In March of 2017, efinancialcareers published an article that spoke to something we know well, that survival for fundamental investors, in a world that is being re-shaped by technology and big data, means embracing and including data science within the fundamental investment process. But this is not an easy marriage, no matter how much it makes sense. Having been on the buyside as a fundamental investor for over 25 years, these two disciplines, quantitative and fundamental analysis, have mostly lived in different neighborhoods, each thinking theirs was the better one. At EDS, this was our challenge, and one we started in 2013 - However, as with many paradigm shifts, we found the tools of the past don’t help solve the challenges of the future, as we can see from these quotes from the article: Why hedge funds don’t have a clue about how to use their quants, AI experts and data scientists:
“hire data scientists and quantitative researchers to look for alpha opportunities and basically hand over an Excel spreadsheet to the portfolio manager who has no idea what to do with it,”
“You have portfolio managers with decades of experience attending courses in Python and R, or learning how to build a factor model,”
“The truth of the matter about the quant versus fundamental debate is no one has figured out not only how to use data science to gain an insight, but how to turn that insight into action,”
Excel, Bloomberg, and other current platforms were never meant to provide fundamental analytics and manipulation on the scale of Big Data. They were also never meant to provide deep, actionable insights. They were meant, and are still meant, as a general platform to deliver information, such as news, quotes, research and basic fundamental metrics. Incorporation of data science and the insights it delivers requires a new approach, which is why, until now, it has been incredibly expensive and resource intensive to implement, support and evolve.
The last two quotes speak to the language of data science. Until the EDS platform, quantitative data was presented to investors from in-house quants and data scientists, in an “excel-driven” process, that left huge “insight” gaps. It should come as no surprise that data scientists and fundamental investors speak entirely different languages, with the only common grounds being excel, so it makes sense that turning that spreadsheet or bloomberg report into insight and action has been difficult - Excel was never meant to provide deep, visual and actionable insights.
At EDS, we set out to embrace new technology, such as the cloud and visualization, to deliver a next generation platform, so that investors can leverage the benefits of data science to make better and more informed decisions, without having to resort to using old and unproductive tools.
We were lucky to work with some of the worlds smartest investors, over the past four years to develop a quantitative engine for fundamental investors that scales across the global equity universe and virtually any dataset. The EDS Quantitative Engine doesn’t use Excel, it is a dynamic, database driven engine, that places the power directly into the hands of investors - giving them (for the first time) the opportunity to manipulate and interact with fundamental data, at scale, and in ways they’ve never been able to do on their own.
We’ve also made it simple to use, by encasing this engine in a visualization layer that provides deep insights, is aligned with investment workflows, and seamlessly incorporates the main constructs of a predictive, data-driven framework.
And lastly, because we’ve spent the last four years developing this platform, and it's delivered through the cloud, we are able to deliver it at a price point and resource commitment level that is a fraction of competing solutions, making it truly disruptive as well.
No need to learn to program, no need to hire expensive data scientists, and best of all, customers have been using it for years, providing alpha and actionable insight through data science.
Equity Data Science has become an integral part of our daily investment process. No question. It’s helped us create increased alpha and stronger discipline.” — Steve Galbraith, Kindred Capital