In the financial sector, everyone is looking for a new way to get ahead. Since the invention of the personal computer, and perhaps even before, large financial institutions have been using software to guide all manner of investment decisions. The turn of the century saw the rise of High Frequency Trading, or HFT, in which highly optimized bots make millions of split-second transactions a day.
Recently, [Wired] reported on Numerai — a hedge fund founded on big data and crowdsourcing principles. The basic premise is thus — Numerai takes its transaction data, encrypts it in a manner that hides its true nature from competitors but remains computable, and shares it with anyone who cares to look. Data scientists then crunch the numbers and suggest potential trading algorithms, and those whose algorithms succeed are rewarded with cold, hard Bitcoin.
The encryption, which is reported to be similar to homomorphic encryption, is necessary to protect Numerai’s proprietary secrets. While it slows down computation, it does allow the company to more comfortably farm out its algorithm development to the wider public. Machine learning algorithms are used to determine which trades to make, and under which conditions. This isn’t the first time machine learning has been used in the financial sector, but it is interesting to see it applied in a crowdsourcing context. This allows the company to pick the best algorithms submitted by a wide base of coders, rather than relying on a handful of talented hires. Numerai is then perhaps most interesting for its hiring strategy, rather than doing anything particularly groundbreaking in a technical sense.
The fund has been trading for a year, and the founder, [Richard Craib], claims it is turning a profit. Investors are flocking to the company, which has recently completed a multi-million dollar funding round. The article sums things up rather well, however:
The company comes across as some sort of Silicon Valley gag: a tiny startup that seeks to reinvent the financial industry through artificial intelligence, encryption, crowdsourcing, and bitcoin. All that’s missing is the virtual reality.
Like it or not, machine learning is here to stay. If, like this writer, you could use some help getting to grips with it all, check out our machine learning primer.