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Relevant bibliographies by topics / Rate of return

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Academic literature on the topic 'Rate of return'

Author: Grafiati

Published: 4 June 2021

Last updated: 29 July 2024

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Journal articles on the topic "Rate of return"

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Okechukwu, Izunobi Anthony, Nzotta Samuel Mbadike, Ugwuanyim Geoffrey, and Benedict Anayochukwu Ozurumba. "Effects of Exchange Rate, Interest Rate, and Inflation on Stock Market Returns Volatility in Nigeria." INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE AND BUSINESS ADMINISTRATION 5, no. 6 (2019): 38–47. http://dx.doi.org/10.18775/ijmsba.1849-5664-5419.2014.56.1005.

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This study employed GARCH (1.1) techniques to evaluate the existence of high stock market returns volatility, and the impact of the exchange rate, interest rate and inflation on stock market returns in Nigeria, using monthly series data from 1995 – 2014. Excessive volatility hinders the stock market from playing its role of Mobilizing, financial resources from surplus units to deficit units and may cause a financial crisis. The research finding shows that interest rate has a negative relationship with stock market returns, while the inflation rate and exchange rate have a positive relationship with stock market returns. The conclusion therefore is, there is high and persistent volatility in the Nigerian stock market returns. Exchange rate, interest rate, and inflation significantly impact stock market return volatility in Nigeria. The study recommends that regulatory authorities should take proactive steps to minimize stock market return in order to restore confidence in the market.

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Valach, Josef. "Internal Rate of Return or Modified Internal Rate of Return." Český finanční a účetní časopis 2013, no. 3 (October 1, 2013): 114–21. http://dx.doi.org/10.18267/j.cfuc.375.

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Cornelius, Frederick J. "Calculating Returns: Different Rate of Return Formulae = Different Results." CFA Digest 32, no. 2 (May 2002): 71–72. http://dx.doi.org/10.2469/dig.v32.n2.1079.

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Ze-To, Samuel Y. M. "Expected Stock Returns and Option-Implied Rate of Return." Journal of Mathematical Finance 02, no. 04 (2012): 169–279. http://dx.doi.org/10.4236/jmf.2012.24030.

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Mariam Mathews, Merry. "Mathematics of Finance: Internal Rate of Return (IRR)." International Journal of Science and Research (IJSR) 12, no. 12 (December 5, 2023): 863–64. http://dx.doi.org/10.21275/sr231209195431.

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Poudel, Min Raj. "Survey on Rate of Return on Investment in Education." Interdisciplinary Research in Education 7, no. 1 (September 5, 2022): 129–46. http://dx.doi.org/10.3126/ire.v7i1.47505.

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The rate of return to education is the sum of discounted benefits and costs. It shows the relatively profitable sector for a secure investment. The main objective of this study is to review and analyze the volume of the rate of return to education. The literature review, survey design was used, and the materials were collected using purposive sampling. The analysis concludes that the rate of return on education can be analyzed based on the additional year of schooling, sex, levels of education, occupations, geographical regions, countries, and sectors. Different studies conducted in different countries reveal that the size of the rate of return differs according to the categories mentioned above. It means that overall returns to education seem highly heterogeneous. Likewise, most studies show that the private rate of returns for females is higher than that of males; the tertiary level's returns are higher than the other levels, and the urban sector's returns are higher than that of the rural sector.

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Burnham, Laurie. "High Rate of Return." Scientific American 259, no. 6 (December 1988): 22–23. http://dx.doi.org/10.1038/scientificamerican1288-22b.

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Shultz, Harris S. "Internal Rate of Return." Mathematics Teacher 98, no. 8 (April 2005): 531–33. http://dx.doi.org/10.5951/mt.98.8.0531.

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The Principles and Standards for School Mathematics (NCTM 2000, pp. 65–66) states, “School mathematics experiences at all levels should include opportunities to learn about mathematics by working on problems arising in contexts outside of mathematics. These connections can be to other subject areas and disciplines as well as to students' daily lives.” In this article we shall see that the discipline of finance can provide rich real–life applications of mathematics.

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Zhang, Guangfeng, Qiong Zhang, and Muhammad Tariq Majeed. "Exchange Rate Determination and Forecasting: Can the Microstructure Approach Rescue Us from the Exchange Rate Disparity?" ISRN Economics 2013 (December 18, 2013): 1–12. http://dx.doi.org/10.1155/2013/724259.

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Using two measures of private information and high-frequency transaction data from the leading interdealer electronic broking system Reuters D2000-2, we examine the association between exchange rate return and contemporaneous order flow and the predictability power of lagged order flow on the future exchange rate return. Our empirical analysis demonstrates that at high frequency (5, 10, 15, 20, 25, and 30 min) there exists strong positive association between exchange rate returns and contemporaneous order flow. However, the results indicate weak predictability of order flow on the future exchange rate return.

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Roenganan, Sorrawee, Masnita Misran, and Nattakorn Phewchean. "A Study of Life Internal Rate of Return." WSEAS TRANSACTIONS ON MATHEMATICS 20 (April 2, 2021): 122–33. http://dx.doi.org/10.37394/23206.2021.20.13.

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Life insurance, not included as a part of the legal obligation in some countries, is one of the investment approaches that might not stand high in the public favor for some people since this is a type of investments that the investor cannot know beforehand the exact return, and the returns completely depend on uncertainty of the policy specification in some circumstances. Similar to the other kinds of investment, investors in life insurance products have been seeking a tool for investment evaluation. However, currently there are no accurate tools that can provide the value of the investment in a life insurance product sensitive to the uncertainty. Internal rate of return is the basic tool that buyers or bankers may apply in order to find the rate of return of this type of investment. The investment decision tool is one of the most important keys that investors have utilized upon making their decisions on investments. Therefore, in this research, we propose a new mathematical model with applications for investment decision, being an extension of the internal rate of return by taking into account the life probability, considering different types of life insurance policies, and other factors specified on life insurance investments such as the premium, the death benefit, the maturity value, the sum insured, the lapse rate, the surrender value, the annuity certain, and the lapse rate with different genders and ages. This newly proposed model is named as the "Life Internal Rate of Return" or Life-IRR model. By using the sample data for both males and females aged 30 years old with expected benefit of 100,000 baht for different types of life insurance policies which are endowment plan, whole life plan and retirement plan, the results show that, for males, the highest life rate of returns is that obtained from the retirement plan (3.633692%), and the lowest life internal rates of returns is that obtained from the endowment plan (2.384443%), while the whole life plan offers moderate life rate of returns of 2.427941%. For females, the highest life rate of returns is that obtained from the retirement plan (3.335189%), and the lowest life internal rates of returns is that obtained from the whole life plan (2.104658%), while the endowment plan offers moderate life rate of returns of 2.308062%. The sensitivity analyses of the life internal rates of return perform the natural characteristics of life insurance.

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Dissertations / Theses on the topic "Rate of return"

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Stettler, Martin. "Statistische Betrachtungen zur Non-Return-Rate von Prüfstieren /." [S.l : s.n.], 1987. http://www.ub.unibe.ch/content/bibliotheken_sammlungen/sondersammlungen/dissen_bestellformular/index_ger.html.

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Bigham, Joshua D. "Return on investment in the public sector /." Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2004. http://library.nps.navy.mil/uhtbin/hyperion/04Dec%5FBigham.pdf.

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Vigoles, Anna Frances. "Empirical aspects of the rate of return to education." Thesis, University of Newcastle Upon Tyne, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.262921.

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Kim, Young Do. "Return distributions and applications." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2007. http://wwwlib.umi.com/cr/ucsd/fullcit?p3266772.

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Thesis (Ph. D.)--University of California, San Diego, 2007.
Title from first page of PDF file (viewed August 7, 2007). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references.

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Homer, Jason B. "Collecting, retrieving and analyzing Knowledge Value Added (KVA) data from U.S. navy vessels afloat." Thesis, Monterey, California : Naval Postgraduate School, 2009. http://edocs.nps.edu/npspubs/scholarly/theses/2009/Sep/09Sep%5FHomer.pdf.

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Thesis (M.S. in Information Warfare Systems Engineering)--Naval Postgraduate School, September 2009.
Thesis Advisor(s): Housel, Thomas J. ; Bergin, Richard D. "September 2009." Description based on title screen as viewed on November 9, 2009. Author(s) subject terms: ROI, return on investment, ROA, return on asset, IT ROI, IT performance, IT valuation, KVA, Knowledge Value Added, public sector finance. Includes bibliographical references (p. 65). Also available in print.

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Wong, Po-shing. "Some mixture models for the joint distribution of stock's return and trading volume /." [Hong Kong] : University of Hong Kong, 1991. http://sunzi.lib.hku.hk/hkuto/record.jsp?B13009485.

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Kotze, Gerrit. "Commercial property : a required rate of return investigation / Gerrit Kotze." Thesis, North-West University, 2005. http://hdl.handle.net/10394/1202.

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When faced with an investment opportunity in commercial real estate, the investor requires knowledge of the discount rate since it can be used to convert expected future cash flows from the property in today's terms and in doing so, place a value on the property. The so-called required rate of return would be the appropriate conversion rate since it compensates the investor for risk and, if attainable, will induce the investor to invest. An inaccurate assessment of the discount rate could, depending on the direction of the error, lead to a potential over or under estimation of the property value. A number of single or multiple variable frameworks for required return have been derived by other researchers for the US, UK and EU property markets. Each of the variables encountered in these frameworks acts as a proxy for some aspect of systematic risk associated with the investment. However, locally, such models are either not extensively published or well described and are limited to single explanatory variables. Some professionals prefer to avoid frameworks and simply divert to qualitative, gut-feel and experienced based considerations in order to derive at required return rate. This dissertation addressed the possible local need for an explanatory framework of required return on commercial property. The scope of work entailed: (i) a review of the literature to establish the theoretical determinants of return and (ii) an empirical study to test a short-list of parameters for Retail, Offices and Industrial sites in Cape Town, Pretoria, Bloemfontein and Durban, respectively. Three categories of explanatory variables were identified: (i) Capital market variables and alternative investment opportunities in the form of stocks on the JSE, (ii) economic activity indicators and (iii) property market fundamental parameters. The empirical study entailed a three-phase methodology, which included the following steps: (i) data sampling and processing, (ii) screening variables through the simple regression and correlation coefficients and (iii) multiple regression complemented by statistical significance testing. Between 69% and 98.2 % (alpha=O.1) of the variation in returns could be explained in terms of the variation by the explanatory variables that passed the rigorous screening process. The relative good results are likely to be related to the higher explanatory power of the multi-factor approach. The remaining unexplained portion of return can potentially be decreased by using larger samples and pursuing some of the other recommendations for additional research.
Thesis (M.B.A.)--North-West University, Potchefstroom Campus, 2006.

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Åkerström, Paul Linus Martin. "RETURN PATTERNS PROXIMAL TO CENTRAL BANK RATE DECISION ANNOUNCEMENTS : OMX 30 excess return and monetary policy announcements." Thesis, Stockholms universitet, Finansiering, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-105824.

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In this study, it is determined that excess returns on the OMX 30 are confirmed to rise in anticipation of monetary policy decisions made by the central banks of Sweden and The United States of America. Those findings were manifested at a greater magnitude on the first day prior to the announcements and on a statistically significant level one day prior to monetary policy decisions from the Federal Open Market Committee. Moreover, excess returns beyond the average rate were found to be substantially higher on the first and third day prior monetary policy decisions from the Swedish Central bank (Riksbanken) albeit not on a statistically significant level. The results drawn from the data in the study were reinforced by findings in similar tests conducted during times of global recession.

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Zhang, Jie. "Two essays on empirical asset pricing : 1. Forecasted earnings per share and the cross section of expected returns and 2. The limits to arbitrage and the fundamental value-to-price trading strategies /." View abstract or full-text, 2006. http://library.ust.hk/cgi/db/thesis.pl?FINA%202006%20ZHANG.

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Lee, John Byong Tek. "Higher idiosyncratic moments and the cross-section of expected stock returns /." Thesis, Connect to this title online; UW restricted, 2008. http://hdl.handle.net/1773/8710.

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Books on the topic "Rate of return"

1

Thompson, Robert B. Return on investment. 4th ed. Saranac Lake, N.Y: American Management Association, 1994.

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Oulton, Nicholas. The social rate of return to investment. London: National Institute of Economic and Social Research, 1996.

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Plewa, Franklin James. Keys to improving your return to investment (ROI). New York: Barrons, 1991.

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Scott, David Logan. Understanding and managing investment risk & return. Chicago, Ill: Probus Pub., 1990.

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Canning, David. The social rate of return on infrastructure investments. Washington, DC (1818 H St., NW, Washington 20433): World Bank, Development Research Group, Public Economics, 2000.

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Bekaert, Geert. International stock return comovements. Cambridge, Mass: National Bureau of Economic Research, 2005.

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Cummins, J. David, and Scott E. Harrington, eds. Fair Rate of Return in Property-Liability Insurance. Dordrecht: Springer Netherlands, 1987. http://dx.doi.org/10.1007/978-94-015-7753-3.

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Collins, Brett. On calculating the break-even rate of return. Melbourne: University of Melbourne. Graduate School of Management, 1988.

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David, Cummins J., and Harrington Scott E, eds. Fair rate of return in property-liability insurance. Boston: Kluwer-Nijhoff Pub., 1987.

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Hetherington, Bill. Estimating the rate of return for gas transportation. London: Office of Gas Supply, 1992.

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Book chapters on the topic "Rate of return"

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Hagemann, Harald. "Internal rate of return." In Capital Theory, 195–99. London: Palgrave Macmillan UK, 1990. http://dx.doi.org/10.1007/978-1-349-20861-6_16.

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Magni, Carlo Alberto. "Internal Rate of Return." In Investment Decisions and the Logic of Valuation, 487–554. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-27662-1_9.

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Hagemann, Harald. "Internal Rate of Return." In The New Palgrave Dictionary of Economics, 6692–95. London: Palgrave Macmillan UK, 2018. http://dx.doi.org/10.1057/978-1-349-95189-5_798.

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Hagemann, Harald. "Internal Rate of Return." In The New Palgrave Dictionary of Economics, 1–4. London: Palgrave Macmillan UK, 1987. http://dx.doi.org/10.1057/978-1-349-95121-5_798-1.

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Hagemann, Harald. "Internal Rate of Return." In The New Palgrave Dictionary of Economics, 1–4. London: Palgrave Macmillan UK, 2008. http://dx.doi.org/10.1057/978-1-349-95121-5_798-2.

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Thompson, Howard E. "Beyond Rate of Return Regulation." In Regulatory Finance, 213–22. Boston, MA: Springer US, 1991. http://dx.doi.org/10.1007/978-1-4615-3948-3_15.

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Magni, Carlo Alberto. "Average Internal Rate of Return." In Investment Decisions and the Logic of Valuation, 415–86. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-27662-1_8.

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Ruegg, Rosalie T., and Harold E. Marshall. "Internal Rate-of-Return (IRR)." In Building Economics: Theory and Practice, 67–78. Boston, MA: Springer US, 1990. http://dx.doi.org/10.1007/978-1-4757-4688-4_5.

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Ruegg, Rosalie T., and Harold E. Marshall. "Overall Rate-of-Return (ORR)." In Building Economics: Theory and Practice, 79–91. Boston, MA: Springer US, 1990. http://dx.doi.org/10.1007/978-1-4757-4688-4_6.

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Mishan, E. J., and Euston Quah. "The internal rate of return." In Cost-Benefit Analysis, 121–24. Sixth edition. | Milton Park, Abingdon, Oxon ; New York : Routledge, 2020.: Routledge, 2020. http://dx.doi.org/10.4324/9781351029780-24.

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Conference papers on the topic "Rate of return"

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Krishnamurthy, Prashant, P. Balasubramanian, and Deepti Mohan. "Study on relationship between exchange rate return and various stock indices returns." In 2017 International Conference on Data Management, Analytics and Innovation (ICDMAI). IEEE, 2017. http://dx.doi.org/10.1109/icdmai.2017.8073533.

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Terry, R. E., and M. P. Ehman. "Internal Rate of Return: Friend or Foe?" In SPE Hydrocarbon Economics and Evaluation Symposium. Society of Petroleum Engineers, 1985. http://dx.doi.org/10.2118/13771-ms.

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Limani, Ramadan. "Internal Rate of Return and Corresponding Effective Interest Rate for Loans." In University for Business and Technology International Conference. Pristina, Kosovo: University for Business and Technology, 2017. http://dx.doi.org/10.33107/ubt-ic.2017.260.

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Emrich, C., D. Shaw, S. Reasoner, and D. Ponto. "Codell Restimulations Evolve to 200% Rate of Return." In SPE Production and Operations Symposium. Society of Petroleum Engineers, 2001. http://dx.doi.org/10.2118/67211-ms.

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Yuan, Yifei. "Analysis of Influencing Factors of Stock Return Rate." In International Conference on Data Analysis and Machine Learning. SCITEPRESS - Science and Technology Publications, 2023. http://dx.doi.org/10.5220/0012801600003885.

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Inoma, Akitoshi. "A New Project Evaluation Tool —Risked Rate of Return." In SPE Asia Pacific Conference on Integrated Modelling for Asset Management. Society of Petroleum Engineers, 2000. http://dx.doi.org/10.2118/59456-ms.

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Chen, Jiajia. "Relationships between Return of Stock Price Index and Interest Rate." In 8th International Conference on Management and Computer Science (ICMCS 2018). Paris, France: Atlantis Press, 2018. http://dx.doi.org/10.2991/icmcs-18.2018.84.

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Malchev, Bojan. "Financial Performance Indicators and Stock Returns: A Decade-Long Analysis of MBI10 Firms in North Macedonia." In Economic and Business Trends Shaping the Future. Ss Cyril and Methodius University, Faculty of Economics-Skopje, 2023. http://dx.doi.org/10.47063/ebtsf.2023.0008.

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This paper investigates the relationship between financial performance indicators and annual stock returns of the MBI10 companies in North Macedonia over a ten-year period from 2013 to 2022. A total of 100 observations from the Macedonian stock market index (MBI10) are analyzed, using audited financial statements as the primary data source. The financial performance indicators studied include Return on Assets (ROA), Return on Equity (ROE), Earnings per Share (EPS), and Dividend per Share (DPS). A multiple linear regression model is applied to examine the impact of these indicators on annual stock returns, with the model estimated through ordinary least squares (OLS) estimation. The research tests four hypotheses, aiming to establish significant positive relationships between ROA and Stock Return, as well as EPS and Stock Return. The results confirm the hypotheses related to ROA and EPS, with significant positive impacts on Stock Return. However, the relationships between ROE, DPS, and Stock Return lack statistical significance. The findings suggest that the financial performance indicators considered in this study only account for a limited proportion (4.9%) of the variations in Stock Return, indicating the influence of other essential factors not included in the model. To enhance the reliability of the findings, a robustness check was conducted by introducing two control variables: Macedonian GDP annual real growth rates, and DAX30 Index annual rate of return. The regression model, including these control variables, exhibited almost the same results as the model without them. Furthermore, the model with the control variables demonstrated a slightly higher Adjusted R Square value (0.058) compared to the model without them (0.049), implying a slightly improved explanatory power.This study highlights the complexities of the Macedonian stock market and emphasizes the importance of investigating additional factors that significantly contribute to stock price movements and returns in this specific market context.

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Gisin, V. B., and E. S. Volkova. "Internal rate of return of investment projects with fuzzy interactive payments." In 2017 XX IEEE International Conference on Soft Computing and Measurements (SCM). IEEE, 2017. http://dx.doi.org/10.1109/scm.2017.7970705.

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Yu, J. P. "Simulation Approach in Risk-Weighted Cash Flow Rate of Return Determination." In SPE Annual Technical Conference and Exhibition. Society of Petroleum Engineers, 1986. http://dx.doi.org/10.2118/15557-ms.

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Reports on the topic "Rate of return"

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Jordà, Òscar, Katharina Knoll, Dmitry Kuvshinov, Moritz Schularick, and Alan Taylor. The Rate of Return on Everything, 1870–2015. Cambridge, MA: National Bureau of Economic Research, December 2017. http://dx.doi.org/10.3386/w24112.

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Genesove, David, and Wallace Mullin. Predation and Its Rate of Return: The Sugar Industry, 1887-1914. Cambridge, MA: National Bureau of Economic Research, May 1997. http://dx.doi.org/10.3386/w6032.

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Heckman, James, Seong Hyeok Moon, Rodrigo Pinto, Peter Savelyev, and Adam Yavitz. The Rate of Return to the High/Scope Perry Preschool Program. Cambridge, MA: National Bureau of Economic Research, November 2009. http://dx.doi.org/10.3386/w15471.

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Schankerman, Mark. Revisions and Investment Plans and the Stock Market Rate of Return. Cambridge, MA: National Bureau of Economic Research, December 1991. http://dx.doi.org/10.3386/w3937.

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Abel, Andrew. On the Invariance of the Rate of Return to Convex Adjustment Costs. Cambridge, MA: National Bureau of Economic Research, December 2001. http://dx.doi.org/10.3386/w8635.

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Abel, Andrew B. On the Invariance of the Rate of Return to Convex Adjustment Costs. Cambridge, MA: National Bureau of Economic Research, December 2001. http://dx.doi.org/10.3386/w8649.

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Genakoplos, John, Olivia Mitchell, and Stephen Zeldes. Would a Privatized Social Security System Really Pay a Higher Rate of Return. Cambridge, MA: National Bureau of Economic Research, May 2000. http://dx.doi.org/10.3386/w6713.

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Karlsson, Hyunjoo Kim, and Yushu Li. Investigation of Swedish krona exchange rate volatilityby APARCH-Support Vector Regression. Department of Economics and Statistics, Linnaeus University, June 2024. http://dx.doi.org/10.15626/ns.wp.2024.10.

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This paper investigates daily exchange rate volatility behaviors with a focus on a small open economy’s currency, the Swedish krona (SEK), against four currencies: the U.S. dollar, Euro, the Pound Sterling (GBP), and the Norwegian krone (NOK) over the whole period from Jan. 2010 to March 2023, whereas the whole period is divided into different sub-sample periods based on the economic events. In the framework of APARCH models, we find that volatility behavior of the Swedish krona (SEK) exchange rates varies across different currency pairs (SEK being included in all cases) and sub-sample periods. Precisely, a negative asymmetric return-volatility relationship was found for the case of the SEK/EUR exchange rate, while an inverted asymmetric relationship was detected in the case of SEK/NOK exchange rate. Significant asymmetric effects of volatility in the SEK/USD and SEK/GBP exchange rates were not observed for either the whole period or the three sub-sample periods. As the return of exchange rate are all non-normally distributed, we then use a distribution-free support vector machine-based regression, called support vector regression (SVR), to estimate and forecast volatility in the framework of the chosen APARCH model for each krona exchange rate. The result shows that the SVR-APARCH based volatility forecasting performs better than the forecasting based on APARCH model estimated by maximum likelihood estimation (MLE).

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Rincón-Torres, Andrey Duván, Kimberly Rojas-Silva, and Juan Manuel Julio-Román. The Interdependence of FX and Treasury Bonds Markets: The Case of Colombia. Banco de la República, September 2021. http://dx.doi.org/10.32468/be.1171.

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We study the interdependence of FX and Treasury Bonds (TES) markets in Colombia. To do this, we estimate a heteroskedasticity identified VAR model on the returns of the COP/USD exchange rate (TRM) and bond prices, as well as event-analysis models for return volatilities, number of quotes, quote volume, and bid/ask spreads. The data under analysis consists of 5-minute intraday bid/ask US dollar prices and bond quotes, for an assortment of bond species. For these species we also have the number of bid/ask quotes as well as their volume. We found, also, that the exchange rate conveys information to the TES market, but the opposite does not completely hold: A one percent COP depreciation leads to a persistent reduction of TES prices between 0.05% and 0.22%. However, a 1% TES price increase has a very small effect and not entirely significant on the exchange rate, i.e. a COP appreciation between 0.001% and 0.009%. Furthermore, TRM return volatility increases do not affect bond return volatility but its liquidity, i.e. the bid/ask quote number and volume. These results are coherent with the fact that the FX market more efficiently reflects the effect of shocks than the TES market, which may be due to its low liquidity and concentration on a specific habitat. These results have implications for the design of financial stability policies as well as for private portfolio design, rebalancing and hedging.

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Heckman, James, Seong Hyeok Moon, Rodrigo Pinto, Peter Savelyev, and Adam Yavitz. A New Cost-Benefit and Rate of Return Analysis for the Perry Preschool Program: A Summary. Cambridge, MA: National Bureau of Economic Research, July 2010. http://dx.doi.org/10.3386/w16180.

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