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A long form discussion on the history of programming for quants at the banks from SAS to Python and the rise of machine learning. While the hype of machine learning changed some of the banking modeling practices the industry kept their head straight as regulators closely watched. Now in 2026 with the AI hype wave and regulators being less strict, the banks seem lost as many are calling to replace SR 11-7 with general frameworks to reduce risk management and drive more efficiency. While this sounds good from a profit perspective, it is throwing out common definitions of models in a chase for non-sense.

Balancing the hype and trends also has been hard with the YouTube channel. It is much easier to sell snake oil as everyone wants a magical cure to profit, high salaries, minimal work, programming, math, and stats without putting in any work. I have done fairly well at sticking to creating real quant educational materials and industry perspectives even when passing up easy growth opportunities. Ten years later and we passed 100k subscribers without selling out.

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Didier Lopes studied control systems and electrical engineering in Europe before moving to the United States to build OpenBB, a next-generation financial research workspace.

Frustrated by how fragmented data, analysis, and decision-making tools were across finance and other industries, Didier set out to create a professional-grade platform where teams can bring their data, analytics, and AI into one unified environment.

Before founding OpenBB, he worked on cutting-edge technologies ranging from self-driving cars to wearable fitness devices, following a deep curiosity for complex systems and real-world impact.

In this episode, we talk about building in the age of AI, navigating life as a founder in the U.S., and the nuances of time-series modeling in financial markets.

OpenBB Examples:
https://openbb.co/solutions

OpenBB Product:
https://pro.openbb.co/

LinkedIn:
https://www.linkedin.com/in/didier-lopes/

High Growth Handbook (book recommendation - affiliate link):
https://amzn.to/4aAvbfS

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Jeffrey Rosenberg, CFA, Managing Director is a senior portfolio manager within BlackRock Systematic. He leads active and factor investments for mutual funds, institutional portfolios and ETFs within BlackRock’s Systematic Fixed Income (“SFI”) portfolio management team. In this role he serves as a member of the SFI Investment and Executive Committees and as a senior portfolio manager for several investment products including the BlackRock Systematic Multi-Strategy Fund (BIMBX), the iShares Systematic Alternatives Active ETF (IALT) and the iShares Managed Futures Active ETF (ISMF).

We talked about systematic portfolio managers compared to discretionary portfolio managers, his career and education from finance and math into computational finance at Carnegie Mellon, the changes in the market from banks to hedge funds being driven by the global financial crisis, and some book recommendations.

BlackRock Systematic Investing: https://www.blackrock.com/us/individual/investment-ideas/systematic-investing

BlackRock’s Q1 Fixed Income Outlook:
https://www.blackrock.com/us/financial-professionals/literature/market-commentary/fixed-income-market-outlook.pdf

Jeffrey Roseberg:
https://www.blackrock.com/us/individual/biographies/jeffrey-rosenberg

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Michael Jordan Pilgreen was a poetry and art major but as covid hit and the commercial art industry changed he looked for a new path. He considered financial planning but ended up learning finance and technology to become an engineer on Wall Street in the fixed income market. Now he is a co-founder of Enduring Markets which is a capital markets publication covering a range of interesting topics.

I got the privilege to advise Michael about 5 years ago during his journey on what quant finance was. Today I got to learn more in depth about fixed income from him.

Michael Jordan Pilgreen
https://www.linkedin.com/in/michael-jordan-pilgreen-7a3099108/details/experience/

Enduring Markets
https://www.enduringmarkets.org

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Interested in what quantum computing is? Ramis Movassagh explains the basics of quantum, some applications to finance, why it is a hard problem to solve, and ways to learn more about it.

Ramis is an applied mathematician and a theoretical physicist who researches quantum computation and information theory, and quantum cryptography and complexity. He does an amazing job at laying out some of the basic ideas of quantum mechanics.

Ramis' Links:

LinkedIn:
https://www.linkedin.com/in/ramis-movassagh-33465717/

Website and Blog:
https://ramismovassagh.wordpress.com/
https://ramismovassagh.wordpress.com/blog

X handle:
@Ramis_Movassagh

Quantum supremacy paper:
https://www.nature.com/articles/s41567-023-02131-2

PDF for those behind the paywall:
https://www.nature.com/articles/s41567-023-02131-2.epdf?sharing_token=oYgyql7M-nUPNwLJ4F2Q_tRgN0jAjWel9jnR3ZoTv0M5gli-apQIlZ1xThgS5KRp3t28rkad24bSeQ-gRMhmOaNP232U_FZZQjPrseDCTdXIRryTWL339snJllwZAjuD5PMkLKij96GMA_OniVnTz5JjaARH0qW5OV-AKwZr4VI%3D

Press coverage:
https://phys.org/news/2023-09-difficulty-simulating-random-quantum-circuits.html

https://communities.springernature.com/posts/the-quest-for-quantum-primacy

Quantum Merkle Trees:
https://quantum-journal.org/papers/q-2024-06-18-1380/

IBM's "Basics of Quantum Information":
https://quantum.cloud.ibm.com/learning/en/courses/basics-of-quantum-information

John Preskill from CalTech:
https://www.preskill.caltech.edu/

MIT "Quantum Computing":
https://ocw.mit.edu/courses/18-435j-quantum-computation-fall-2003/

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Diving into pure math, quantitative finance, and solving business problems with AI and LLMs. Cheikh Fall is a co-founder of Sabr Research and an MIT grad who is looking to solve many business problems with the advancements in AI. We discuss potential issues with AI, what hedge funds look for in quant researchers, and how to prepare as a student for AI.

Cheik Fall
https://www.linkedin.com/in/fallcheik/

Sabr Research
https://www.linkedin.com/company/sabr-research/


Dimitri Bianco
https://www.linkedin.com/in/dimitri-bianco/

My favorite coffee which supports the creation of these podcasts
https://volcanicacoffee.pxf.io/yq6Qj3

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I had a blast taking to Michael Watson who is the founder and CEO of Hedgineer.

"AI is the future. But not everyone is prepared for it. To effectively integrate AI into a company, it needs an organized, thorough, and secure inventory of data. Without one, every AI implementation remains incomplete because it only has access to a subset of the relevant information it needs.

Most hedge funds are built on disjointed networks of research portals, order management systems, and datasets. The ones that don't consolidate them will run the risk of falling behind the AI curve."

Michael's LinkedIn:
https://www.linkedin.com/in/michaeldavidwatson/

Hedgineer:
https://www.hedgineer.io/
https://www.youtube.com/@hedgineer
https://podcasts.apple.com/us/podcast/the-hedgineer-podcast/id1674929284
https://open.spotify.com/show/0Aq6pxdUONA4aJPntsvqf2
https://www.linkedin.com/company/hedgineer-io/

Video Version:

https://youtu.be/2hyfMMl1pGg

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Learn about financial AI expert, Igor Halperin's journey from the Soviet Union to physics and finally quantitative finance in the US. A great discussion on why many physists choose to go into quantitative finance, the positive and negative impacts of LLMs, and some perspectives on careers.

Igor Halperin:

https://www.linkedin.com/in/igor-halperin-092175a/

YouTube Version:

https://youtu.be/J7O6Scnc5NA

Igor's Textbook:

https://amzn.to/42IGAGh

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