The Use of Inferential Statistics, Field Experiments, and Machine Learning in Corporate Finance

Abstract

Lars Hornuf will present two ongoing research projects, which illustrate the methods and data used in state-of-the-art business research. Does it matter for business success how prominent an investor is? Using inferential statistics, he analyzes the determinants of funding success and consequent firm performance of 2768 early-stage ventures that made a business pitch during the Canadian, German, UK or US versions of the reality television show Dragons’ Den. The data was in part scraped from public sources and classified using machine learning tools. What motivates crowd funders to support projects on online crowdfunding platforms? To answer this question, the nowadays “gold-standard” in economics and business research is applied: field experiments. Lars will give a brief introduction why and how this method is applied today.


About the Speaker

Lars Hornuf holds the Chair of Business Administration, especially Financial Services and Financial Technology at the University of Bremen. He received an M.A. in Political Economy (University of Essex, UK), a Ph.D. in Economics (LMU Munich, Germany), and is a certified exchange trader and a certified derivatives trader. He worked for the Ifo Institute for Economic Research and the Institute for International Law at the University of Munich. Lars was a visiting scholar at UC Berkeley, Stanford University, Duke University, Georgetown University, CESifo and the House of Finance at Goethe-University Frankfurt. Currently, he is an Affiliated Research Fellow at the Max Planck Institute for Innovation and Competition and the CESifo Research Network. His research interest is in entrepreneurial finance, data privacy, as well as law and finance. The Economist and Foreign Policy have covered his research.

Speaker:
Prof. Dr. Lars Hornuf