Andrea Barbon
Assistant Professor of Finance at University of St. Gallen
SFI Faculty Member at Swiss Finance Institute
Schools
- Swiss Finance Institute
- University of St. Gallen
Expertise
Links
Biography
University of St. Gallen
Andrea Barbon works as Assistant Professor in Financial Technology at the Center for Financial Services Innovation at the University of St.Gallen (FSI-HSG), where he teaches “Mathematics for Finance” to Ph.D. students and “Financial Technology” to Master students. He was born in Venice and holds a Bachelor’s degree in pure and applied mathematics from the University of Padua, a Master’s degree in pure mathematics from the University of Amsterdam and a PhD in finance from the University of Lugano. His research interests revolve around financial technology with a focus on decentralized finance (DeFi), NFT markets, asset prices, market microstructure, and monetary policy. He has published in the Journal of Finance and the Review of Asset Pricing Studies.
Education
- Bachelor’s Degree in Pure and Applied Mathematics - University of Padua, Italy
- Master Degree in Pure Mathematics - WU Amsterdam, The Netherlands
- Ph.D. in Financial Economics - USI Lugano and Swiss Finance Institute
Professional Career
- Android Developer - NetStudio
- PhD in Finance - USI Lugano
- Assistant Professor of Finance - HSG
Teaching Activities
- Mathematics for Finance (PhD students)
- Financial Technology (Master students)
Swiss Finance Institute
Andrea Barbon is Assistant Professor of Finance at the University of St.Gallen. Professor Barbon shares his expertise in the field of artificial intelligence with Syntagma Global Investments, a research company that provides consultancy services across different asset classes and markets.
Expertise
Professor Barbon is investigating issues related to decentralized finance. In his work on the market quality of cryptocurrency exchanges, he compares price efficiency and market liquidity between decentralized and centralized exchanges. In more recent work, he leverages blockchain data to study the behavior of retail investors during price bubbles in the non-fungible tokens (NFTs) market. His research reveals that price crashes can be predicted to a significant extent by employing aggregate and agent-based variables.
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