Financial Thought Exchange Podcast

In Part 2, Francesco Fabozzi, PhD—Managing Editor of the Journal of Financial Data Science—joins host Lotta Moberg, CFA, PhD, to explore how modern NLP and large language models are reshaping investment management. Building on the technical foundations from Part 1, this episode turns to real-world applications: when to fine‑tune models versus rely on prompt engineering, how retrieval‑augmented generation (RAG) keeps models current with fast‑changing financial information, and why agentic systems are emerging as powerful tools for research automation. Fabozzi explains practical use cases ranging from sentiment‑driven return prediction to efficient knowledge‑distillation workflows, research assistants that read earnings reports, and coding agents that help back‑test investment ideas. The discussion closes with a look at where innovation is headed, including the potential of "general price transformers" for market forecasting. This episode is essential for anyone applying AI within investment processes.

Francesco Fabozzi, PhD, Managing Editor of the Journal of Financial Data Science, joins Lotta Moberg, CFA, PhD to unpack how natural language processing matured into the powerful tool it is today. The discussion traces early finance‑focused techniques—dictionary counts, sentiment word lists, and sparse document‑term matrices, along with their limits around context and negation. Fabozzi then explains how neural networks introduced embeddings and contextual meaning, paving the way for recurrent models and eventually transformer architectures. He breaks down how self‑attention, encoder–decoder designs, and decoder‑only LLMs transformed language understanding and made large‑scale modeling feasible. This episode lays the groundwork for understanding how modern NLP models interpret financial text. Look for Part 2, where the conversation turns to practical applications in investment management.

In the concluding episode, Lotta Moberg, CFA, PhD and Oswaldo Zapata, PhD look toward the future of quantum computing in finance. They discuss potential high‑value applications such as optimization, option pricing, machine learning, and large‑scale simulations. Zapata also highlights the cyber‑security implications of quantum technologies, including the threat of breaking RSA encryption and the urgency of adopting quantum‑safe protocols. The conversation covers industry readiness, from hedge fund research to major institutions investing in quantum capabilities, as well as the emerging need for "quantum‑quants." This episode provides a forward‑looking view of how quantum computing may reshape financial services, risk management, and professional skill sets in the decade ahead. To read Oswaldo Zapata, PhD's chapter in AI in Asset Management, follow this link: https://rpc.cfainstitute.org/research/foundation/2025/chapter-9-quantum-computing-for-finance

Part 2 explores the technical hurdles shaping quantum computing's readiness for financial applications. Oswaldo Zapata, PhD and host Lotta Moberg, CFA, PhD discuss qubit quality, error rates, and why today's devices remain in the "noisy intermediate‑scale quantum" (NISQ) era. The episode breaks down hybrid classical‑quantum approaches, quantum‑inspired algorithms, and the complex process of encoding classical data into quantum states. Zapata explains why portfolio optimization is a promising—but still aspirational—area for quantum speedups, and how current hardware limitations constrain real‑world deployment. This conversation offers an honest assessment of where the technology stands today and what breakthroughs are still needed before quantum tools can meaningfully impact finance. To read Oswaldo Zapata, PhD's chapter in AI in Asset Management, follow this link: https://rpc.cfainstitute.org/research/foundation/2025/chapter-9-quantum-computing-for-finance

In Part 1 of this three-part interview, host Lotta Moberg, CFA, PhD, speaks with Oswaldo Zapata, PhD, co‑founder of the Quantum Finance Boardroom and contributor to the CFA Institute Research Foundation monograph AI in Asset Management. This episode introduces the fundamentals of quantum computation, outlining how qubits, superposition, and quantum gates differ from classical computing. Zapata explains why quantum systems can process information in exponentially richer ways and discusses the challenges of building reliable qubits in real‑world laboratory environments. The conversation sets the groundwork for understanding how quantum computers may eventually tackle computational problems that classical machines cannot. This episode is ideal for finance professionals seeking a clear, accessible foundation in quantum technologies before diving into applications. To read Oswaldo Zapata, PhD's chapter in AI in Asset Management, follow this link: https://rpc.cfainstitute.org/research/foundation/2025/chapter-9-quantum-computing-for-finance

In this enlightening discussion, Marcos López de Prado, a professor and expert in machine learning for finance, joins Vincent Zoonekynd, a leader in quantitative research. They unveil the pitfalls of factor models, including the perils of p-hacking and collider bias. Listeners discover how causal graphs can enhance factor attribution and improve model design. The duo emphasizes that factor investing should focus on causality rather than mere statistical correlations, urging researchers to clarify their assumptions in model reporting.

Dr. William J. Bernstein, a seasoned author and former neurologist, dives into the pillars of economic prosperity, highlighting property rights, scientific rationalism, and capital markets. He explores the Henrich hypothesis on trust and contrasts cultural versus institutional factors in industrial growth. Bernstein advocates for passive investing, emphasizing liability-matching portfolios and TIPS for retirement security. He raises concerns over de-globalization and questions the long-held belief in 'stocks for the long run,' hinting at a provocative new book co-authored with Ed McQuarrie.

In this episode of the Financial Thought Exchange podcast, host Lotta Moberg, CFA, PhD, speaks with David Knox, PhD, former senior partner at Mercer and author of the Research Foundation brief De-risking Global Pension Systems. Knox explores the complexities of global pension structures, the shift from defined benefit to defined contribution plans, and the growing reliance on private pensions. He discusses demographic pressures, funding challenges, and the importance of governance, regulation, and communication in securing retirement outcomes. A timely conversation for professionals navigating the future of pension policy and retirement planning.

Sébastien Page, CFA, Head of Global Multi-Asset and CIO at T. Rowe Price, joins the FTE Podcast to explore the intersection of leadership psychology and investment strategy. Drawing from his books Beyond Diversification and The Psychology of Leadership, Page shares how storytelling enhances financial education, the importance of resilience in investing, and how personality traits like openness and agreeableness shape portfolio management. He also reflects on goal-induced blindness, the underrated skill of quitting, and the deeper meaning behind active management. A must-listen for finance professionals and aspiring leaders.

Ehren Stanhope, CFA of O'Shaughnessy Asset Management explains how custom indexing builds on direct indexing by integrating tax loss harvesting, ESG preferences, and quantitative equity factors. He discusses how platforms like Canvas enable personalized portfolio construction while maintaining benchmark alignment. Stanhope also shares insights on the implications of rising interest rates, inflation, and changing asset correlations for long-term investment strategy and risk management.