Xinyi Zhang

Research

Working papers

1. Aggregate Risk and the Price of Immediacy for Predictable Demand. [Job market paper]

I examine how prevailing aggregate market risk affects the compensation required to absorb predictable trading demand at execution. Exploiting annual Russell index reconstitutions and variation in benchmarking intensity around the Russell 1000/2000 cutoff, I find that reconstitution-day returns remain sensitive to aggregate market risk, even though much of the price adjustment occurs in advance. A one-standard-deviation increase in the VIX amplifies the reconstitution-day return response to a one-percentage-point increase in benchmarking intensity by 9.5 basis points. This additional response subsequently attenuates and is more pronounced among less liquid stocks with fewer institutional holders. These findings are consistent with liquidity providers requiring greater compensation for bearing temporary inventory risk when accommodating predictable demand under elevated market risk. The results also highlight an important implication for passive investing: price-insensitive rebalancing by index funds may impose implicit costs on fund investors.

2. Pure Momentum, with Roberto Renò and Roméo Tédongap, R&R at Management Science. [Paper]

Momentum trading strategies exploit return persistence, but conventional signals based on past-year cumulative returns are noisy and attenuate performance. We propose a pure momentum strategy that identifies trends directly from daily returns through a statistical measure of drift strength. The resulting stock-selection rule lowers volatility, tail risk, and transaction costs while increasing profitability. Performance is primarily driven by long positions in pure winners. Our results are consistent with theories that emphasize overconfidence among winners and the slow diffusion of information among losers.

3. Misspecification and Weak Identification in the Nontraded Factor Zoo, with Amedeo Andriollo, Cesare Robotti, and Giulio Rossetti. [Paper]

To explain the cross-section of asset returns, a "zoo" of nontraded factors has been proposed. In contrast to traded factors, nontraded factors exhibit lower correlations with 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 nontraded 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 nontraded 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. Complementing these tests, a comprehensive beta-sorted portfolio analysis shows that few nontraded factors translate into economically meaningful investment premiums. However, when summarizing the nontraded factors via PCA, we find that the zoo does carry some non-zero pricing information.

4. Why is Crypto Premium so High?, with Roberto Renò

Teaching

Teaching Awards

• Outstanding Contribution to Student Learning Award 2025-2026

• Outstanding Contribution to Student Learning Award 2024-2025

• Outstanding Contribution to Teaching Excellence Award 2021-2022

Seminar Teaching

Postgraduate

• Research Methodology, 2021-2022, 2023-2025

• Data Analysis for Finance, 2025-2026, 2026-present

• Research Methodology for Financial Management, 2021-2022, 2023-present

• Quantitative Methods for Financial Management, 2023-2024

Undergraduate

• Foundation of Finance, 2024-2025

Online MBA

• Financial Management, 2025-present