Quantcast – a Risk.net Cutting Edge podcast

Walter Farkas, Director of the Master's in Quantitative Finance at ETH Zurich and the University of Zurich, shares insights on bridging academia and industry. He discusses the integration of industry lecturers to enhance practical learning and the importance of internships for students. Walter highlights a recent curriculum refresh that includes machine learning and data-driven methods. He also emphasizes the balance in topics between buy-side and sell-side exposure while fostering curiosity through hands-on projects. Finally, he reveals what traits they seek in applicants to ensure a strong program.

Jack Jacquier, Director of the MSc in Mathematics and Finance at Imperial College London, brings a wealth of knowledge in volatility modeling and quantum computing. He discusses the program's blend of theoretical understanding and practical industry connections in London. Recent curriculum changes incorporate topics like quantum machine learning. Jack emphasizes the importance of curiosity and interpersonal skills, as well as the long-term impact of volatility research and quantum algorithms on finance. His insights into collaborative projects and industry links reveal a dynamic future for finance education.

Kihun Nam, Director of the Masters in Financial Mathematics at Monash University, discusses transformative trends in quantitative finance education. He highlights the program's shift toward buy-side skills driven by Melbourne's superannuation industry. Kihun details curriculum evolution from pure mathematics to AI and asset management, and the importance of internships for job placements. He shares insights on student diversity and pathways to PhDs, encouraging curious minds to connect math with financial applications.

Petter Kolm, Director of the Master's in Mathematics and Finance at NYU's Courant Institute, dives into the evolution of finance education inspired by real-world needs. He discusses the shift in curriculum focus post-2008 crisis and the vital role of internships in preparing students for industry. Petter also highlights the impact of generative AI on coding education and the importance of foundational skills. He shares insights from his research on order book data and the evolution of prediction models in high-frequency trading.

Laura Ballotta, Director of the Masters in Quantitative Finance at Bayes Business School, dives into the fusion of rigorous theory and practical industry experience in finance education. She discusses the curriculum's shift towards machine learning and climate risk modeling, emphasizing a balanced approach between theory and practical assessments. Laura also highlights the importance of coding skills in Python and MATLAB and explores the role of AI in enhancing student projects. Her insights into the international applicant landscape provide a glimpse into evolving trends in finance education.

Stefano Iabichino, Director of the QS team at UBS, dives into the intersection of AI and finance. He discusses designing finance-first neural networks that adhere to no-arbitrage principles. Stefano critiques conventional AI for its pattern reliance, emphasizing the imperative of no-arbitrage across market regimes. He highlights the use of each neuron as a representation of future market states and explores practical applications in hedge funds, including learning market probabilities and innovative stress-based risk management. His research aims for coherence in financial AI models.

Imperial College’s mathematical finance head introduces new tool to measure slippage and trade quality

Dario Villani, Co-founder and CEO of Duality Group, and Kharen Musaelian, Co-founder and CIO, share insights from their pioneering work in quantum cognition machine learning (QCML). They discuss the game-changing impact of integrating quantum theory into finance, emphasizing how QCML can improve predictions with noisy data. The duo dives into the complexities of statistical learning and the contrasting views of uncertainty in classical versus quantum frameworks. They also explore advancements in healthcare and the pressing need for regulation as AI and quantum technologies evolve.

BoE quant discusses a top-down counterparty risk framework that uses Gaussian distributions and copulae

Trio of senior quants explain how autoencoders can reduce dimensionality in yield curves