Company Valuation and Bankruptcy Prediction: Forecasting of Companies' Future Performance Through Analyst Assessments and Stochastic Modeling
Doctoral Thesis / Dissertation from the year 2013 in the subject Economics - Finance, grade: summa cum laude, University of Cologne, language: English, abstract: 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.
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Company Valuation and Bankruptcy Prediction: Forecasting of Companies' Future Performance Through Analyst Assessments and Stochastic Modeling
Doctoral Thesis / Dissertation from the year 2013 in the subject Economics - Finance, grade: summa cum laude, University of Cologne, language: English, abstract: 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.
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Company Valuation and Bankruptcy Prediction: Forecasting of Companies' Future Performance Through Analyst Assessments and Stochastic Modeling

Company Valuation and Bankruptcy Prediction: Forecasting of Companies' Future Performance Through Analyst Assessments and Stochastic Modeling

by Jan Klobucnik
Company Valuation and Bankruptcy Prediction: Forecasting of Companies' Future Performance Through Analyst Assessments and Stochastic Modeling

Company Valuation and Bankruptcy Prediction: Forecasting of Companies' Future Performance Through Analyst Assessments and Stochastic Modeling

by Jan Klobucnik

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Overview

Doctoral Thesis / Dissertation from the year 2013 in the subject Economics - Finance, grade: summa cum laude, University of Cologne, language: English, abstract: 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.

Product Details

ISBN-13: 9783656543589
Publisher: GRIN Verlag GmbH
Publication date: 01/01/2013
Sold by: CIANDO
Format: eBook
Pages: 151
File size: 4 MB
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