Academic Website

Welcome to the Academic Website of Stefan Palan


I am a financial economist with research interests in the fields of behavioral and experimental finance, experimental economics and scientific methodology.

I am currently associate professor of finance at the University of Graz and lecturer at the University of Innsbruck and at Management Center Innsbruck. I am also editor-in-chief of the Journal of Behavioral and Experimental Finance, a founder and officer of the Society for Experimental Finance, coordinator of the Finance Research Platform Graz, and scientific director of the Max Jung Lab Graz.

This website aims to give an overview of my areas of academic interest and job experience. I am glad for any and all comments!

Best regards,
Stefan Palan.


Associate Professor of FinanceInstitute of Banking and FinanceUniversity of GrazUniversitaetsstrasse 15/F28010 GrazAustria
E: stefan.palan@uni-graz.atT: +43(316)380-7306W: academic.palan.biz

New working papers out

31.03.2021

The first quarter of the year has been a busy one, with two papers submitted and two new working papers published. In "Trading frictions and the post-earnings-announcement drift", Josef Fink, Erik Theissen and I study the effect of a short selling ban and transaction fees on the post-earnings-announcement drift. We find evidence for lower trading activity and higher asset prices in the presence of these types of frictions.

In "A Critical Perspective on the Conceptualization of Risk in Behavioral and Experimental Finance", Felix Holzmeister, Christoph Huber and I discuss the conceptualization of "risk" in finance, urging researchers to clearly distinguish between risk preferences, risk perceptions, and risk taking.

I welcome all thoughts and comments on these papers and topics!

Free, online z-Tree course

2020-12-14

I have spent the past weeks and months preparing a fully-fledged online z-Tree course, which is free for everyone (published under a CC-BY-SA license). It is designed to allow beginners with no prior z-Tree experience to learn all they need to start programming their own simple and not-so-simple experiments. I hope it will prove helpful to you and welcome any feedback you may have!