Determination of the Risk-free Rate of Return on an Investment Efficiency Based on the Fractal Markets Hypothesis
In determining the economic efficiency of an investment project, the rationale and choice of the discount rate is the most difficult step. The methods of investment assessment are built on the rate of return used to discount future cash flows back to their present value. To increase the accuracy of calculations and reduce the subjective assessments of experts, statistical methods are used. The market process is known to be stochastic. Therefore, investors know that the application of statistical methods is not practical, and thus prefer to use their intuition and professional experience. The alternative group of methods such as the Fractal Markets Hypothesis is not widely used because it is difficult to carry out calculations according to the proposed formulas in practice. In this paper, the aim is to propose a method for determining the risk-free rate of return on an investment project based on the Fractal Markets Hypothesis for identifying long-term dependence and assessing the contribution to the total result of changes in inflation. The objective of the study is the determination of the risk-free rate of return on an investment project. The real risk-free rate is calculated as the existing inflation rate. The result of this paper is the definition of inflation boundaries for Poland, Ukraine and Russia, which may be used for determining the risk-free rate of return on an investment project. (original abstract)
- Miratech, Inc., New York, United States
- University of State Fiscal Service of Ukraine, Irpin, Ukraine
- Vasyl' Stus Donetsk National University, Vinnytsia, Ukraine
- Chernihiv National University of Technology, Chernihiv, Ukraine
- Zhytomyr National Agroecological University, Zhytomyr, Ukraine
- Donetsk Law Institute of the Ministry of Internal Affairs of Ukraine, Kryvyi Rih, Ukraine
- Ackerer, D., Filipović, D. (2020), Linear credit risk models, Finance and Stochastics, 24, 169-214. https://doi.org/10.1007/s00780-019-00409-z
- Adrian, T., Estrella, A., Song Shin, H. (2018), Risk-taking channel of monetary policy, Financial Management, 48(3), 725-738. https://doi.org/10.1111/fima.12256
- Antonacci, G. (2014), Dual momentum investing: An innovative strategy for higher returns with lower risk. McGraw-Hill Education, N.J.
- Bali, T., Zhou, H. (2016), Risk, uncertainty, and expected returns, Journal of Financial and Quantitative Analysis, 51(3), 707-735. https://doi.org/10.1017/S0022109016000417
- Bernholz, P. (2016), Monetary regimes and inflation: History, economic and political relationships, Cheltenham: Edward Elgar Publishing.
- Chiara F. Del Bo. (2016), The rate of return to investment in R&D: The case of research infrastructures, Technological Forecasting and Social Change, 112, 26-37. https://doi.org/10.1016/j.techfore.2016.02.018
- Crayton, L.A. (2016), Inflation: What it is and how it works (Economics in the 21st Century), Berkeley Heights, NJ: Enslow Pub Inc.
- Fisher, I. (2018), The theory of interest as determined by impatience to spend income and opportunity to invest it blurb, San Francisco, CA: Martino Fine Books.
- Graham, B., Zweig, J., Buffett, W.E. (2006), The intelligent investor: The definitive book on value investing. A book of practical counsel (revised edition), New York: Harper Business.
- Hadhri, S., Ftiti, Z. (2019), Asset allocation and investment opportunities in emerging stock markets: Evidence from return asymmetry-based analysis, Journal of International Money and Finance, 93,187-200. https://doi.org/10.1016/j.jimonfin.2019.01.002
- Hašková, S., Fiala, P. (2019), A fuzzy approach for the estimation of foreign investment risk based on values of rating indices, Risk Management, 21, 183-199. https://doi.org/10.1057/s41283-019-00051-1
- Ilina, I., Streltsova, E., Borodin, A., Yakovenko, I. (2019), The impact of public investment on the competitiveness of the Russian R&D sector, International Journal of Mechanical Engineering and Technology, 10(1), 1128-1140.
- Ivanisevic, A., Losonc, A., Radisic, M., Njegovan, M., Pavlovic, A. (2020), Development of an effective planning model for improving financial performance, Forum Scientiae Oeconomia, 8(1), 67-81. https://doi.org/10.23762/FSO_VOL8_NO1_5
- Ingolfsson, A., Almehdawe, E., Pedram, A., Tran, M. (2020), Comparison of fluid approximations for service systems with state-dependent service rates and return probabilities, European Journal of Operational Research, 283(21), 562-575. https://doi.org/10.1016/j.ejor.2019.11.041
- International Monetary Fund. Inflation rate, average consumer prices, retrieved from: https://www.imf.org/external/datamapper/PCPIPCH@WEO/OEMDC/ (accessed 1 February 2020))
- Jackowicz, K., Kozłowski, Ł., Mielcarz, P., (2016), Financial constraints in Poland: The role of size and political connections, Argumenta Oeconomica, 36, 225-239. DOI: 10.15611/aoe.2016.1.09
- Kaletnik, G.M., Zabolotnyi, G.M., Kozlovskyi, S.V. (2011), Innovative models of strategic management economic potential within contemporary economic systems, Actual Problems of Economics, 4(118), 3-11.
- Koziuk, V., Hayda, Y., Dluhopolskyi, O., Klapkiv, Y. (2019), Stringency of environmental regulations vs. global competitiveness: Empirical analysis, Economics and Sociology, 12(4), 264-284. DOI: 10.14254/2071-789X.2019/12-4/17
- Kozlovskyi, V., Gerasymenko, Y. Kozlovskyi, S. (2010), Conceptual grounds for construction of support system for investment decision-making within agroindustrial complex of Ukraine, Actual Problems of Economics, 5(107), 263-275.
- Matthew, E. (2019), Pricing flexibility under rate-of-return regulation: Effects on network infrastructure investment, Economic Modelling, 78, 150-161. DOI: 10.1016/j.econmod.2018.09.016
- Mansour, A., Ahmi, A., Popoola, A. (2020), The personality factor of conscientiousness on skills requirement and fraud risk assessment performance, International Journal of Financial Research, 11(2), 405-415. https://doi.org/10.5430/ijfr.v11n2p405
- Mykhayliv, D., Zauner, K. (2017), The impact of equity ownership groups on investment: Evidence from Ukraine, Economic Modelling, 64, 20-25. DOI: 10.1016/j.econmod.2017.03.005
- Peters, E.E. (1994), Fractal market analysis: Applying chaos theory to investment and economics (1st edition), Hoboken, NJ: Wiley.
- Peters, E.E. (1996), Chaos and order in the capital markets: A new view of cycles, prices, and market volatility (2nd edition), Hoboken, NJ: Wiley.
- Piterbarg, V. (2018), The optimal investment problem in stochastic and local volatility models, Journal of Investment Strategies, 7(4), 1-25. https://doi.org/10.21314/JOIS.2018.104
- Prokopenko, O., Shmorgun, L., Kushniruk, V., Prokopenko, M., Slatvinska, M., Huliaieva, L. (2020), Business process efficiency in a digital economy, International Journal of Management, 11(3), 122-132.
- Raimundo, M.S., Okamoto, J.Jr. (2018), Application of Hurst Exponent (H) and the R/S analysis in the classification of FOREX securities, International Journal of Modeling and Optimization, 8(2), 116-124. DOI: 10.7763/IJMO.2018.V8.635
- Shaikh, Y.H., Rabbani, G. (2014), Gold price data analysis using rescaled range (R/S) analysis, International Journal of Economics, 4(1), 7-14.
- Shearn, M. (2011), The investment checklist: The art of in-depth research, Hoboken, NJ: Wiley Finance.
- Smit, S., Polakow, D. (2018), The global currency tango - the relationship between the carry trade, emerging/commodity currencies and risk, Investment Analysts Journal, 47(4): 285-303. https://doi.org/10.1080/10293523.2018.1485217
- Spier, G. (2014), The education of a value investor: My transformative quest for wealth, wisdom, and enlightenment, New York: St. Martin's Press.
- Steinberg, D.A. (2015), Demanding devaluation: Exchange rate politics in the developing world. Cornell studies in money, Ithaca: Cornell University Press.
- Stukalo, N., Simakhova, A., Shmarlouskaya, H. (2019), Special features of formation of the source base for economic socialization, Problems and Perspectives in Management, 17(3), 271-279. http://dx.doi.org/10.21511/ppm.17(3).2019.22
- Szetela, B., Mentel, G., Mentel, U., Bilan, Y. (2020), Directional movement distribution in the bitcoin markets, Inzinerine Ekonomika-Engineering Economics, 31(2), 188-196. https://doi.org/10.5755/j01.ee.31.2.25162
- Tițan, A. (2015), The efficient market hypothesis: review of specialized literature and empirical research, Procedia Economics and Finance, 32, 442-449. https://doi.org/10.1016/S2212-5671(15)01416-1
- Turkington, D., Yazdani, A. (2020), The equity differential factor in currency markets. Financial Analysts Journal, 76(2), 70-81. DOI: 10.1080/0015198X.2020.1712924
- Uthayakumar, P., Jayalalitha, G. (2014), A comparison of fractal dimension algorithms by Hurst exponent using gold price time series, International Journal for Research in Applied Science & Engineering Technology, 6(2), 1210-1215.
- Yousuf, A., Haddad, H., Pakurar, M., Kozlovskyi, S., Mohylova, A., Shlapak, O., Janos, F. (2019), The effect of operational flexibility on performance: A field study on small and medium-sized industrial companies in Jordan, Montenegrin Journal of Economics, 15(1), 47-60. DOI: 10.14254/1800-5845/2019.15-1.4
- Zhou, L., Wang, Q. (2018), Decision-maker's risk preference based intuitionistic fuzzy multiattribute decision-making and its application in robot enterprises investment, Mathematical Problems in Engineering, 1-6. DOI: 10.1155/2018/1720189