Ever since the release of Flash Boys by Michael Lewis, the interest in algorithmic trading has gone up another notch. But there is good reason for this because algorithms really are taking over the world and taking over Wall Street in particular.
Src: Perpetual Tourist
Most people talk of algorithmic trading and automatically think of HFT (High Frequency Trading), however, the two are not always the same and algorithmic trading can occur on much longer time frames if so desired.
How dominant is algorithmic trading?
One interesting fact about algorithmic trading and HFT especially is that not everyone is sure how prevalent it really is in today’s markets.
Some claim that only 50% of trading volume can be attributed to HFT, which would be 20% less than in 2009. Others claim the figure is closer to 75%.
But the really interesting fact is that while 50% – 75% of trading volume can be attributed to algorithmic trading, around 90-95% of all quotes on the market are from algorithms.
In other words, HFT orders are everywhere but those orders don’t always execute.
Why could this be?
The reason for this is that algorithms are constantly working out ways in which to profit from the markets. Some times the algorithms move in above or below the price in order to influence the direction of the market.
This is a game of speed where the quickest algorithm is able to jump in front of all the others and make the trade. If the algorithm gets in first it makes the trade and wins. If it doesn’t, it misses out and some other algo trade makes the profit.
The result of this is that algorithms constantly compete with each other on speed and the businesses in charge of setting the algos up invest heavily in getting lightning quick connections to the exchange, utilising underwater fibre optic cables and that kind of thing.
I recommend taking 20 minutes to watch the following TEDx talk on algorithmic trading. Sean Gourley is a New Zealander who has spent a lot of time figuring out how algorithmic trading works and claims that we don’t really understand many of the things that these algorithms do.
Most interesting in this is Gourley’s discussion of augmented intelligence.
Sean talks about a chess tournament a few years ago where some of the most powerful computers in the world were pitted against some of the best human players.
While the computers were easily capable of beating the grand masters on their own, it was when humans teamed up with ordinary computers, that they were able to defeat the super computers consistently. Indeed, it seems that a reasonable group of players using an average desktop computer were able to defeat the super computers.
This gives rise to the notion that the future for us all is to work in conjunction with the machine in order to rise above the competition.
I suppose we knew this already. But this is more evidence to get creative with the process.