Spending time amongst Quants, dubbed by Investopedia as “The Rocket Scientists of Wall Street,” has been a fascinating experience for me. Quants’ skills are formidable, their pedigrees impressive – they speak in technical languages I am still only beginning to understand. Over the years, I have had the great fortune to watch Quants become increasingly central to institutions’ investment management processes.
Although Quants now have an incredible amount of power and visibility in the investment world, their mission has become infinitely more competitive and complex. In the past, many Quants built things in house because they had no choice, and they could stand out by building tools that other shops didn’t have. Now, however, Quant leaders are moving beyond building tools and into using the tools creatively (like AI). In short, Quants today need to be much much more than just technologists.
At Scientific Financial Systems (SFS), we are always on the lookout for ways that we can assist Quants in their formidable mission, and my role is to connect the Quant marketplace to the solutions SFS has created. These days, Quants are more and more deluged by information overload, and they need more tools to help manage the enormous flow of data. When I ask customers about their biggest “pain points” that we can help with, routinely I hear “freedom from data headaches” and “relief from operational complexities.”
The good news is that data science has given Quants many new and powerful tools. The Quants’ mission is to apply these tools creatively to uncover new perspectives and insights buried within the data. In this way, Quants of the future need to be more artists than technologists.
This fact was highlighted in James Williams’ recent Hedgeweek article “Quant funds still lack one human power…imagination.” In the article, Williams interviews Michael Weinberg, who is a thought leader in the Quant investment space. Weinberg identifies Autonomous Learning Investment Strategies (ALIS) as a new frontier in Quant finance. As stated in the article, ALI Strategies “combine big data, data science and machine learning techniques, which, coupled with ever more powerful and cheaper computing power and storage, are pushing the envelope in terms of what is possible in quant trading.”
These strategies, according to Weinberg, continue to evolve. As he notes, “The same trends do not persist. In our view, in the future managers who use alternative data will be able to systematically do what managers have historically done on a discretionary basis, and more efficiently.”
Scientific Financial is dedicated to contribute to this evolution and foster new domains in Quantitative investment management. I’m excited to be on this journey of technological enlightenment. More to come.
https://www.investopedia.com/articles/financialcareers/08/quants-quantitative-analyst.asp
https://www.hedgeweek.com/2021/04/12/298489/quant-funds-still-lack-one-human-powerimagination