Trading Experience For Algorithms

Trading anything over a sustained period will produce a pattern and many people have tried to capitalise on these patterns by producing algorithms that tell traders when a trade is good or bad. Most of those algorithms are based on risk and return and trades are often hedged against to further reduce risk, but in reality, no algorithm can beat good honest due diligence on any trade. The problem is that high frequency trading (HFT) is preferred by both traders and markets because of the large profits and positive-growth encouraged by large volume or regular trades. The pressure to trade will often amplify the need for some kind of algorithm.

The Need for Another Trade

Anyone who has traded forex from home using MetaTrader or some other platform will know that the very nature of forex is high frequency trading because there are charges associated with positions held overnight. While you don’t get many individuals influencing the quoted prices, trading firms using HFT strategies are much fewer in number than regular traders, but the volumes they trade are what keeps markets vibrant and they have a great deal of influence on prices. They don’t need to be market makers to influence the overall trend on an index or at least with certain trading pairs.

The Writing on the Wall Street?

The problem with many of the high frequency trades taking place every day is the very algorithms which make them profitable. Lessons have not been learned and traders and institutions are still relying on algorithms to make their decisions. When Lehman Brothers collapsed due to a belief that their risk assessment algorithm was essentially a ticket to print money, we should have all stepped back and realised the error of our ways.

Lehman Brothers algorithm had enjoyed years of success trading according to a risk assessment algorithm, but the data they used to base the algorithm was taken over a thirty period that did not include incredible lows such as the great depression. Had the data showed how markets react under extreme pressure, Lehman Brothers could still be a leading name in trading today.

Fragile Position Exposed

The actual collapse came about when Lehman Brothers bought billions of Euro bonds from struggling countries with mounting debts, such as Italy, Greece and Spain. The bonds eventually paid off, but had to be sold on long before Lehman Brothers could capitalise on them because they had held onto large positions in the sub-prime mortgage market in the United States that was proving to be a bad decision.

The overexposure in both the US and Europe was highlighted when investor confidence slipped and Lehman stock prices plummeted. Some of the world’s best traders had fallen foul to over-reliance in an algorithm that had proven successful in what was a relatively short period even though it ran into years.

A Place for Pattern Trading or Algorithmic Assessment

The fact is Lehman Brothers’ fingers were burnt by their over-reliance on a formula, but that was not the fault of the formula. Had senior Lehman Brothers representatives actually done their homework in the manner all good traders should, there’s a good chance the catastrophe would have been avoidable.

The problem many HFT traders face is a lack of time for serious diligence to take place and that is why many of the trades are hedged by going long or short in the opposite direction to the main trades of the day. However, that leaves many opportunities for problems especially when you consider most large institutions have many hundreds of positions at any one time. It all boils down to the fact that there is no quick solution to being successful at trading. It requires an in-depth understanding of the markets to see continued success.

Image courtesy of worradmu / FreeDigitalPhotos.net

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