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It All Started with a Quble

It All Started with a Quble

In our last SFS blog, we talked about how the technical challenges in the performance and scaling of our Quotient architecture were solved through the integration of our backend with Snowflake’s Snowpark for Python. We called Snowpark a “game changer” for developers...

Houston, We Had a Problem

Houston, We Had a Problem

Scientific Financial Systems (SFS) knew that in Quotient™ we developed a powerful and flexible Python-based data science SaaS application that could improve the effectiveness of quant finance teams.  Our careers in Quant research and fund management led us to...

Transitioning to Quotient™

Transitioning to Quotient™

In our last blog, George Kastner detailed how changing business processes or systems can be complex but also can be rewarding.

Quotient™ Business Value Proposition

Quotient™ Business Value Proposition

Our flagship product, Quotient™, provides modern, efficient, and powerful analysis combined with simplified access to a wide array of financial content.

Displaying SQL Code That Defines Data Item’s Retrieval

Displaying SQL Code That Defines Data Item’s Retrieval

In our recent blog “Intro to Qubles,” we discussed how Quotient leverages the respective strengths of Python and SQL to create a proprietary Python data container class that we call “Qubles.” For sourced data, we display the Python and SQL code that drive that the...

Quotient™ Makes Factor Construction Transparent

Quotient™ Makes Factor Construction Transparent

Quotient makes factor construction transparent through what we call the “lineage” functionality. With the lineage functionality, users can specify the raw data item components of a derived data item to be returned along with the computation of a derived data item....

Making Factor Construction Simple with Quotient™

Making Factor Construction Simple with Quotient™

Factors are the key driver for active quantitative investment research.  Factors are derived data items.  The raw data item used to generate factors can be technical price and trading volume data, and fundamental data including financial statements and...

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