I’m a fourth-year PhD candidate in the Economics & Finance Group at Esade Business School (Barcelona). My research sits at the intersection of empirical asset pricing and corporate finance, with applications to institutional investors, supply chain and ESG.
I am particularly interested in understanding how complex, hard-to-process information gets incorporated into market prices. To do so, I employ large-scale textual analysis and machine learning on datasets like earnings call transcripts, alongside high-frequency market data from options and credit default swaps.
I hold an M.Sc. in Economics and Finance from the Centro de Estudios Monetarios y Financieros (CEMFI), an M.Sc. in Mechanical Engineering from Sungkyunkwan University, and a B.Sc. in Mechanical Engineering from Dalian University of Technology.
The Supply-Chain Risk Factor and Geoeconomic Premium (JMP)
ABSTRACT:
I show that firm-level supply-chain dependence on geoeconomic center constitutes a novel systematic risk (SCF). A zero-cost portfolio sorted on SCF earns a 1.3% monthly premium, which rises to 4.2% after the 2018 U.S.-China tariff announcements. The economic mechanism is market perceptions of geoeconomic distress, which I quantify using a LLM-based textual-analysis pipeline applied to earnings calls across 41 countries. A factor based on this perceived geoeconomic distress fully explains the SCF premium. These results indicate that geopolitical tensions can convert firm-specific supply-chain risk into a systematic risk.