How Wall Street is making Billions from Machine Learning
What if I tell you that what you are learning right now can make you millions or even billions? What if I tell you that this is not a fantasy, but it is happening right now? As computation becomes cheaper and more abundant, more and more innovative trading firms are seeking new ways to profit from this idea: one of which being machine learning. The stock market is thought to be unpredictable; David Siegel wants to shatter this notion. Mr. Siegel is the founder of Two Sigma and he describes the patterns of the stock for Apple Inc. is based off everything from sales to earthquakes. The seemly inauspicious things affecting stock prices, Mr. Siegel incorporated all these possible data into his stock analysis. But he is not the only one in this pursuit, as companies like DE Shaw and Renaissance Technology look to take advantage of these concepts to seek patterns in the sea of information.
The surge of interest in machine learning is growing in the recent years. Evidenced by the growing numbers of hedge funds sponsoring NIPS, a conference which is at the forefront of machine learning and artificial intelligence research. Braxton McKee, the founder of Ufora: an open source python-based platform for data analysis and machine learning algorithm, shows that the innovation in cloud computing which leverages data storage and computational resources allows easier access to utilizing machine learning algorithms. From the availability of the resources to the reduction in computational cost, venture capital grew 20-folds for AI-related start-ups from 2011 to 2014. The trending desire for programming with a background in machine learning and big data analysis has propelled Data Scientist, one of the newest job titles, to become the best-ranked job of 2016 according to GlassDoor.
One company who is at the forefront of AI and Machine Learning at Wall Street is called Two Sigma. Their approach to data analysis incorporates every possible data points such as newswires, earning reports, weather forecast, and Tweets from Twitter to predict which stock would generate the best returns. According to Wall Street Journal, they describe their process as follows: They first devised dozens of computer trading models related to stocks. One example would be using Twitter and market research to examine the public perception of a company. Then they use an algorithm to check stock patterns of such company like the 200-day averages or the buy or sell patterns of the company executives. Each model they devise will make a trade suggestion and the suggestion will be weighted according to the past performances of the model. The best-weighted suggestion will be analyzed for risks and if it passes any given criteria set by Two Sigma; a buy order will be executed.
This is not the only way hedge funds have been using machine learning to find trade patterns. Companies such as Carmot Capital uses machine learning to detect liquidation patterns before the information make it to the general public. The speed of machine analysis and computation allows companies to outpace traditional human analysis and earn millions before such vital information spreads to the average investor. As more and more hedge funds seek machine-learning experts to aid their analysis, a lot of money will be put towards AI-related research. Although these companies do not contribute to the society instead move money from hand to hand, in my opinion, their investment into the field of machine learning will help greatly our understanding of computer and humans. However, do you believe that this will benefit machine-learning research or corrupt it?
Sources
Hope, Bradley. “How Computers Trawl a Sea of Data for Stock Picks.” WSJ. The Wall Street Journal, 1 Apr. 2015. Web. 16 Feb. 2016. <http://www.wsj.com/articles/how-computers-trawl-a-sea-of-data-for-stock-picks-1427941801>.
Sokoloff, George. “Is There Any Hedge Fund Using Machine Learning Based Algorithms for Trading?” Quora. N.p., 31 Oct. 2015. Web. 16 Feb. 2016. <https://www.quora.com/Is-there-any-hedge-fund-using-Machine-learning-based-algorithms-for-trading/answer/George-Sokoloff>.
“25 Best Jobs in America.” Glassdoor. N.p., n.d. Web. 16 Feb. 2016. <https://www.glassdoor.com/Best-Jobs-in-America-LST_KQ0,20.htm>.
Bit, Kelly. “The $10 Hedge Fund Supercomputer That’s Sweeping Wall Street.” Bloomberg.com. Bloomberg, 20 May 2015. Web. 16 Feb. 2016. <http://www.bloomberg.com/news/articles/2015-05-20/the-10-hedge-fund-supercomputer-that-s-sweeping-wall-street>.
