16 research outputs found

    Option-Style Multi-Factor Comparable Company Valuation for Practical Use

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    Classical single-factor comparable company valuation (CCV) like e.g. valuation using the price-earnings ratio is associated with several shortcomings. The two most important are the non-applicability of negative values in the basis of reference and the high requirements to the qualitative characteristics of comparable companies. This paper develops a multi-factor CCV model based on substance and performance related accounting attributes that largely overcomes these drawbacks. Additionally, the model allows to depict expected future earnings development economically sounder than single-factor models. Furthermore, by accounting for management?s option to adapt firm assets differently or to liquidate the company the model can conclusively assign positive stock prices to currently negatively performing companies. --Valuation,Multiples,Real Options

    The Impact of a Stock Market Downturn on Corporate Financing Activities in Germany

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    The paper analyses the potential impact of stock market developments on lending behaviour from different perspectives. First we scrutinize the impact of stock market movements on the banks' and on the borrowers' balance sheets. Subsequently we estimate aggregate credit supply and demand functions including a stock market indicator as explanatory variable. The analysis reveals no major importance of the bank balance sheet channel for the relationship between stock market volatility and corporate financing possibilities of non-financial companies. A possible impact of stock market movements on banks' lending behaviour might be rooted in their impact on the balance sheets of corporate borrowers. The empirical results of the credit market analysis yield some confirming evidence for an impact of stock market developments. However, the results are not very stable and depend on the specification of the model and on the time period under observation. --

    Option-Style Multi-Factor Comparable Company Valuation for Practical Use

    Get PDF
    Classical single-factor comparable company valuation (CCV) like e.g. valuation using the price-earnings ratio is associated with several shortcomings. The two most important are the non-applicability of negative values in the basis of reference and the high requirements to the qualitative characteristics of comparable companies. This paper develops a multi-factor CCV model based on substance and performance related accounting attributes that largely overcomes these drawbacks. Additionally, the model allows to depict expected future earnings development economically sounder than single-factor models. Furthermore, by accounting for managements option to adapt firm assets differently or to liquidate the company the model can conclusively assign positive stock prices to currently negatively performing companies

    The Impact of a Stock Market Downturn on Corporate Financing Activities in Germany

    Get PDF
    The paper analyses the potential impact of stock market developments on lending behaviour from different perspectives. First we scrutinize the impact of stock market movements on the banks' and on the borrowers' balance sheets. Subsequently we estimate aggregate credit supply and demand functions including a stock market indicator as explanatory variable. The analysis reveals no major importance of the bank balance sheet channel for the relationship between stock market volatility and corporate financing possibilities of non-financial companies. A possible impact of stock market movements on banks' lending behaviour might be rooted in their impact on the balance sheets of corporate borrowers. The empirical results of the credit market analysis yield some confirming evidence for an impact of stock market developments. However, the results are not very stable and depend on the specification of the model and on the time period under observation

    GPD-linked Bonds as a Financing Tool for Developing Countries and Emerging Markets

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    The paper examines the applicability of GDP-linked bonds for the financing of developing countries and emerging markets. GDP-linked bonds are bonds of which the coupon and/or redemption payments are tied to the GDP of the issuing country. The study encompasses a detailed empirical analysis of their pricing behaviour, the pricing sensitivities to changes in GDP, and of their behaviour in a portfolio context is conducted. A survey amongst potential investors as well as issuing-side capital market participants assesses the prospects of success of this new type of bond. Finally, the usefulness of a partial public guarantee of payments is examined. The paper provides evidence under which circumstances, for which investors and for which countries GDP-linked bonds might be an appropriate investment vehicle

    Quantitative software reliability evaluation covering component interactions

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    In dieser Arbeit wird ein Verfahren vorgestellt, das die Generierung einer optimierten Testfallmenge erlaubt, die sowohl eine quantitative Bewertung der Softwarezuverlässigkeit ermöglicht, als auch gleichzeitig eine hohe Überdeckung der Komponenteninteraktionen gewährleistet. Die Optimierung erfolgte mittels eines entwickelten genetischen Algorithmus, der die drei Ziele Betriebsprofiltreue, statistische Unabhängigkeit und Überdeckung der Komponenteninteraktionen, verfolgt. Die beiden erstgenannten Ziele sind dabei Voraussetzungen für die Anwendung der statistischen Stichprobentheorie, die die Ableitung der gewünschten, quantitativen Zuverlässigkeitsaussage ermöglicht. Diese beiden Ziele werden deshalb auch als KO-Kriterien bezeichnet. Für die Messung des Überdeckungsgrads der Komponenteninteraktionen finden die kopplungsbasierten Testfallkriterien nach Jin&Offutt Verwendung, welche den Datenfluss über Modulgrenzen hinweg erfassen. Der genetische Algorithmus zur Lösung dieses multi-objektiven Optimierungsproblems strebt eine Maximierung dieser Überdeckung an, stellt aber gleichzeitig sicher, dass die KO-Kriterien Betriebsprofiltreue und statistische Unabhängigkeit gewahrt bleiben. Zudem wurden drei Adaptionen der kopplungsbasierten Testkriterien definiert, die z. B. die unterschiedliche Relevanz von Variablen zu berücksichtigen erlauben. Im anschließenden Evaluierungskapitel wird der Ansatz auf einige Beispielprogramme angewendet und gezeigt, dass die gesetzten Optimierungsziele erreicht werden. Zudem erfolgt noch eine Evaluierung des Fehlererkennungspotentials kopplungsbasierter Testfallmengen mittels Mutationstest.This thesis presents an approach for the generation of optimized test case sets allowing for a quantitative evaluation of software reliability as well as ensuring high interaction coverage. The optimization made use of genetic algorithms aiming at the achievement of the following three optimization goals: operational representativeness, independent test case selection and interaction coverage. The two former goals are conditions for the application of statistical sampling theory, which allows for the derivation of a quantitative reliability estimation. These two goals are therefore called KO-criteria. For the measurement of interaction coverage, the coupling-based testing criteria by Jin&Offutt are used, which capture data flow across module boundaries. The genetic algorithm used for solving this multi-objective optimization problem aims at maximizing the coverage without violating any of the KO-criteria operational representativeness and independent test case selection. Furthermore, three adaptations of coupling-based testing are defined, which e. g. take the different relevance of variables into account. In the final chapter, the approach is applied to two software-based systems and the achievement of the optimization goals is shown. Finally, a mutation test demonstrates the benefit of coupling-based testing compared to random testing

    Dealing with historical capital structure volatility in valuation: how to directly estimate unlevered betas

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    Deriving unlevered betas is a standard exercise for valuation professionals when using the Capital Asset Pricing Model (CAPM). In this article we show that the traditional indirect approach (first deriving levered betas, then recalculating them using beta unlevering formulas) can lead to severely wrong results if capital structures are non-stable over time. A better approach is the direct estimation of unlevered betas (first translating each equity return data point into an asset return data point, then running the regression with these „unlevered“ returns). This approach allows to take financial risk properly into account when debt-to-equity ratios are volatile.</p

    Private Equity for Distressed Companies in Germany

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