Thursday, July 21, 2016

Deep Learning, TensorFlow and Hedge Funds

Deep Learning is in these days. It really looks like late 19th century electricity gold rush deja vu, with industry, academia, as well as regular businesses all jumping in.
Some hedge funds are already heavyweight users of computer power and models ( systematic funds like Renaissance, Two Sigma etc. ).

The complexity and size of modern, globalized markets mandates usage of more advanced, automated data analysis methods. There are already indications ( visible if we observe how hedge funds fared  during Brexit turmoil, for example) that systematic funds stand better fighting chance in today's turbo markets.

The promise of Deep Learning is that critical mass of data and bigger neural networks ( more layers, more computing power ) mean qualitative change and that a new level of modeling accuracy is  achievable. General Deep Learning algorithms can be applied to domain specific use cases, relying primarily on massive amounts of data as the fuel for insights ( rather than the particular domain knowledge i.e. coming up with clever domain specific algorithms ).

Google's TensorFlow is recently open sourced library that runs on heterogeneous ( CPU, GPU, FPGA ), distributed platforms. It can be ( and already is ) used for financial markets modeling. If history is any guide, TensorFlow will ignite a whole new industry and many products will have it as architectural foundation.

TensorFlow makes it easy to perform complex analysis ( flexibly apply Deep Learning algorithms ) to multi dimensional data ( tensors ) and come up with relatively reliable predictions on where market will be based on earlier closed markets, for example. Naturally many other ideas and hypothesis can be tested ( models can be trained and executed-interferred) with great ease  - and that is probably one of the most important TensorFlow advantages.

Since hedge funds deal with publicly available data sets then cloud infrastructure ( AWS, Google Cloud ) can be utilized to essentially rent a supercomputer and perform massive calculations on the cheap. TensorFlow can light up such virtual supercomputer with just a few  lines of code.