The contribution of this study is manifold and relevant for academics and practitioners alike. It adds to the literature in the fields of corporate finance, financial accounting and stochastic modeling. In particular, this dissertation provides answers to the following questions: given the less efficient markets, can specialists as financial analysts provide additional information, which contain investment value? How can the true value of a company be determined with publicly available data and can discrepancies between fundamental and market values be exploited? Finally, is it possible to assess the firm’s financial health and its likelihood of failure several years into the future? Adressing these questions, the study first illustrates the company valuation assessment by financial analysts as summarized in their target prices and the information processing by analysts and investors in detail. Second, this thesis offers a novel empirical implementation of a model for fundamental company valuation that employs accounting data. In this context it demonstrates severe over- and undervaluation from a fundamental perspective in the U.S. technology sector over the last 20 years. Both the analysts’ company valuation captured by their target prices and the implementation of the fundamental company valuation model translate into significant investment value before and after transaction costs, which supports the notion of non-efficient markets. Finally, one major contribution is to evaluate a new approach for bankruptcy prediction that is based on stochastic processes. It is theoretically appealing and performs better especially for longer forecast horizons than standard methods.
Inhaltsverzeichnis (Table of Contents)
- Introduction
- To Buy or Not to Buy? The Value of Contradictory Analyst Signals
- Introduction
- Data and Methodology
- Data, Variables, and Descriptive Statistics
- Methodology
- Empirical Results
- Calendar Time Portfolios
- Factor Loadings, Market Capitalization, and Transaction Costs
- Potential Explanations
- Conclusion
- Valuing High Technology Growth Firms
- Introduction
- Related Literature: Firm Growth and Valuation
- Valuation Models
- Fundamental Pricing: The Schwartz-Moon Model
- Introducing a Benchmark: Enterprise-Value-Sales Multiple
- Data and Methodology
- Data Collection
- Model Implementation
- Revenue Dynamics
- Cost Dynamics
- Balance Sheet and Remaining Firm Parameters
- Environmental and Risk Parameters
- Simulation Parameters
- Summary Statistics
- Main Empirical Results
- Feasibility and Deviations from Market Values
- Detecting Over- and Undervaluation: The Trading Strategy
- Robustness Checks
- Discussion and Conclusion
- Bankruptcy Prediction Based on Stochastic Processes: A New Model Class to Predict Corporate Bankruptcies?
- Introduction
- Prior Research
- The Model
- Sales and Costs
- The Accounting Volatilities
- The Change in Net Working Capital
- Data and Model Implementation
- The Data
- Parameter Estimation
- Empirical Analyses
- Summary Statistics and Correlations
- Accuracy
- Test of Information Content
- Discussion and Conclusion
- Summary and Conclusion
Zielsetzung und Themenschwerpunkte (Objectives and Key Themes)
This dissertation investigates the forecasting of companies' future performance using both analyst assessments and stochastic modeling. It aims to explore the value of contradictory analyst signals in predicting company performance and to develop a new model class for bankruptcy prediction based on stochastic processes. The key themes explored in the dissertation include:- The value of analyst signals in company valuation
- The impact of contradictory analyst signals on company performance
- Stochastic modeling for predicting corporate bankruptcies
- Valuation of high-technology growth firms
- Developing new model classes for predicting corporate bankruptcies
Zusammenfassung der Kapitel (Chapter Summaries)
- The first chapter provides an introduction to the topic of company valuation and bankruptcy prediction, outlining the dissertation's objectives and research questions. It discusses the limitations of traditional approaches and highlights the potential of analyst assessments and stochastic modeling for forecasting company performance.
- The second chapter examines the value of contradictory analyst signals in predicting company performance. It analyzes data on analyst recommendations and target prices, exploring the relationship between contradictory signals and subsequent stock price movements. This chapter investigates the potential for constructing profitable trading strategies based on analyst signals.
- The third chapter focuses on the valuation of high-technology growth firms. It applies a stochastic model to estimate the value of these firms and assesses the model's ability to predict future performance. This chapter investigates the feasibility of the model and analyzes the deviations between predicted and actual market values, exploring the potential for identifying over- and undervalued companies.
- The fourth chapter presents a new model class for bankruptcy prediction based on stochastic processes. It develops a model that incorporates key accounting variables and uses historical data to estimate future financial distress. This chapter investigates the model's accuracy in predicting bankruptcy and examines its ability to outperform existing models.
Schlüsselwörter (Keywords)
Company valuation, bankruptcy prediction, analyst signals, stochastic modeling, high-technology growth firms, corporate finance, financial modeling, accounting data, trading strategies, model development, empirical analysis.- Quote paper
- Dipl. Vw. Jan Klobucnik (Author), 2013, Company Valuation and Bankruptcy Prediction, Munich, GRIN Verlag, https://www.grin.com/document/264986
