Deeponomics

Welcome, friend and future deep-dweller!

In this episode of Deeponomics, I sit down with Stefan Leins, Professor of Social Anthropology at the University of Bern and author of Stories of Capitalism, to explore what actually happens inside a financial analyst department at a large Swizz bank.

Based on a two-year ethnography, Leins takes us into the everyday world of buy-side financial analysts, a world far more narrative-driven than standard finance theory would ever admit.

We talk about how analysts work under radical uncertainty, why narratives matters, and how wildly different strategies, from technical analysis to being inspired by astrology and Fibonacci, coexist under the same institutional roof.

A central theme of the conversation is why financial analysts continue to exist despite decades of evidence that markets are difficult, if not impossible, to beat. Leins shows that the real product analysts deliver is not prediction accuracy, but compelling investment narratives that create orientation, agency, and legitimacy in an unknowable future.

We dive deep into the idea of narrative authority, how analysts build credibility through narratives rather than prediction accuracy, how forecasts travel through the bank via client advisors and asset managers, and how responsibility for failure is continuously pushed around the organization.

Along the way, we unpack how narratives differ from stories, why performativity only gets us part of the way, and what all of this means for investors, banks, and our understanding of expertise in finance.

If you are interested in markets as cultural systems, in finance as a narrative practice, or in what really sustains belief in professional expertise under uncertainty, this episode is a must-listen.

Click on his name to learn more about Stefan Leins and his work.

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Email: ⁠⁠[email protected]

Welcome, friend and future deep-dweller!

In this episode of Deeponomics, I sit down with Yuval Millo, Professor of Accounting at Warwick Business School, to trace the intellectual journey behind the social studies of finance and what it means to take markets seriously as social and reflexive systems.

Millo walks us through the early days of the field, including how his investigation into the Black–Scholes option pricing model led him to the idea of performativity and the insight that financial theories don’t just describe markets, they shape them.

We dive into his recent work on financial analysts, investors, and the subtle social structures that create market inertia, from overconfidence born in tight networks to the stickiness of buy-side and sell-side relationships.

We also explore his research on active fund managers, why so many still persist despite decades of underperformance, and what happens when the rise of passive investing becomes an epistemic threat to the identity of active professionals.

Finally, we touch on his newer work on machine learning and credit modeling, where opaque systems risk creating self-referential loops that humans cannot easily escape or evaluate.

If you’re curious about how markets actually work once you zoom in on the humans, tools, and stories that animate them, this conversation offers a rare inside view from someone who helped shape the field.

Learn more about Yuval Millo: https://www.wbs.ac.uk/about/person/yuval-millo/

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Find Us Deep

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Email: ⁠⁠[email protected]

Welcome, friend and future deep-dweller!

In this episode of Deeponomics, we sit down with Eldar Maksymov to explore the human side of data analytics.

Maksymov, a Professor at Arizona State University and Visiting Professor at the Stockholm School of Economics, studies how organizations actually make analytics useful in financial reporting and decision-making. His work highlights the human, interpretive, and organizational dimensions that often get overshadowed by the technology itself.

We take a deep dive into his recent research based on interviews with American financial executives—uncovering how leaders frame, negotiate, and embed analytics into everyday practice.

Along the way, we discuss sensemaking, resistance, and the messy process of transforming underperforming tools into genuinely decision-useful practices.

Drawing on qualitative, field-based insights, Maksymov shows that analytics succeeds not because of algorithms alone, but because humans give it meaning, legitimacy, and purpose in complex organizational settings.

Learn more about Eldar Maksymov: https://search.asu.edu/profile/2393744

This episode is produced in cooperation with the Stockholm School of Economics podcast, Numbers Talk. It is a longer and less filtered version of that conversation.

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Find Us Deep

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Email: ⁠⁠[email protected]

Welcome, friend and future deep-dweller!

In this episode of Deeponomics, we sit down with Johan Graaf to learn about the emergence of the field of investor relations.

Graaf, an Associate Professor at the Stockholm School of Economics, brings an interdisciplinary and ethnographic approach to the study of accounting as a social and institutional practice. His work explores how accounting shapes equity investment, the role of sell-side equity advisors, and the dynamics of rankings and performance management.

We take a deep dive into his current research on Investor Relations in a Swedish context—examining why the profession emerged, what it actually entails, and why practitioners must master a diverse mix of communication, financial understanding, and institutional awareness.

Drawing on qualitative, field-based methods, Graaf traces how IR officers navigate increasingly complex demands—from translating accounting and financial analysis into meaningful narratives, to responding to the shifting expectations of fund managers and other capital market actors.

Learn more about Johan Graaf: https://www.hhs.se/en/persons/g/graaf-johan/

This episode is produced in cooperation with the Stockholm School of Economics podcast, Numbers Talk. It is a longer and less filtered version of that conversation.

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Find Us Deep

Substack: deeponomics.substack.com

Instagram: @deeponomics

YouTube: @Deeponomics

Website: deeponomics.com

Email: ⁠⁠[email protected]

Welcome, friend and future deep-dweller!

In this episode of Deeponomics, we sit down with Les Coleman to examine the widening gap between modern finance theory and the realities of investing.

Coleman, a multidisciplinary researcher and long-time critic of conventional models, takes aim at the limitations of both neoclassical and behavioral finance. While behavioral finance may explain why investors act the way they do, Coleman argues it rarely offers guidance that actually improves decision-making.

We explore his view of financial markets as complex closed loop systems—interconnected, adaptive, and inherently difficult to predict.

From risk management to the underperformance of active fund managers, Coleman calls for a more grounded, multidisciplinary and applied approach to research.

He also shares principles from his own approach to equity investment, including why naive extrapolation of recent data might be the only useful forecasting tool.

In the end, Coleman’s message is one of humility: finance offers no certainties, investing is inherently challenging, but questioning assumptions, adapting to change, and drawing on multiple disciplines can improve our approach.

Learn more about Les Coleman: https://findanexpert.unimelb.edu.au/profile/75699-les-coleman

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Find Us Deep

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YouTube: @Deeponomics

Website: deeponomics.com

Email: ⁠⁠[email protected]

Welcome, friend and future deep-dweller!

In this episode of Deeponomics, we take a closer look at the enduring practice of market forecasting—despite decades of evidence showing how rarely it works.

We explore three major schools of thought—neoclassical, behavioral, and institutional economics—to see whether any of them can justify the financial analyst’s role. Each offers a different lens on why forecasts are made, but none quite explains why they should work.

In the end, we suggest that forecasting is not really about prediction. It is about sensemaking. In a world of uncertainty, forecasts offer structure, direction, and a shared story we can act on—even when the future remains unknown.

References:

Leins, S. (2018) Stories of Capitalism: Inside the Role of Financial Analysts. Chicago: University of Chicago Press.

Working, H. (1934) ‘A random-difference series for use in the analysis of time series’, Journal of the American Statistical Association, 29(185), pp. 11–24.

Kendall, M.G. (1953) ‘The analysis of economic time series’, Journal of the Royal Statistical Society. Series A (General), 116(1), pp. 11–34.

Osborne, M.F.M. (1959) ‘Brownian motion in the stock market’, Operations Research, 7(2), pp. 145–173.

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Find Us Deep

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Instagram: @deeponomics

YouTube: @Deeponomics

Website: deeponomics.com

Email: ⁠[email protected]

Welcome, friend and future deep-dweller!

In this episode of Deeponomics, we explore what makes a decision good — and why the answer has less to do with outcomes than you might think.

From a snowstorm at Narva in 1700 to Darwin’s pro-and-con list on marriage, we reflect on how decision-making is shaped not only by reason but by bias, framing, inertia, and emotion. Along the way, we question what it means to decide well — in finance, in economics, in life.

We also meet some of the usual suspects: confirmation bias, the sunk cost fallacy, anchoring, overconfidence, and more. But rather than stopping at diagnosis, we examine tools and “cognitive repairs” that might help us decide better under uncertainty.

This one is about process. About being less wrong. And about learning to live with the fact that even a good decision can lead to a bad result — and vice versa.

References:

Kahneman, D. (2011). Thinking, Fast and Slow.

Montier, J. (2006). Behaving Badly.

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Find Us Deep

Substack: deeponomics.substack.com

Instagram: @deeponomics

YouTube: @Deeponomics

Website: deeponomics.com

Email: [email protected]

Welcome, friend and future deep-dweller!

In this episode of Deeponomics, we bring accounting into the conversation—not as a neutral record of facts, but as a system built on choices, assumptions, and storytelling.

We trace how the connection between book values and market prices has weakened over time, and explore what happens when the numbers we rely on reflect only part of the picture.

References:

Hines, R. D. (1988). Financial accounting: In communicating reality, we construct reality. Accounting, Organizations and Society, 13(3), 251–261.

Hopwood, A. G. (1976). The path ahead. Accounting, Organizations and Society, 1(1), 1–4.

Lev, B., & Gu, F. (2016). The End of Accounting and the Path Forward for Investors and Managers. Wiley.

Broadbent, J. (1998). The gendered nature of accounting logic: Pointers to an accounting that encompasses multiple values. Critical Perspectives on Accounting, 9(3), 267–297.

Young, J. J. (2006). Making up users. Accounting, Organizations and Society, 31(6), 579–600.

Power, M. (1997). The Audit Society: Rituals of Verification. Oxford University Press.

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Find Us Deep

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Instagram: @deeponomics

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Website: deeponomics.com

Email: [email protected]

Welcome, friend and future deep-dweller!

This is the seventh monologue episode of Deeponomics—a podcast exploring the research, deep ideas, and theories shaping markets, finance, and accounting.

In this episode, we ask: Who does the Representative Agent really represent? We explore the simplification at the heart of many economic models—a single fictional individual standing in for millions. Why is this figure so dominant, and what do we lose when we model economies this way?

References:

Arrow, K.J., 1986. Rationality of self and others in an economic system. Journal of Business, 59(4), pp.S385–S399.

Brock, W.A. and Durlauf, S.N., 2001. Discrete choice with social interactions. Review of Economic Studies, 68(2), pp.235–260.

Kirman, A.P., 1992. Whom or what does the representative individual represent? Journal of Economic Perspectives, 6(2), pp.117–136.

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Find Us Deep

Substack: deeponomics.substack.com

Instagram: @deeponomics

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Website: deeponomics.com

Email: [email protected]

Welcome, friend and future deep-dweller!

This is the second interview episode of Deeponomics—a podcast exploring the research, deep ideas, and theories shaping markets, finance, and accounting.

This episode features a conversation with investigative journalist and accounting expert Francine McKenna, founder of the Substack newsletter The Dig, which explores the underexamined mechanics of auditing, regulation, and financial truth.

The discussion centers on the role of audits, the nature of accounting, and whether financial information can really be taken at face value. Beneath the numbers, it asks: who is the financial information for, who verifies it—and can they be trusted?

Topics explored include:

• ​What accounting actually is—and whether it reflects economic reality
• ​The role and limits of audits in protecting investors
• ​Why the Big Four audit firms face deep structural conflicts
• ​How financial storytelling shapes public understanding of risk and accountability
• ​What it would mean to rethink trust in financial reporting from the ground up

This is not just a conversation about accounting rules. It is a reflection on trust, transparency, and the architecture of belief that underpins modern capital markets.

Oh, and if you are curious about her work, check out The Dig: https://thedig.substack.com

Subscribe to follow along as each episode unpacks academic work, interrogates market assumptions, and ventures beneath the surface of financial storytelling.

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Find Us Deep

Substack: ⁠⁠deeponomics.substack.com⁠⁠

Instagram: ⁠⁠@deeponomics⁠⁠

YouTube: ⁠⁠@Deeponomics⁠⁠

Website: ⁠⁠www.deeponomics.com⁠⁠

Email: ⁠⁠⁠[email protected]