So much has been written lately about the integration of Quantitative Investing and Machine Learning. Are you wondering about whether to apply ML to your investment process or feel like your team isn’t progressing fast enough? We hope that our new blog series on...
ChatGPT’s SQL Translation: Pros, Cons & Room for Improvement
At Scientific Financial Systems, we have mapped a lot of vendor data into Quotient – mostly from MS SQL Server databases. With the ever-growing popularity of Snowflake, vendors are releasing versions of their data products on this highly scalable, performant, and...
Why Should We Consider the Use of Machine Learning in Quantitative Finance?
During our time in Quant Finance, regression analysis was generally the best tool we had for determining the effectiveness of factors and models. We at SFS, we were especially comfortable performing regressions when the relationship between our variables was clearly...
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SFS AND Refinitiv: Spend more time on research and developing models with read-to-use data and Python-based factor construction. No SQL coding required
SFS is excited to announce that it has partnered with Refinitiv, the global provider of financial market data and infrastructure.
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