ESTIMATE OF AN AVERAGE SITUATION OF REGIONS IN VALUE CHAINS

Evgenii LUKIN

Candidate of Sciences (Economic), Deputy Department Head, Vologda Research Center of the RAS, Russia

lukin_ev@list.ru

Abstract

The article considers an indicator that reflects an average position of industries and regions in value chains. It shows high differentiation of territorial distribution of its values in Russian economy. It determines a strong correlation between GRP per capita and an upstreamness index in the economy of Russian regions. The paper compares obtained results with the data on US economy.

Keywords: region, upstreamness, value chains, GRP

JEL classification: O18
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EVALUATING THE INVESTMENT ATTRACTIVENESS OF A REGION BASED ON THE BALANCED SCORECARD APPROACH

Vladimir MYAKSHIN

Associate professor, Nothern (Arctic) Federal University, Russia, Arkhangelsk, Naberezhnaya Severnoy Dviny 17

mcshin@yandex.ru

Vladimir PETROV

Professor, St. Petersburg State Forestry University, Russia, St. Petersburg,

Institutsky pereulok 5

wladimirpetrov@mail.ru

Abstract

This article discusses how the investment attractiveness of a region’s economic system (case study of Arkhangelsk Region) can be evaluated usingА the balanced scorecard developed and disclosed herein by the authors. It seeks to provide a rationale for the relevance and applicability of the balanced scorecard as a tool for identifying local investment-related challenges. The article further explains the importance of developing a sound mechanism for aligning the interests of the key stakeholders of investment process (private investors, local community, and public bodies). This mechanism should employ a balanced estimate of a region’s investment attractiveness which, in its turn, should rely on the target user groups’ informational needs. Having analyzed the basic methodologies being used by the investigators of the region’s investment attractiveness, we became convinced that the issue needs a more balanced representation and have therefore developed the balanced scorecard, accompanied by the user guide which is intended for the governmental authorities in charge of the measures to enhance the investment attractiveness locally. The analysis of the balanced scorecard has shown that it proves a useful tool for evaluating a region’s investment attractiveness and identifying its investment-related challenges and growth opportunities. In performing our study, we were governed by the current theories of institutional economics, region’s economy, and the theory of investment, the latter viewing the investment attractiveness through the prism of investment efforts. The results and conclusions of this study may serve as the basis for elaborating the region-level investment promotion strategies.

Keywords: investment potential, investment risks, investment climate, investment policy, investment attractiveness, investment efforts, core drivers, region’s economic system, balanced scorecard, balanced estimate

JEL classification: D92, L50, L52, L90
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OPTIMAL PORTFOLIO SELECTION WITH VALUE AT RISK CRITERION IN SELECTED TEHRAN STOCK EXCHANGE COMPANIES (PSO AND MPSO APPROACHES)

Hamidreza FAALJOU

Assistant Professor of Economics, Urmia University

h.faahjou@urmia.ac.ir

Kiumars SHAHBAZI

Associate Professor of Economics, Urmia University

K.shahbazi@urmia.ac.ir

Ebrahim NASIRIAN

Ph.D. of Economics, Urmia University, Corresponding Author

nasirian1353@gmail.com

Abstract

The optimal portfolio selection problem has always been the most important issue in the modern economy.  In this Study, It has been shown that how an investment with n risky share can achieve the certain profits with less risk that spread between stocks. Such a portfolio, it is called an efficient portfolio and it is necessary to find solving the optimization problem. Hence, the Improved Particle Swarm Optimization algorithm is used. The value of Portfolio and its risk are applied as the parameters in optimizing aim and criterion value exposed to contingent risk. Three intended applications have been indicated to the portfolio. In the next stage ,to evaluate and validate the method and to estimate the value of the portfolio in the next days and hold the series of the stock prices ,within a specified period, to predict the price and The Autoregressive method algorithms is used for modeling of the time-series. Practical result achieved for solving the portfolio optimization problem in Tehran Stock Exchange for the next day, by choosing the basket which includes 20 companies among the 30 most active industry indicates the performance and high capability of the algorithms and used in solving constrained optimization and appropriate weighted portfolios.

Keywords: Portfolio Selection, Conditional Value at Risk, Particle Swarm Optimization algorithm, Price and Return Forecasting

JEL classification: C22, G12, G24
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