Advertisement

The Issue of Investment Decision-Making of Leveraged Projects

  • Lucia Michalkova
  • Erika Spuchlakova
Conference paper
Part of the Springer Proceedings in Business and Economics book series (SPBE)

Abstract

Investment decision-making is based on many criteria and analysis. Currently, the projects imposed many requirements that are often in mutual contradiction or project is very risky. One example for increasing risk of the project is a financing by debt. The paper is focused on the issue of leveraged projects, because their valuation is different from the valuation of projects financed merely by equity, and an existence of some financial effects of leverage affects financial decision-making. Hence, a general method of quantification of net present value and adjusted net present value is described. Next, it is focused on sensitivity analysis as a one of the steps of risk analysis. The aim of the paper is to analyse the net present value of the certain leveraged project, make a sensitivity analysis of the project and identify significant factors that affect the project value. Finally, there are mentioned some weaknesses of sensitivity analysis and other methods used for risk analysis.

Abstract

Nowadays companies all over the world face the consequences caused by the financial crisis. Almost every one of them must be financed by debt, and one of the goals of the company is often to decrease risk (Corejova et al. 2014). Also it is difficult for any company to choose the variant of the offered investment opportunities that it will bring the most benefit, whether it is a short-term or long-term investment decision (Dengov and Gregova 2010). A second former is characterized by a high involvement of decision-makers on the outcome of the decision. Therefore, the decision should include attitudes, opinions and judgments of the decision-maker, but it should be an outcome of an objective assessment of the decision situation (Grublova 2010).

Keywords

Adjusted net present value Sensitivity analysis Leverage Tax shield 

Notes

Acknowledgement

The paper is an output of the science project VEGA 1/0428/17 Creation of New Paradigms of Financial Management at the Threshold of the 21st Century in Conditions of the Slovak Republic.

References

  1. Bartošová, V., Majercak, P., & Hraskova, D. (2015). Taking risk into account in the evaluation of economic efficiency of investment projects: Traditional methods. Procedia Economics and Finance, 24, 68–75. Elsevier Publisher.CrossRefGoogle Scholar
  2. Brealey, R. A., Myers, S. C., & Allen, F. (2010). Principles of corporate finance (10th ed.). New York: McGraw-Hill/Irwin.Google Scholar
  3. Buc, D., & Kliestik, T. (2013). Aspects of statistics in terms of financial modelling and risk. In: 7th International Days of Statistics and Economics, Prague, Czech Republic (pp. 215–224).Google Scholar
  4. Cisko, S., & Kliestik, T. (2013). Financny manazment podniku II. Zilina: EDIS Publishing.Google Scholar
  5. Corejova, T., Bachanova, P. H., & Mockova, M. (2014). Industry and business study of architecture in terms of the Zilina Region. In: Nijkamp, P., Kourtit, K., Bucek, M., Hudec, O. (Eds.), CERS 2014: 5th Central European Conference in Regional Science, Kosice, Slovakia, 05–08 October 2014 (pp. 125–135).Google Scholar
  6. Damodaran, A. (2002). Investment valuation: Tools and technique for determining the value of any asset (2nd ed.). New York: Wiley.Google Scholar
  7. Dengov, V. V., & Gregova, E. (2010). Economic decision-making under uncertainty and risk. Methodology and criteria for decision-making. Ekonomicko-manazerske spektrum, 4(2), 28–45.Google Scholar
  8. Dinh, T. T. H. (2016). Evaluating the decision-making on a Public-Private Partnership to finance a road project in Vietnam. Journal of International Studies, 9(3), 124–137.  10.14254/2071-8330.2016/9-3/10.CrossRefGoogle Scholar
  9. Dluhosova, D. (2010). Financni rizeni a rozhodovani podniku: analyza, investovani, ocenovani, riziko, flexibilita (3rd ed.). Praha: Ekopress.Google Scholar
  10. Gazdikova, J., & Sustekova, D. (2009). Selected statistical tools for financial analysis. Ekonomicko-manazerske spectrum, 3(2), 8–11.Google Scholar
  11. Grublova, E. (2010). Attitudes to risk and ability to take risky decisions. Ekonomicko-manazerske spectrum, 4(2), 58–63.Google Scholar
  12. Kliestik, T., Lyakin, A. N., & Valaskova, K. (2014a) Stochastic Calculus and Modelling in Economics and Finance. In: 2nd International Conference on Economics and Social Science (ICESS), Advances in Education Research, Shenzhen, China, Vol 61 (pp. 161–167).Google Scholar
  13. Kliestik, T., Misankova, M., & Adamko, P. (2014b). Sensitivity analysis of credit risk models based on Greeks. In: 2nd International Conference on Management Innovation and Business Innovation (ICMIBI 2014), Lecture Notes in Management Science, Bangkok, Thailand, Vol. 44 (pp 99–104).Google Scholar
  14. Kral, P., & Kliestik, T. (2015). Estimation of the level of risk based on the selected theoretical probability distributions. In: 10th International Scientific Conference Financial management of Firms and Financial Institutions, Ostrava, Czech Republic (pp. 603–610).Google Scholar
  15. Lehutova, K., Krizanova, A., & Kliestik, T. (2013). Quantification of equity and debt capital costs in the specific conditions of transport enterprises. In: 17th International Conference on Transport Means, Transport Means, Proceedings of the International Conference, Kaunas, Lithuania (pp. 258–261).Google Scholar
  16. Luehrman, T. A. (1997). Using APV: A better tool for valuing operations. Harvard Business Review, 75(3), 145–154.Google Scholar
  17. Myers, S. C. (1974). Interactions of corporate financing and investment decisions implications for capital budgeting. Journal of Finance, 29(1), 1–25.CrossRefGoogle Scholar
  18. Valaskova, K., Kramarova, K., & Bartošová, V. (2015). Multi criteria models used in Slovak consumer market for business decision making. Procedia Economics and Finance, 26, 174–182, Elsevier Publisher.CrossRefGoogle Scholar
  19. Vochozka, M. (2010). Development of methods for comprehensive evaluation of business performance. Politicka Ekonomie, 58(5), 675–688.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of EconomicsUniversity of Zilina, Faculty of Operation and Economics of Transport and CommunicationsZilinaSlovak Republic

Personalised recommendations