In our latest episode of The Stream, we had the privilege of hosting one of our newer hedge fund managers featured on Agora who has pioneered a “quantamental” approach to commodity derivatives trading. With nearly two decades of cross-asset investment experience, our guest shared insights into how modern trading strategies are evolving at the intersection of quantitative analysis and fundamental research.
Key highlights from the discussion included:
- An in-depth exploration of how combining data-intensive analytics with traditional market intelligence networks can create a competitive edge in commodity markets
- A fascinating debate on the relevance of the “commodities supercycle” concept as we look toward 2025 and beyond
- Critical analysis of energy demand projections, particularly examining how technological advancements like AI and data centers are reshaping traditional consumption patterns
- Practical insights into building and maintaining diverse, high-performing investment teams in today’s competitive landscape
The conversation revealed several compelling insights about the future of commodity trading. Our guest challenged conventional wisdom about the “physical connection” advantage in commodity markets, offering a nuanced perspective on when and how this edge truly matters. The discussion also touched on innovative approaches to team building, emphasizing the importance of cognitive diversity and complementary skill sets in modern investment teams.
Of particular interest was the analysis of how technological evolution might impact energy markets. The conversation explored how innovations like on-device AI processing could potentially reshape traditional energy demand forecasts, offering valuable insights for investors positioning themselves for the future of commodity markets.
The session also included practical advice for aspiring fund managers, touching on essential leadership qualities, risk management strategies, and the importance of maintaining a learning mindset in an ever-evolving market landscape.
For those seeking to understand and navigate the complexities of today’s commodity markets, this webinar should be worthy of your time. Want to dive deeper into these topics? Accredited institutional investors can now watch the replay on demand. Click the button below to head to Agora and access the full replay.
Watch our latest episode of The Stream
About the Guest
A distinguished investment professional with over 18 years of cross-asset experience, spanning derivatives trading, structured products, and innovative quantitative strategies. After beginning her career at a major European investment bank, she transitioned to commodity trading, where she developed a unique “quantamental” approach combining systematic analysis with fundamental research. Her expertise encompasses interest rates modeling, AI applications in finance, and Big Data analytics.
Having held senior positions at leading financial institutions in London and Switzerland, she now leads a commodity-focused investment strategy that bridges traditional market intelligence with cutting-edge quantitative methods. Her approach has garnered attention for successfully navigating complex market cycles while maintaining consistent risk-adjusted returns.
A graduate of both engineering and finance programs from top institutions, she brings a rare combination of technical expertise and market intuition to her investment approach. Her thought leadership on commodities markets and quantitative trading strategies is regularly featured in industry publications and conferences.
The views expressed above are not necessarily the views of Thalēs Trading Solutions or any of its affiliates (collectively, “Thalēs”). The information presented above is only for informational and educational purposes and is not an offer to sell or the solicitation of an offer to buy any securities or other instruments. Additionally, the above information is not intended to provide, and should not be relied upon for investment, accounting, legal or tax advice. Thalēs makes no representations, express or implied, regarding the accuracy or completeness of this information, and the reader accepts all risks in relying on the above information for any purpose whatsoever.
