Deep Learning Could Replace High Frequency Trading

Deep Learning

High Frequency Trading (HFT) is NOT the most popular or embraced program by many traders and money managers. But hey, its here and hard to fight. But now, those flash order folks may have a significant threat to their “gold mine” (or cryptocurrency mine). Deep learning may topple HFT. This is very interesting and is going to be fun to watch how it shakes out.
(Bill Taylor/ CEO)

“Deep learning just may be poised to shake investment strategies based on alpha capture to their knees, according to some experts.

The machine learning sub-discipline is setting itself up to displace high-frequency trading which has dominated many of the electronically traded markets since approximately 2007.

Similar to high-frequency trading, deep learning-based strategies do not approach a trade with a preconceived hypothesis but examines the data for useful information it might contain, explained Gaurav Chakravorty, chief investment officer of online asset manager qplum and who spoke during a webinar hosted by Quantitative Brokers.

“It is the first machine learning algorithm that tries to remove noise from the data before it starts predicting,” he added.

 Deep learning does this by using “layers” to summarize the content of the previous layers until a few summaries can describe all of the original data. Chakravorty cited an example where an initial layer was composed of 5,000 distinct pieces, and each subsequent layer reduced the amount of data by a third until the model had five summaries in the end.

“The deeper that you go, the literally more intelligence that you get,” he said.

However, Chakravorty has never worked on a network that processed more than ten layers because of the cost it would take to build something larger. In comparison, experts estimated that the deepest network in the human mind is 4 million layers deep, he added…”

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