Working Papers


Abstract: Investors discipline fund managers by reallocating capital toward those with stronger perceived skill and away from poor performers. However, as financial advisors increasingly implement model portfolios, a growing share of fund flows is determined by these centralized allocation rules rather than by dispersed investor judgment. I construct a measure of model-implied demand: the rebalancing pressure generated by deviations of fund weights from model portfolio targets. I show that model-implied demand is a significant driver of fund flows and generates more persistent flows than discretionary investor demand. Model-implied demand also buffers funds against performance-driven outflows, especially during periods of market stress. This shift affects managers’ risk-taking behavior: funds with greater model exposure reduce portfolio risk and take smaller active bets following poor performance. Funds also reduce fees when added to a model or when facing the threat of removal from it. The continued growth of model portfolios may increase the coordination of fund flows and shift competitive discipline from performance toward model inclusion.

Main presentations: 19th International Risk Management Conference (IRMC), 32nd Annual Meeting of the German Finance Association (DGF), HEC Paris PhD Workshop 2026, SFI Research Days 2026, USI Lugano.





Abstract: The trading behavior of U.S. Senators has faced growing public scrutiny due to potential misuse of insider information. I document a novel empirical fact: stock trades by U.S. Senators predict abnormal returns in the same direction after disclosure exceeding 90 bps in a month, but not after the actual transaction. I reconcile this evidence by isolating a set of potentially speculative trades (multiple purchases and sales of the same stock), which frequently originate from industries under considerable governmental oversight and public controversy. Realized returns on speculative trades earn more than 9 bps daily. Since the speculative nature becomes apparent only ex-post, there is uncertainty on the trade type at the disclosure time. Consequently, the market may overreact or mistakenly replicate also uninformed trades. In accordance, the price impact after disclosure is only temporary. Nonetheless, a trading strategy timed on disclosure yields substantial financial gains, even while being agnostic about the nature of the underlying trade. Overall, this study suggests a re-evaluation of the effectiveness of public disclosure as a disciplining mechanism for political insiders. Indeed, politicians are still able to profit abnormally on many of their trades. At the same time, disclosure may unintentionally act as a catalyst in fostering noise trading. 

Main presentations: : USI Lugano, Bocconi-SFI PhD Workshop 2023, SFI Research Days 2024, Wolfe Research LLC (Invited, 2025).


Other Working Papers


Abstract: Obituaries are traditionally seen as expressions of grief and remembrance. We argue that they also have an underappreciated economic role: they are vehicles for strategic social and economic signaling. In this paper, we develop a simple theoretical framework in which paid obituaries serve as a form of self-promotion, especially when the deceased is a prominent public figure. We then test this hypothesis using data from Italy, exploiting the variation in mortality caused by the COVID-19 pandemic as a natural experiment. We show that higher mortality rates are associated with increases in per-capita obituaries, driven not by informational needs but by strategic advertising motives. Our results suggest that obituaries function as a marketplace for visibility and status, where social and economic incentives intersect.  


Abstract: The interest for the dynamics of natural disasters has significantly expanded during the last decades, from natural sciences to other fields, including economic research, due to the global increase in frequency and socio-economic impact of such events. Economic evaluation of natural disasters nevertheless constitutes a complex and multidisciplinary field. This note presents the Natural Disasters Database for Italy (NDDI), a data set obtained by combining different data sources and describing the evolution of natural disasters and their impact on public spending starting from the Second World War.

Media: Media: ItaliaOggi (09/08/19), OggiScienza, AUA-UnipolSai, Panorama Assicurativo, Giornale delle PMI, AgoraVox.