Deep learning and big data: Wall Street and the new data paradigm

Wall Street is big business, and it is about to become even bigger with the rise of big data. It is every investor's dream to have prior knowledge of the direction of the market before it happens, which is why financial investment firms are driven to mine for data rather than for gold in the information economy. Traditionally, investors have based their decisions on fundamentals, intuition, and analysis drawn from traditional data sources, such as quarterly earnings reports, financial statement filings to the U.S. Securities and Exchange Commission (SEC), historical market data, institutional research reports and sometimes the so-called "expert networks." The new data-driven paradigm, fueled by new alternative data sources, high performance computing and predictive analytics, offers a more robust framework to generate data-driven investment theses. Data – from satellite images of areas of interest, automated drones, people-counting sensors, container ships' positions, credit card transactional data, jobs and layoffs reports, cell phones, social media, news articles, tweets, online search queries – is now the most valuable commodity for Wall Street.