What Do You Call Fundamental Investors Who Leverage Quantitative Research
Why a Quantitative Framework is so Important
In today’s hyper-connected, complex markets, integrating a wide variety and volume of information is critical to making sound investment decisions. Sources of predictive data are multiplying exponentially, and over 70% of market volumes are quantitatively driven.
A few questions that are answered in seconds, within a Quantitative Framework
Which stocks, sectors, styles, regions are discounting lower profitability or growth compared to history? Are these assumptions reasonable in the current environment, given revisions, and expectations?
Am I being paid for taking systematic and thematic risk?
Are the under/over valuations a symptom of the style/industry/region being out of favor or are their systemic issues at work?
For companies where there is skepticism built in (discounting slower growth), are the stocks inherently cheap vs. all stocks or just versus history?
Where am I taking the bulk of the portfolio systematic risk?
What systematic characteristics are being rewarded by the market?
They’re painful and time consuming to use for deep analytics.
Can’t scale efficiently across the entire investable universe
Have limited statistical capabilities
Aren’t designed to streamline and automate the analytics process
The Market is Not Waiting for "traditional tools" to catch up, they are Building their Own
Traditional tools aren’t up to the challenge:
This is Why we Created Equity Data Science:
We are your “In-House" data-scientist, providing all of the benefits of an in-house solution at a fraction of the cost. We provide sophisticated investment research and portfolio management tools that are easy-to-use, provide actionable insights and information and saves you time. Delivered as a service (no lengthy installation or IT support), its easy to use, provides greater functionality than current platforms, and is super affordable, requiring a fraction of the investment in infrastructure and people.
How a Quantitative Overlay helps
There are many benefits to using a quantitative framework within your investment process, but one of the most important is the enhancement of the inputs into your investment methodology. As the saying goes, Garbage In, Garbage Out (GIGO). At EDS, we are committed to improving your process (getting rid of the garbage), right from the beginning!
Data Science at Work Within the
Top of the Funnel
This is where ideas are filtered by investment philosophy (value, growth, large, small cap, etc.) for actionable insights. A quantitative layer increases idea flow, as well as precisely filtering the ideas that make it into the funnel.
Inside the Funnel
Not all ideas that make it into the funnel, end up in the portfolio. This is where the hard fundamental work takes place. A quantitative layer helps increase efficiency by automating and streamlining many of the repeatable workflows during this process. A quantitative layer also dramatically increases the number of companies that can be analyzed.
Since higher quality names come into the funnel, and a disciplined process was used inside the funnel, the output is enhanced. A quantitative layer, at the portfolio level enhances risk management, by precisely identifying exposure to specific segments and factors of risk in the market. By understanding this detailed level of risk, managers can quickly make needed adjustments.