Andrea Andolfatto
Bocconi University | Andrea Andolfatto

I am a Ph.D. student in Finance at Bocconi University.

My research interests include Asset Pricing, Machine Learning, Behavioral Finance, and Decentralized Finance.

Download CV

Research

Working Papers

From Numbers to Words: Breaking Down Institutional Beliefs

with Federico Bastianello · [SSRN]

Abstract: We examine how large asset managers form and justify long-horizon beliefs by analyzing their Capital Market Assumptions (CMAs), articulated through tables, figures, and narratives. We develop a method that transforms CMA narratives into quantifiable causal networks using large language models, capturing both the complexity of managers' mental models and their allocation of attention across macro-financial topics. Our analysis reveals substantial heterogeneity in asset managers' beliefs, both quantitative and narrative. We document systematic biases using quantitative and textual evidence: return expectations deviate predictably from objective benchmark forecasts, greater cognitive complexity is associated with larger ex-ante forecast errors, and differences in attention to key building blocks affect the degree of over- or underreaction. Institutional expectations are economically meaningful and linked to objective return predictors, yet they still exhibit systematic and predictable deviations from objective benchmarks.

Decentralized and Centralized Options Trading: A Risk Premia Perspective

with Siddharth Naik and Lorenzo Schönleber · [SSRN]

Abstract: On-Chain options refer to option contracts implemented as smart contracts and traded on decentralized exchanges. We report a set of stylized facts about decentralized options trading and how automated market-making, a new model of liquidity provision for options, contributes to market fragmentation and segmentation. Empirically, we document that the prices of On-Chain options exceed those of Off-Chain options traded on centralized exchanges. Key factors driving this include automated market-maker mechanisms to mitigate risks and the impact of trading volume and net demand pressure. We propose a theory to explain the price difference and empirically verify its key implications.

Presentations: Canadian Derivatives Institute (CDI) Conference (Montreal), 2nd Knut Wicksell Conference on Crypto and Fintech (Lund), Annual Conference of the Asia-Pacific Association of Derivatives* (online), ToDeFi 2025* (Rome), Tech 4 Finance #2: AI and Blockchain* (Paris), 1st Bocconi PRIN Workshop in Crypto and Quantitative Finance (Milan), International Fintech Research Conference (Perugia), IFMB 2025 (online), AFA Annual Meeting* (San Francisco), AFA Annual Meeting - Poster Session (San Francisco), AlgoDefi24 Workshop* (Milan), IRMC, FMA European Conference, Universita Cattolica del Sacro Cuore (Milan), 2nd Structured Retail Products and Derivatives Conference, Lancaster-Manchester-Warwick Joint PhD Workshop on Quantitative Finance and Financial Technology (Warwick)
(*presented by coauthor)

Awards and Grants

  • 2025 - Best Paper Award, International Fintech Research Conference
  • 2024 - AFA Doctoral Student Travel Grant
  • 2024 - Fintech Chair Grant sponsored by the Université Paris Dauphine for "Decentralized and Centralized Options Trading: A Risk Premia Perspective" (with L. Schönleber and S. Naik)

Teaching

Instructor

  • Finance 3 (Ph.D.) - Bocconi University, 2023-2024. Course held by Prof. Max Croce.
  • Finance 4 (Ph.D.) - Bocconi University, 2023-2024. Course held by Prof. Nicolas Serrano Velarde.
  • Excel for Finance (Undergraduate) - University of Verona, 2019-2020. Course held by Prof. Marco Minozzo.

Teaching Assistant

  • Theory of Finance - Bocconi University. Course held by Prof. Claudio Tebaldi (2023-2024), Prof. Florian Nagler (2024-).
  • Big Data in Finance - Bocconi University. Course held by Prof. Clement Mazet-Sonilhac (2023-).
  • Advanced Corporate Finance for Management - Bocconi University. Course held by Prof. Jakob Ahm Sorensen (2024-).