Corporate Restructuring PT
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Quantitative Methods in Restructuring Management

level of course unit

second cycle, Master

Learning outcomes of course unit

Upon successful completion of the course, students are able to calculate basic statistical parameters (e.g. mean and standard deviation, correlation, distributions) and apply it to business management problems. In addition, students are able to statistically evaluate and test empirical questions

prerequisites and co-requisites

not applicable

course contents

A. Probability Theory:
• Concepts in probability theory
• Continuous / discrete probability and distribution functions
• Position dimensions , measures of dispersion & correlation

B. Specific statistical distributions :
• Binomial distribution
• Hypergeometric distribution
• Poisson distribution
• Normal distribution
• Hypothesis Tests

C. Specific statistical techniques :
• (linear ) regression analysis
• Econometric Time Series Analysis

D. Statistical Applications in insolvency early detection :
• Discriminant analysis
• Logistic Regression
• Neural Networks
• Empirical and theoretical hurdles in connection with statistical methods in the early detection of insolvency

E. Results of empirical research in the area of insolvency early detection :
• Quantitative factors in the insolvency early detection
• Qualitative factors in the insolvency early detection
• Results from selected studies.

recommended or required reading

Situm Mario (2013) Krisenindikatoren und Methoden zur Früherkennung von Unternehmenskrisen. In: Exler, Markus (Hrsg.) Restrukturierungs- und Turnaround-Management, S.269-312, Berlin, Anderson. R. (2007). The Credit Scoring Toolkit: Theory and Practice for Retail Credit Risk Management and Decision Automation. Oxford Krengel, U. (2003). Einführung in die Wahrscheinlichkeitstheorie und Statistik. Wiesbaden Sachs, L. (1997). Angewandte Statistik: Anwendung statistischer Methoden. 8. Auflage. Berlin-Heidelberg Thomas, L. C., Edelman, D. B., & Crook J. N. (2002). Credit Scoring and ist Applications. Philadelphia Johnson, R. A., & Wichern D. W. (1982). Applied Multivariate Statistical Analysis, Englewood Cliffs Krzanowski, W. J., & Marriott, F. H. C. (1995). Multivariate Analysis. Part 2: Classification, Covariance Structures and Repeated Measures. London McDonald, R. L. (2006). Derivatives Markets, Boston Rencher, C. A. (1995). Methods of Multivariate Analysis, New York Salkind, N. (2006). Exploring Research, New Jersey Solnik, B., & McLeavey, D. (2009). Global Investments, Boston

assessment methods and criteria

Written examination or homework

language of instruction

German

number of ECTS credits allocated

3

planned learning activities and teaching methods

Lecture, group work, presentation and task discussion

semester/trimester when the course unit is delivered

1

name of lecturer(s)

Prof. (FH) DDr. Mario Situm

year of study

1.year of studies

recommended optional program components

not applicable

course unit code

B.GLR.1

type of course unit

compulsory (integrated lecture)

mode of delivery

In-class course

work placement(s)

not applicable

Contact

Situm Mario
Prof. (FH) DDr. Mario Situm, MBA
Director of Studies
+43 5372 71819 147
Mario.Situmfh-kufstein.ac.at
questions -  Any
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+43 5372 71819 500
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Internationales Symposium Restrukturierung

Am 25. Oktober 2019 findet das „8. Internationale Symposium Restrukturierung“ an der Fachhochschule Kufstein Tirol statt.

Im Mittelpunkt der Jahreskonferenz 2019 steht das Rahmenthema "Geschäftsmodelle im Wandel". Details finden Sie hier.

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RESTRUKTURIERUNGS-QUALITÄTSSIEGEL FÜR KUFSTEINER MASTERSTUDIENGANG

Der berufsbegleitende Masterstudiengang „Unternehmensrestrukturierung & -sanierung“ ist nach einjähriger Begutachtung offiziell „TMA zertifiziert“ – das renommierte Qualitätssiegel des Verbandes der deutschen Restrukturierungsexperten (TMA).

Weitere Informationen siehe hier.

Restrukturierungs- und Turnaround-Management

ild: Buch Restrukturierungs- und Turnaround- Management