Hi, I’m Yuhan Ye
Ph.D. Candidate in Finance, Swiss Finance Institute (SFI) & Università della Svizzera italiana (USI). I am on the 2025–2026 academic job market.
Research Interests
- Corporate Finance
- Machine Learning in Finance
- Human vs. Machine Decision Making
Contact: yuhan.ye@usi.ch
Job Market Paper
This paper investigates whether better information environments favor humans or machines by shaping the relative forecasting performance of analysts and algorithms with detailed forecasts across 47 global stock markets from 1985 to 2024.
Abstract
This paper investigates whether better information favors humans or machines. Using detailed analyst forecasts and machine-learning predictions for 47 global stock markets from 1985 to 2024, I study how information environments affect the relative forecasting performance of human analysts and algorithms. Human forecasts are relatively more accurate in stronger information environments, characterized by greater data availability, transparency, and access to information. These results indicate that richer information environments favor humans over machines. The evidence is consistent with humans’ comparative advantage in processing qualitative and contextual information when credible data and transparent institutions are present. In contrast, in weaker information environments, machines complement humans by providing stable, data-driven signals. Cross-market patterns further show that institutional transparency amplifies humans’ relative advantage, underscoring the role of information environments in shaping human–machine complementarity in financial forecasting.
Presented at: AFA 2026 (Poster, scheduled), EPFL Memento Brown Bag Seminars (scheduled), SFI Academic Job Market Workshop, USI IFin Brown Bag, CREDIT Venice 2025, HEC PhD Workshop, 2nd HKUST IAS–SBM Joint Workshop (Poster), PhD Summer School on Finance and Product Markets, UZH Rising Scholars Conference, and SFI Research Days.