Sean McMeekin PhD was educated at Stanford University and the University of California, Berkeley. Having visited American and European battlefields, libraries and archives, venturing as far east as Russia and Turkey, he now teaches at Bard College. His eight award-winning books include ‘Stalin's War: A New History of World War’. His latest book is ‘To Overthrow the World: The Rise and Fall and Rise of Communism’. In this podcast we discuss the early roots of Communism, Karl Marx and political violence, Lenin and how to seize power, and much more. 

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Christian is Managing Director and Head of Data Science in the financial markets division at Standard Chartered. He focuses on credit and previously worked at Mizuho and Credit Suisse. His postgraduate studies were in financial mathematics. In this podcast we discuss whether we are in an AI bubble, why credit markets have lagged other markets in adopting AI, using generative AI to create synthetic data, and much more. 

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Jay Pelosky is the founder of TPW Advisory. He has over 35 years of buy-side and sell-side financial market experience. Before going independent, Jay was at Morgan Stanley, where he was ranked #1 by Institutional Investor in Global Equity Strategy and Global Asset Allocation Strategy. In this podcast, we discuss what the chances of recession are, US earnings and productivity, equities are not just a tech story, and much more. 

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Mirza Baig is a senior EM strategist at Macro Hive. He has been researching and trading global FX and rates products for 20 years. His career boasts affiliations with premier sell-side entities such as Morgan Stanley, BNP Paribas, and Deutsche Bank. Moreover, his invaluable expertise from the buy-side perspective at Point 72 positions him uniquely in the industry. In this podcast we discuss how EM has performed in recent years, the long-term case for EM, China: broad weakness, narrow strength, and much more. 

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Bob Elliott is the Co-Founder of Unlimited, which uses machine learning to create index replication ETFs of alternative investments, like hedge funds. Prior to founding Unlimited, Bob was a Senior Investment Executive at Bridgewater Associates, where he served on the Investment Committee (G7) and led Ray Dalio’s personal investment research team for nearly a decade. Bob holds a degree in History and Science from Harvard. In this podcast we discuss income business cycle rather than credit cycle, parallels to 1950s and 1960s, whether Fed policy is restrictive, and much more. 

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J. Doyne Farmer is Director of the Complexity Economics Programme and Professor of Complex Systems Science at the University of Oxford. He is also External Professor at the Santa Fe Institute and Chief Scientist at Macrocosm. He was a founder of Prediction Company, a quantitative automated trading firm that was sold to UBS in 2006. His book, Making Sense of Chaos: A Better Economics for a Better World, was published in 2024. During the 1980s he was an Oppenheimer Fellow and the founder of the Complex Systems Group at Los Alamos National Laboratory. While a graduate student in the 1970s, he built the first wearable digital computer, which was successfully used to predict the game of roulette. This podcast covers what chaos theory is, what complexity science is, how economists model the economy, and much more. 

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Shawn Edwards is Bloomberg’s Chief Technology Officer. Based in New York, he oversees the development of Bloomberg’s global technology strategy. In 2017, Shawn was named in the top ten of the Institutional Investor Tech 40 – an annual ranking of financial industry technology leaders. Prior to joining Bloomberg in 2003, Shawn worked for Bear Stearns & Co. where he was a managing director in the company’s fixed income trading group. He has also held positions at Mentor Graphics and IBM. This podcast covers philosophy around tech innovation, product and infrastructure strategy, adapting to cloud, mobile and API-first, and much more. 

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Brad Setser is the Whitney Shepardson senior fellow at the Council on Foreign Relations. His expertise includes global trade and capital flows, financial vulnerability analysis, and sovereign debt restructuring. He regularly blogs at Follow the Money. Brad served as a senior advisor to the United States Trade Representative from 2021 to 2022, where he worked on the resolution of a number of trade disputes. He had previously served as the deputy assistant secretary for international economic analysis in the US Treasury from 2011 to 2015 and as a director for international economics on the staff of the National Economic Council and the National Security Council. This podcast covers yen carry trade dynamics, FX intervention, Japan fiscal dynamics, and much more. 

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My colleague Mirza Baig hosted this podcast on my behalf. Liang is a markets professional, with 20 years’ experience as a portfolio manager, quantitative analyst, currency strategist, and China economist. He has spent most of his career based in Germany, where he earned his PhD and worked at several asset managers including DWS. Liang recently returned to his hometown of Shanghai, from where he speaks to global asset managers through the Macro Hive platform, advising them about the macro and policy outlook for China. This episode covers whether Fed rate cuts can prevent a deeper sell-off in global equity markets, current state of the Chinese economy, whether the Chinese government is becoming more serious about reflating the economy, especially consumer demand, and much more. 

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Álvaro Cartea is Professor of  Mathematical Finance in the Mathematical Institute, University of Oxford, and director of the Oxford-Man Institute of Quantitative Finance. He is a founding member and deputy chairman of the Commodities & Energy Markets Association (CEMA). Before coming to Oxford, Álvaro was Reader in Mathematical Finance at University College London. He was also previously JP Morgan Lecturer in Financial Mathematics, Exeter College, University of Oxford. Álvaro obtained his doctorate from the University of Oxford in 2003. This podcast covers the evolution of AI trading strategies, the unintented consequences of AI market makers, and the regulatory aspects of AI in finance.