Optimal investment decision making on the model of production enterprise with limited resources
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Author(s)Tetiana IvanenkoLink to ORCID Index: https://orcid.org/0000-0001-7580-8483
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Viktor HrushkoLink to ORCID Index: https://orcid.org/0000-0001-6963-9847
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Anatolii FrantsuzLink to ORCID Index: https://orcid.org/0000-0003-2861-1252
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DOIhttp://dx.doi.org/10.21511/imfi.15(4).2018.05
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Article InfoVolume 15 2018, Issue #4, pp. 61-68
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200 Downloads
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Creative Commons Attribution 4.0 International License
Investments are among the most important factors of national economic growth. Selection of optimal investment project is the first priority for any enterprise with limited financial resources. This study is dedicated to a choice among mutually exclusive projects, which are impossible to complete partially, so, one project must be chosen and all others must be rejected. An investor must find among all possible projects the one that allows to better achieve all investor’s aims. A mathematical model of multi-purpose multi-criteria investor decision making is proposed for investment project selection problem. Efficiency and riskiness of studied projects are evaluated using such indicators as profit, rate of return, payback period, marginal cost of capital, also taking into account subjective characteristics, namely the investor’s attitude towards financial risks, importance assessment of decision making criteria, etc. Decision making assessment methods for the situations of risk and uncertainty are applied to resolve the problem of optimal project selection, such as Wald’s pessimistic criterion, maximax optimistic criterion, as well as Hurwicz’s, Laplace’s, Bayes- Laplace, Hodges-Lehmann criteria, and Savage’s minimax risk criterion. Calculations carried out and results obtained indicate that the best investment project chosen that way will provide the highest absolute profit, despite certain disadvantages such as lower rate of return, longer payback period and higher risk than other projects.
- Keywords
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JEL Classification (Paper profile tab)D81, G11, H43, O22
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References17
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Tables6
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Figures0
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- Table 1. Dynamics of capital investments into the Ukrainian economy in the period 2015–2017
- Table 2. NPV – net present value of projects (thousands UAH)
- Table 3. PI – profitability index of projects
- Table 4. IRR – investment rate of return for projects (%)
- Table 5. DPP – discounted payback period for projects (years)
- Table 6. Estimation of investor strategies and recommendations for choosing alternatives
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Analyzing the Turkish insurance companies’ financial performance traded on BIST implementing the critic-based PIV method
Mehmet Mete Karadağ
doi: http://dx.doi.org/10.21511/ins.15(2).2024.05
Insurance Markets and Companies Volume 15, 2024 Issue #2 pp. 47-60 Views: 66 Downloads: 16 TO CITE АНОТАЦІЯThe insurance industry, which is an important component of the financial channel, is an essential part of the Turkish economy, and assessing the financial performance is critical for insurance companies to improve efficiency and productivity, increase competitiveness, and enhance fiscal health. The study presented a technique for assessing the financial performance of all insurance companies registered in Borsa Istanbul by implementing an integrated method that combines the Criteria Importance Through Intercriteria Correlation (CRITIC) and Proximity Indexed Value (PIV) methods. The rationale for implementing the PIV method is the lack of adequate financial studies available on the insurance companies that employed this specific model. Initially, 18 evaluation criteria were defined. The CRITIC method was applied for the criteria weights, and insurance companies were ranked using PIV. Subsequently, the COPRAS, VIKOR, ARAS, and SAW Multi-Criteria Decision-Making (MCDM) methodologies were applied. Performance rankings derived from PIV were compared with those obtained from other MCDM models employed. Finally, Spearman’s Rank Correlation and Kendall’s Rank Correlation Coefficient methods were applied to analyze the extent of correlations and interactions between ranking outcomes. The PIV assessment results pointed out that AGESA received the highest rank for financial performance, and AKGRT had the lowest rank. AGESA consistently received high rankings compared to all other methods examined. Nevertheless, RAYSG and AKGRT constantly ranked poorly. All deployed methods ranked AKGRT and RAYSG in the final two positions. The study’s findings underscore that ranking outcomes of PIV largely align with alternate MCDM methodologies utilized.
