The Alternative Data revolution on Wall St
Submitted by Gene Ekster (@geneman) on Monday, 11 July 2016
This talk will focus on the role that non-traditional data research, known as alternative data, is beginning to play across the investment community. We will address how datasets such as point of sale transactions, web site usage, municipality records, social media data and similar information are being utilized by traditional long-short funds, quantitative hedge funds and also mutual funds.
Topics covered will include aspects of the developing alternative data ecosystem including:
- Alternative data R&D process flow
- Computing infrastructure and the technology stack
- Research & analytics providers
- Technical solutions to common issues found in alt. data
- Best practices
We’re going to walk through a few examples of how noisy, unstructured data become an investable signal using tools such as text mining and machine learning. The aim is to introduce the audience to the process of how hedge fund portfolio managers and sell-side research analysts are systematically generating returns by leveraging unique primary (bots / scrapers, channel checks) and third party datasets (including data brokers). This includes sourcing, compliance, scrubbing out PII, alpha generation related to revenue estimates and approaches to balance the secret sauce with product transparency. Finally, we’ll ponder the future of alternative data in finance and touch on how companies in the data space can best take advantage of this growing trend.
Gene Ekster was previously head of R&D at Point72 Asset Management (formerly SAC Capital), a Director of Data Product at 1010Data and a Senior Analyst at Majestic Research (now ITG Investment Research). Currently, Gene works with asset management firms and data providers in a consulting capacity to help integrate alternative data into the investment process. He can be reached via LinkedIn (https://www.linkedin.com/in/geneekster).