Doktorarbeit: Valuation and Default Risk Assessment in Venture Capital Investments

Valuation and Default Risk Assessment in Venture Capital Investments

The Impact of Biases in Management Forecasts and the Relevance of Selected Financial and Non-Financial Information from Due Diligence Documents

Finanzmanagement, Band 92

Hamburg 2012, 156 Seiten
ISBN 978-3-8300-6658-3 (Print & eBook)

Bankruptcy Prediction, Cross-Sectional Projection Models, Default Risk Assessment, Entrepreneuership, Financial Accounting, Management Forecast Biases, Optimism, Overconfidence, Pre-Money Values, Start-Ups, Valuation, Venture Capital

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This book examines the impact of selected due diligence information on the valuation of venture-backed start-ups and the assessment of default risks. By investigating the characteristics and consequences of biases in multi-year management forecasts, this thesis also sheds light on the role of optimism and confidence in entrepreneurial environments. In addition, this study presents cross-sectional models that allow investors to identify potential biases in management forecasts before investment decisions.

The book builds on a proprietary dataset of venture capital investments and consists of three research papers. The first study provides evidence of significant biases in management forecasts and analyzes potential determinants of these biases. Furthermore, the study evaluates a cross-sectional projection approach developed by prior research with regard to ist suitability to derive benchmarks for management forecasts. The second study investigates the relevance of financial and non-financial information for the valuation of venture-backed start-ups. Further analyses examine the accuracy of popular valuation approaches based on basic industry-specific revenue or total asset multiples. The third study links the research findings from the two previously presented studies and additionally examines default risks. The study introduces a new cross-sectional projection method that enables investors to obtain benchmarks for management forecasts before an investment decision. Further empirical analyses show that firms with large forecast errors file significantly more often for bankruptcy than do less biased entrepreneurs in the years following the investment.

Overall, the results emphasize the relevance of accounting information and business plans and should enable investors to make superior investment decisions. Furthermore, the findings support the academic community, standard setters, and practitioners in better understanding the specific characteristics of venture capital investments.



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