About

Andrea Vedolin is a Professor and Department Chair of Finance at Boston University Questrom School of Business. His research focuses on various aspects of financial economics, including interest rate risk management, exchange rates, asset prices, and monetary policy uncertainty. Vedolin has contributed to the understanding of central bank communication, model complexity in expectations, and the global factor structure of exchange rates, among other topics. His work has been published in leading journals such as the Journal of Financial Economics, The Review of Financial Studies, and the Journal of Finance. Vedolin's research provides insights into the behavior of financial markets and the impact of economic uncertainty, and he is recognized for his significant contributions to the field of finance.

Research topics

• Computer Science
• Economics
• Econometrics
• Macroeconomics
• Financial economics
• Monetary economics
• Mathematics
• Political Science
• Artificial Intelligence
• Business
• Statistics
• Microeconomics
• Finance
• Financial system

Selected publications

• Demand-based Expected Returns

  SSRN Electronic Journal · 2025-01-01

  preprintOpen accessSenior author
  PublisherDOI

• Skewness and Time-Varying Second Moments in a Nonlinear Production Network: Theory and Evidence

  SSRN Electronic Journal · 2025-01-01

  preprintOpen accessSenior author
  PublisherDOI

• Robustness and dynamic sentiment

  Journal of Financial Economics · 2024-10-30 · 4 citations

  article
  PublisherDOI

• The global factor structure of exchange rates

  Journal of Financial Economics · 2023 · 19 citations

  Senior authorCorresponding
  • Computer Science
  • Economics
  • Econometrics

  We propose a model-free methodology to estimate international stochastic discount factors (SDFs) that jointly price cross-sections of international stocks, bonds, and currencies in markets with frictions. We theoretically establish a SDF decomposition into one global factor and a currency basket. We show that our global factor prices a large cross-section of international asset returns, not just in- but also out-of-sample, across different currency denominations. Moreover, the pricing ability of the global factor is largely independent of the market structure or the size and type of market friction.

  PublisherDOI

• Model Complexity, Expectations, and Asset Prices

  The Review of Economic Studies · 2023 · 13 citations

  Senior authorCorresponding
  • Computer Science
  • Economics
  • Econometrics

  Abstract This paper analyses how limits to the complexity of statistical models used by market participants can shape asset prices. We consider an economy in which the stochastic process that governs the evolution of economic variables may not have a simple representation, and yet, agents are only capable of entertaining statistical models with a certain level of complexity. As a result, they may end up with a lower-dimensional approximation that does not fully capture the intertemporal complexity of the true data-generating process. We first characterize the implications of the resulting departure from rational expectations and relate the extent of return and forecast-error predictability at various horizons to the complexity of agents’ models and the statistical properties of the underlying process. We then apply our framework to study violations of uncovered interest rate parity in foreign exchange markets. We find that constraints on the complexity of agents’ models can generate return predictability patterns that are simultaneously consistent with the well-known forward discount and predictability reversal puzzles.

  PublisherDOI

• Model Complexity, Expectations, and Asset Prices

  National Bureau of Economic Research · 2021-01-01 · 13 citations

  reportOpen accessSenior author

  This paper analyzes how limits to the complexity of statistical models used by market participants can shape asset prices. We consider an economy in which agents can only entertain models with at most k factors, where k may be distinct from the true number of factors that drive the economy's fundamentals. We first characterize the implications of the resulting departure from rational expectations for return dynamics and relate the extent of return predictability at various horizons to the number of factors in the agents' models and the statistical properties of the underlying data-generating process. We then apply our framework to two applications in asset pricing: (i) violations of uncovered interest rate parity at different horizons and (ii) momentum and reversal in equity returns. We find that constraints on the complexity of agents' models can generate return predictability patterns that are consistent with the data.

  PublisherDOI

• Skewness and Time-Varying Second Moments in a Nonlinear Production Network: Theory and Evidence

  National Bureau of Economic Research · 2021-11-01 · 17 citations

  preprintSenior author

  This paper studies asymmetry in economic activity over the business cycle. It develops a tractable multisector model of the economy in which complementarity across inputs causes aggregate activity to be left skewed with countercyclical volatility. We then examine implications of the model regarding the time-series skewness of activity at the sector level, cyclicality of dispersion and skewness across sectors, and the conditional covariances of sector growth rates, finding support for each in the data. The empirical skewness of employment growth, industrial production growth, and stock returns increases with the level of aggregation, which is consistent with the model's implication that it is the nonlinearity in the production structure of the economy that generates the skewness. Other prominent models of asymmetry are not able to simultaneously match the range of empirical facts that the production network model can.

  PublisherDOI

• Central bank communication and the yield curve

  Journal of Financial Economics · 2021 · 100 citations

  • Political Science
  • Monetary economics
  • Economics
  PublisherOA PDFDOI

• Robustness and Dynamic Sentiment

  SSRN Electronic Journal · 2021-01-01 · 2 citations

  articleOpen access
  PublisherDOI

• Skewness and Time-Varying Second Moments in a Nonlinear Production Network: Theory and Evidence

  SSRN Electronic Journal · 2021-01-01 · 5 citations

  articleOpen accessSenior author
  PublisherDOI

Frequent coauthors

• Philippe Mueller

  32 shared

• Fabio Trojani

  University of Geneva

  26 shared

• Alireza Tahbaz-Salehi

  Northwestern University

  23 shared

• Aytek Malkhozov

  Queen Mary University of London

  11 shared

• Gyuri Venter

  University of Warwick

  10 shared

• Sofonias Alemu Korsaye

  Swiss Finance Institute

  8 shared

• Hao Xing

  Citadel

  7 shared

• Andrea Buraschi

  Centre for Economic Policy Research

  7 shared

Education

• Ph.D., Finance

  University of California, Berkeley

  2003

• M.S., Finance

  University of California, Berkeley

  1999

• B.A., Economics

  University of California, Santa Barbara

  1997