Reflecting interdependencies between risk factors in corporate risk modeling using Monte Carlo simulation

• Authors: Kaczmarzyk Jan

Title variants

PL

Odzwierciedlanie współzależności pomiędzy czynnikami ryzyka w modelowaniu ryzyka działalności gospodarczej przedsiębiorstwa z wykorzystaniem symulacji Monte Carlo

• Languages of publication: EN

Abstracts

EN

Modern enterprises use various spreadsheet financial models to project their financial situation as well as to address potential entrepreneurial activity risk exposure. The most advanced solution is provided by the Monte Carlo approach that offers much broader possibilities in terms of entrepreneurial risk measurement than in the case of traditional methods. One of the most significant problems of the Monte Carlo approach is to identify, quantify and reflect interdependencies between variables that are risk factors in any risk analysis. The aim of this paper is to discuss possibilities to identify and quantify interdependencies in terms of historical data availability as well as to present a spreadsheet solution that would reflect interdependencies in risk simulation and which would be easy to implement. The solution presented is not the only one available, but it does not require too much effort to be implemented in any financial model developed in the form of a spreadsheet, especially by the individuals responsible for risk management in small and medium sized enterprises.

Keywords

EN

Corporate finance; Risk; Monte Carlo

• Publisher: Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu
• Journal: Econometrics. Ekonometria. Advances in Applied Data Analytics
• Year: 2016
• Issue: 2 (52)
• Pages: 98-107

Contributors

author

Kaczmarzyk Jan

References

• Chapman R., 2006, Simple Tools and Techniques for Enterprise Risk Management, John Wiley & Sons, West Sussex.
• Cherubini U., Luciano E., Vecchiato W., 2004, Copula Methods in Finance, John Wiley & Sons, West Sussex.
• Cruz M.G., 2002, Modeling, Measuring, and Hedging Operational Risk, John Wiley & Sons, West Sussex.
• Gentle J., 2003, Random Number Generation and Monte Carlo Methods. Second Edition, Springer Science+Business Media Inc., New York.
• Hull J., 2015, Risk Management and Financial Institutions, John Wiley & Sons, New Jersey.
• Jäckel P., 2002, Monte Carlo methods in finance, John Wiley & Sons, West Sussex.
• Kaczmarzyk J., 2013, A subjective approach in risk modeling using simulation techniques, Studia Ekonomiczne University of Economics in Katowice, no. 127, pp. 23–34.
• Kaczmarzyk J., Zieliński T., 2010, Metody symulacyjne w poszerzonej analizie wrażliwości, Studia Ekonomiczne University of Economics in Katowice, No. 71, pp. 171–187.
• Korn R., Korn E., Kroisandt G., 2010, Monte Carlo Methods and Models in Finance and Insurance, Chapman & Hall/CRC Press, Boca Raton.
• Krysiak Z., 2008, Wycena a ryzyko, [in:] Panfil M., Szablewski A. (ed.), Metody wyceny spółki. Perspektywa klienta i inwestora, Poltext, Warsaw.
• Merna T., Al-Thani F.F., 2008, Corporate Risk Management, John Wiley & Sons, West Sussex.
• Rogowski W., 2008, Rachunek efektywności inwestycji, Oficyna Ekonomiczna/Wolters Kluwer Polska, Cracow.
• Vose D., 2008, Risk Analysis. A Quantitative Guide, John Wiley & Sons, West Sussex.
• Wilmott P., 2006, Paul Wilmott on Quantitative Finance. Volume 3, John Wiley & Sons, West Sussex.
• Zieliński T., 2010, Ryzyko na rynku finansowym, [in:] Pyka I. (ed.), Rynek finansowy, Akademia Ekonomiczna w Katowicach, Katowice.