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Andreas Fuster

Adjunct Associate Professor of Finance at Leonard N. Stern School of Business

SFI Senior Chair at Swiss Finance Institute

Schools

  • Leonard N. Stern School of Business
  • Swiss Finance Institute

Links

Biography

Leonard N. Stern School of Business

Biography

Andreas Fuster is a Research Officer in the Capital Markets Function at the Federal Reserve Bank of New York, with main research interests in household and real estate finance, as well as behavioral and experimental economics. His recent work examines the effects of securitization on mortgage contract design, the factors affecting mortgage defaults, the effects of financing conditions on the housing market, and the determinants of risk premia in the prices of mortgage-backed securities. Andreas’s research has been published in academic journals such as the Quarterly Journal of Economics, the Review of Financial Studies, and the Journal of Economic Perspectives. Andreas obtained his Ph.D. from Harvard University in 2011, and also holds an M.Phil. from Oxford University and a B.A. from the University of Lausanne (Switzerland), all in economics. During graduate school, he was a research associate and graduate fellow at the Federal Reserve Bank of Boston.

Courses Taught

  • Real Estate Capital Markets (FINC-GB.2339)

Academic Background

Ph.d., Economics, 2011
Harvard University

M.Phil, Economics, 2006
Oxford University

B.A., Economics, 2004
HEC University of Lausanne

Swiss Finance Institute

Andreas Fuster is Associate Professor of Finance at the Ecole Polytechnique Fédérale de Lausanne and a research fellow at the Center for Economic Policy Research. Previously, he worked in the research department of the Federal Reserve Bank of New York and in the financial stability department at the Swiss National Bank. Professor Fuster's research has been published in the top economics and finance journals.

Expertise

Professor Fuster is studying household and real estate finance, banking, and behavioral and experimental economics. He is particularly interested in the effects of technological innovations on household credit markets. For instance, he finds that US Fintech lenders process mortgage applications faster than traditional lenders and are better able to adjust their processing capacities when faced with a demand shock; their loans also exhibit lower default rates. When considering how machine learning will reshape the mortgage market, he finds that credit risk assessments improve, but that the benefits may not accrue to all groups in society equally.

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