About me

I am an Assistant Professor at the Finance Department (DRM) at Université Paris Dauphine - PSL.

I obtained my PhD in Economics from the University of Warwick in June 2025.

My research lies at the intersection of econometrics, time series and financial econometrics, with a particular focus on asset returns and macroeconomic data.

E-mail: amedeo.andriollo[at]dauphine.psl.eu

Research

(feedback is welcome!)

Working Papers

• “Causality versus Serial Correlation: an Asymmetric Portmanteau Test”. 2026.
  SSRN. Recipient of the 2025 Carlo Giannini prize.
  Abstract:
  This paper studies specification testing in dynamic linear models in the presence of omitted variables. The null hypothesis of interest is weak exogeneity: structural shocks have zero conditional expectation given their own past and the past of omitted variables. Existing tests based on quadratic forms of serial cross-correlations suffer from size distortions because their variance incorporates symmetric dependence in both directions, including causality from past shocks to present omitted variables (inverse causality). This paper proposes a correction that offsets the contribution of inverse causality, yielding an asymmetric Portmanteau statistic that is asymptotically normal under the null, without requiring parametric modeling of the joint dynamics. An empirical application revisits Diercks et al. (2024) and rejects weak exogeneity of Baker et al. (2016)’s EPU shocks. Addressing this failure by augmenting the information set with additional controls leads to a positive inflation response, pointing to a supply-side shock interpretation.

• “Misspecification and Weak Identification in the Nontraded Factor Zoo”. 2025. with Cesare Robotti, Giulio Rossetti and Xinyi Zhang.
  WP link.
  Data: Nontraded Factor Zoo (monthly).
  Abstract:
  To explain the cross-section of asset returns, a zoo of economic factors that are not portfolio excess returns has been proposed. In contrast to traded factors, the non-traded factors tend to exhibit lower correlations with the asset returns. Standard inference on risk premium therefore tends to be more fragile, and the issue of weak identification might be exacerbated by the degree of model misspecification. Yet, robust inference has often been overlooked by many empirical studies, while limited efforts have been devoted to domesticating such factors. After re-evaluating the non-traded factor zoo, we find that the vast majority of the original model specifications published in top academic journals suffer from the aforementioned fragilities. Robust inference indicates that most of the proposed non-traded factors are unpriced in the commonly used portfolios. The findings are more drastic when considering multiple hypothesis testing adjustments, or when incorporating the market factor as an additional control. However, when summarizing the non-traded factors via PCA, we find that the zoo does carry some non-zero pricing information.

Works in Progress

• “Social Interactions under Cluster Dependence”. with Luis E. Candelaria.

• “Clustering Risk in Corporate Bonds”. with Giulio Rossetti.

• “Demand and Supply in Commodity Markets”. with Evgenia Passari and Michel A. Robe.

• “Theories as Regularizers”. with Juan F. Imbet.

Dormant WP

• “On the statistical properties of tests of parameter restrictions in beta-pricing models with a large number of assets”. 2023. with Cesare Robotti and Giulio Rossetti.
  WP link.

Teaching

• Université Paris Dauphine – PSL.
  Master level: Business Analytics (M2-270), 2025.

  Master level: Empirical Asset Pricing, 2026.

• University of Warwick.
  Postgraduate level: EC9A3 Advanced Econometric Theory, 2021-4, taught by Eric Renault and Luis Candelaria.

  Undergraduate level: EC226 Econometrics, 2021-2, taught by Jeremy Smith and Kenichi Nagasawa; EC204 Economics 2, 2021, taught by Jennifer Smith; EC201 Macroeconomics 2, 2021, taught by Roberto Pancrazi.

• Queen Mary University of London.
  Graduate level: Economics of Inequality (EMAP), 2022, taught by Sang Yoon Lee.

• University of Bologna.
  Graduate level: Macroeonomics 3, 2018, taught by Laura Bottazzi.