High volumes of these small trades seem to cancel each other out by competing with each other and the room for technical advantage is narrowing fast as we reach the limits of computer speed and latency. This competition without taking a real life view of an asset improves liquidity but appears to have an overall damping effect on value most of the time, but when a statistically significant trend makes the algo effects move in the same direction then it can make massive swings either up or down in the value of a stock because the trades are starting to work as one, possibly the cause of the 2010 market crash. Something else is happening that appears to offset this effect and that is that the financial news providers are now packaging their data in computer readable format (Bloomberg etc) to satisfy the need for algo trading to base some of their decisions on real life events (using neural nets, bayesian, genetic algorithms etc). So the latest systems take a digital news feed and run some algorithms on it to provide the decision point for the auto trading. This approach has been fuelled by diminishing returns in the purely speed related mathematical methods. The good thing about this is that it will start to reflect real life asset values again not just ‘skimming off the top’ so we should start to get more meaningful asset values being reflected. Because this approach is still a small percentage of overall algo trading I don’t believe the good market effects of this have been seen yet. Because of the limitations of computers in being able to handle large numbers of variables this approach is still in its infancy and it takes serious compute time to handle even a small number of variables. So this is where there is need for a ‘front end’ to this process that can look at huge numbers of variables in ‘real time’ and make very quick decisions. Clearly if everybody started to use this front end then the advantage would be reduced over time but the real winner will be the market because ALL decisions will be made on real life asset events so stocks should rise to their true values which is what I believe the SEC is currently concerned about. So I believe that if the SEC was able to skew the percentage ratio of pure algo trading to more real life algo trading then volatility should decrease, asset values and overall liquidity improve. D


I notice also today that the 2 trillion hedge fund industry lost 5.02% in the past 3 months alone, (Hedge Fund monitor), the worst result since the third quarter of 2008. So no matter that many ultra clever people are involved in algorithmic trading, wouldn’t their time be better spent trying to track major market shifts more correctly instead?



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