In the 6th episode of the Hedgineer podcast, Thomas Li, co-founder of Daloopa, delves into the crucial role of precise historical financial data in fundamental investing. The discussion highlights a significant problem faced by financial analysts: the painstaking, time-consuming task of data extraction and management of financial models in Excel. As Michael and Thomas have both experienced first hand this is no easy task, but Daloopa aims to address this issue (and pretty much as solved it) by providing a comprehensive, single-source database for historical fundamentals, ensuring high quality and precise data for fundamental equity investors. This innovation is a game-changer for hedge funds and asset managers, offering them a more efficient and reliable resource for fundamental investing.The conversation moves towards the unique approach Thomas and team take to structuring financial data. The focus is placed on presenting data exactly as the company reports it, ensuring accuracy over taxonomy in their data model. Thomas also discusses how with the help of machine learning and AI models, the company navigates the complexities of KPIs and adjustments, acting as a 'perfect messenger' of publicly available data.This is a great episode for financial analyst, hedge fund engineers, entrepreneurship, and anyone interested in learning about a core problems for a fundamental investor. Hosted on Acast. See acast.com/privacy for more information.

When it comes to using technology to be at the cutting edge, the quality of the data you are using is the name of the game. In trading that some times means spending tens or even hundreds of millions of dollars for data that gives you insight into the world that very few have. In this episode we bring on Rich Brown who has lead data and sourcing teams at some of the most successful and well hedge funds in the world to shed to light on this industry.We talk about the different ways that data is used for discretionary and systematic managers. This can include everything from real time exchange feeds, data from bbg terminals, to the most exotic data you could image. We touch on how some alternative data is used to forecast not just price action but more fundamental performance of KPIs that a separate process may then use to forecast future returns. We also discuss how to think about licensing data to train LLMs where the licensed data my be embedded in the model weights but not easily traced back to the original source. Rich points out that some of this is new but mostly already solved problems, at least contractually, where the products are conscidered derived work products and are likely covered depending on the licensing model used. There is a wealth of insight and we hope that you enjoy this episode as much as we did in creating it. Hosted on Acast. See acast.com/privacy for more information.

In episode 4, Michael invites Sachin Kullkarni on to discuss alterative data and AI. Sachin is currently head of data science at a multi billion dollar credit hedge fund, and previously was at Point72 as a Sector Data Analyst (SDA) in health care. They discuss how alternative data is used in large hedge funds and how they see the space evolving with Generative AI and Large Language Models (LLMs). They also look back on the alternative data space and how it has evolved over the past 10 years. Michael and Sachin discuss some of his favorite tools and how they are used including Snowflake, Airflow, Jupyter and Materalize. Then they discuss how they see this landscape evolving over the course of the next couple years as LLMs start to disrupt the space. Hosted on Acast. See acast.com/privacy for more information.

In the third episode of The Hedgineer Podcast, Michael invites equities quant researcher and commodities analyst Lucas (Hog) Rooney to talk about how AI and software engineering can be leveraged for hedge fund investors. In the same way that Python has been a force multiplying tool for Lucas as an investor, LLMs like LLaMa and GPT could be even more impactful for an investor's ability to synthesize information. We talk through how software engineering is developed for fin, how to bridge LLMs into a research process, and what the future may look like. We also go a bit off the beaten path into the back woods of the Pacific Northwest where Lucas guided expeditions into the great unknown. This is a fun episode because of Lucas's unique journey to end up where he is today. He is a blast to chat with and we hope you enjoy the episode. You can find more about the engineer in all of your favorite apps below:Slack: https://hedgineer.slack.com/Instagram: https://www.instagram.com/hedgineer/Twitter: https://twitter.com/hedgineeringLinkedIn: https://www.linkedin.com/company/hedg...TikTok: https://www.tiktok.com/@hedgineer Hosted on Acast. See acast.com/privacy for more information.

In this episode of the Hedgineer Podcast, Neel Somani, joins us to discuss his journey from being a software engineer and quantitative researcher for Citadel Commodities to a CEO and founder of Eclipse. We talk about how he was able to pivot after the collapse of Terra Luna and raise $15,000,000 to build out a blockchain as a service protocol that leverages the power of ZK rollups.Careers:Neel talks us through the transition from a software engineer at AirBnB, to a financial engineer and quantitative researcher at Citadel, then lastly as a founder. Later in the episode he talks about similarities and differences for engineers that decide to work on blockchain projects and how the motivations are similar to financial engineering because it interweaves economics and computer science.Finance:He was quick to point out that he now spends very little time writing code, although is still involved in all architecture discussions. One area he spends more time on is business development. He provides insight into the similarities between BD in crypto vs non-crypto companies. We discuss that, similar to equities, the KPIs to focus on for BD, are protocol/sector specific. As Neel points out, for protocols like Eclipse you would look at transaction count, but for something like Gnosis, you look at TVL. We also compare crypto to commodities and get Neel's take on how best to compare the two, and Michael even highlights the comparisons to nation state currencies.TechNeel gives a brief overview of ZK roll-ups and how they provide cryptographic proof of the operations that have been executed to provide the current state of the network. We also touch on the tech stack similarities and differences between financial engineering vs block chain engineering, where the language level differences are pretty minimal if working in Rust. Neel also highlights the importance of Computer Science fundamentals that are especially true when designing an L1.Hedgineer = Hedge Fund + EngineerLearn more at https://hedgineer.io or follow us on YouTube, TikTok, Instagram, or Twitter. Hosted on Acast. See acast.com/privacy for more information.

In this episode former SpaceX and Citadel software engineer joins us to discuss his experience joining SpaceX out of college to help on the mission of sending mankind to Mars. After writing software for multiple launches, he made a big career decisions to move from LA to New York and work for Citadel, a major hedge fund. There aren't many people who can compare these two incredible organizations, but Brian is one of them.Brian and Michael go back and forth talking about their careers and provide unique insight into the career development of engineers behind these major alternative asset managers. And in case you were curious...Hedgineer = Hedge Fund + Engineer Hosted on Acast. See acast.com/privacy for more information.