The Relevance of Biases in Management Forecasts for Failure Prediction in Venture Capital Investments

31 Pages Posted: 4 Jul 2012

Date Written: June 2012

Abstract

This study shows how venture capital investors can identify potential biases in multi-year management forecasts before an investment decision and derive significantly more accurate failure predictions. By advancing a cross-sectional projection method developed by prior research and using firm-specific information in financial statements and business plans, we derive benchmarks for management revenue forecasts. With these benchmarks, we estimate forecast errors as an a priori measure of biased expectations. Using this measure for our proprietary dataset on venture-backed start-ups in Germany, we find evidence of substantial upward forecast biases. We uncover that firms with large forecast errors fail significantly more often than do less biased entrepreneurs in years following the investment. Overall, our results highlight the implications of excessive optimism and overconfidence in entrepreneurial environments and emphasize the relevance of accounting information and business plans for venture capital investment decisions.

Keywords: Management forecast biases, cross-sectional projection models, venture-backed start-ups, failure prediction, overoptimism, overconfidence

JEL Classification: G24, G32, M13, M41

Suggested Citation

Mokwa, Christopher Frederik and Sievers, Soenke, The Relevance of Biases in Management Forecasts for Failure Prediction in Venture Capital Investments (June 2012). Available at SSRN: https://ssrn.com/abstract=2100501 or http://dx.doi.org/10.2139/ssrn.2100501

Christopher Frederik Mokwa

University of Cologne ( email )

Albertus-Magnus-Platz
Cologne, 50923
Germany

Soenke Sievers (Contact Author)

Paderborn University ( email )

Warburger Str. 100
Paderborn, 33098
Germany

HOME PAGE: http://www.upb.de/accounting

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