Research
Working Papers
From Numbers to Words: Breaking Down Institutional Beliefs
Abstract: We examine how large asset managers form and justify long-horizon beliefs using their Capital Market Assumptions (CMAs). Our evidence points to a common architecture: managers decompose equity return expectations into shared building blocks, populate them using heterogeneous modeling assumptions, and process information through causal narratives, while peer consensus anchors forecast revisions. Valuation change and growth explain 77% of cross-sectional dispersion and are most strongly linked to equity allocations. Valuation-change expectations are countercyclical, whereas growth expectations are procyclical, generating countercyclical return expectations overall, with substantial heterogeneity across managers. Disclosed modeling assumptions matter too: mean-reversion and historical calibration predict systematic deviations from peer consensus. Using a new LLM methodology, we extract directed, signed causal networks from CMA narratives. Greater network complexity and attention to valuation change are associated with underreaction to positive earnings news, whereas attention to dividend yield and downturns is associated with overreaction. Comparisons with N-CSR shareholder letters show that CMA narratives reflect persistent institution-specific investment views. Volatility and correlation forecasts, by contrast, vary less across managers and remain closely tied to historical realizations.
Presentations: EFA 2026 (scheduled), NBER SI Asset Pricing 2026 (scheduled), WFA 2026 (scheduled), FIRS 2026 (Miami), Bocconi Ph.D. Workshop in Behavioral Economics and Finance 2026, Bocconi Workshop on Machine Learning and Financial Decision Making 2026, Harvard Behavioral Reading Group 2025
Decentralized and Centralized Options Trading
Abstract: On-Chain options are option contracts implemented as smart contracts and traded on decentralized exchanges. Although decentralized exchanges dominate spot markets, they account for only 1% of total options volume. We study this puzzle by documenting stylized facts about decentralized options trading and how automated market-making, a new model of liquidity provision, contributes to market fragmentation and persistent price differences across venues. Empirically, on-chain option prices exceed those on centralized exchanges, driven by blockchain-specific risks, automated market makers' risk-mitigation mechanisms, and volume and net buying 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)
Awards and Grants
- 2026 - BAFFI Ph.D. Fellowship, BAFFI Centre, Bocconi University
- 2026 - Pre-EFA Ph.D. program Travel Grant
- 2026 - The Brattle Group Ph.D. Candidate Awards For Outstanding Research, WFA
- 2025 - Best Paper Award, International Fintech Research Conference
- 2024 - AFA Doctoral Student Travel Grant
- 2024 - Fintech Chair Grant sponsored by the Université Paris Dauphine