Задача о поиске равновесия при решении агентской проблемы с точки зрения риск-менеджмента Выпускная квалификационная работа аспиранта, обучающегося по основной образовательной программе аспирантуры «Экономика и управление народным хозяйством (логистика;
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Литература 1. Valackiene A. Theoretical Substation of the Model for Crisis Management in Organization // Eng. Econ. 2011. Vol. 22, № 1. 2. Brunnermeier M.K., Pedersen L.H. Predatory Trading // J. Finance. 2005. Vol. 60, № 4. P. 1825–1863. 3. Allen F., Gale D. Financial Contagion // J. Polit. Econ. 2000. Vol. 108, № 1. P. 1–33. 4. Kodres L.E., Pritsker M. A Rational Expectations Model of Financial Contagion // J. Finance. 2002. Vol. 57, № 2. P. 769–799. 5. Aragon G.O., Strahan P.E. Hedge funds as liquidity providers: evidence from the Lehman bankruptcy. 2011. 6. Clarida R., Gali J. Sources of Real Exchange Rate Fluctuations: How Important Are Nominal Shocks? 1993. 7. Longstaff F.A. The subprime credit crisis and contagion in financial markets // J. financ. econ. 2010. Vol. 97, № 3. P. 436–450. 8. Sims C.A. Macroeconomics and Reality // Econometrica. 1980. Vol. 48, № 1. P. 1–48. 9. Maekawa K., Tanaka K. The ET Interview: Professor Michio Hatanaka // Econom. Theory. 1990. № 6. P. 385–402. 10. Hatanaka M. On the Global Identification of the Dynamic Simultaneous Equations Model with Stationary Disturbances // Int. Econ. Rev. (Philadelphia). 1975. Vol. 16, № 3. P. 545. 11. Baum C.F. VAR, SVAR and VECM models [Electronic resource]. 2013. P. 1–61. URL: http://fmwww.bc.edu/EC-C/S2013/823/EC823.S2013.nn10.slides.pdf. 12. Weisstein E.W. Cholesky Decomposition [Electronic resource] // MathWorld--A Wolfram Web Resource. http://mathworld.wolfram.com/CholeskyDecomposition.html. URL: http://mathworld.wolfram.com/CholeskyDecomposition.html. 13. Fukushima Y. Macroeconomic Shock and Labour Market Programmes // Procedia Econ. Financ. 2012. Vol. 1. P. 138–147. 14. Самуэльсон П.Э., Нордхаус В.Д. Экономика. Москва: ООО “И.Д. Вильямс,” 2012. 1360 p. 15. Dąbrowski M.A., Wróblewska J. Financial shocks as a cause of real exchange rate fluctuations in Poland – evidence from the Bayesian structural VAR models. 16. Blanchard O.J., Quah D. The Dynamic Effects of Aggregate Demand and Supply Disturbances. 17. Binning A. Underidentified SVAR models: A framework for combining short and long-run restrictions with sign-restrictions. 2013. 18. Кондратьев Н.Д., Яковец Ю.В., Aбалкин Л.И. Большие циклы коньюнктуры и теория предвидения. Избранные труды. Москва: Экономика, 2002. 550 p. 19. Кравцов А.О. Управление изменениями как антикризисное управление. Санкт-Петербург, 2015. 43-47 p. 20. Олейник Д.В. Антикризисные стратегии и управление рисками в организациях. Санкт-Петербург, 2015. 165-167 p. 21. Ряховская А.Н., Кован С.Е. Трансформация антикризисного управления в современных экономических условиях // Эффективное антикризисное управление. 2013. Vol. 5, № 80. P. 62–73. 22. Author R., Sargan J.D. The Maximum Likelihood Estimation of Economic Relationships with Autoregressive // Source Econom. 1961. Vol. 29, № 3. P. 414–426. 23. Li Z., Wang H. Research on the Enterprise Crisis Management System Basic on Knowledge Demand. 24. Jianying Z. Crisis Management based on the Five Hypotheses proposed by Jack Welch // Proceedings of the 2012 International Conference on Public Management (ICPM-2012). Paris, France: Atlantis Press, 2012. 25. Tingting B., Zhanglu T. On the Crisis Management of the Modern Enterprise. 26. Wernerfelt B. A Resource-based View of the Firm // Strateg. .Management J. 1984. Vol. 5. P. 171–180. 27. Welch D., Welch S. Winning. New York: HarperCollins Publishers Inc., 2005. 385 p. 28. Федорова Е.А., Афанасьев Д.О. Комплексный кризисный индикатор для России // Журнал Новой экономической ассоциации. 2014. Vol. 23, № 2. P. 38–59. 29. Mountford A., Uhlig H. What are the Effects of Fiscal Policy Shocks ? References 1. Valackiene A. Theoretical Substation of the Model for Crisis Management in Organization // Eng. Econ. 2011. Vol. 22, № 1. 2. Brunnermeier M.K., Pedersen L.H. Predatory Trading // J. Finance. 2005. Vol. 60, № 4. P. 1825–1863. 3. Allen F., Gale D. Financial Contagion // J. Polit. Econ. 2000. Vol. 108, № 1. P. 1–33. 4. Kodres L.E., Pritsker M. A Rational Expectations Model of Financial Contagion // J. Finance. 2002. Vol. 57, № 2. P. 769–799. 5. Aragon G.O., Strahan P.E. Hedge funds as liquidity providers: evidence from the Lehman bankruptcy. 2011. 6. Clarida R., Gali J. Sources of Real Exchange Rate Fluctuations: How Important Are Nominal Shocks? 1993. 7. Longstaff F.A. The subprime credit crisis and contagion in financial markets // J. financ. econ. 2010. Vol. 97, № 3. P. 436–450. 8. Sims C.A. Macroeconomics and Reality // Econometrica. 1980. Vol. 48, № 1. P. 1–48. 9. Maekawa K., Tanaka K. The ET Interview: Professor Michio Hatanaka // Econom. Theory. 1990. № 6. P. 385–402. 10. Hatanaka M. On the Global Identification of the Dynamic Simultaneous Equations Model with Stationary Disturbances // Int. Econ. Rev. (Philadelphia). 1975. Vol. 16, № 3. P. 545. 11. Baum C.F. VAR, SVAR and VECM models [Electronic resource]. 2013. P. 1–61. URL: http://fmwww.bc.edu/EC-C/S2013/823/EC823.S2013.nn10.slides.pdf. 12. Weisstein E.W. Cholesky Decomposition [Electronic resource] // MathWorld—A Wolfram Web Resource.http://mathworld.wolfram.com/CholeskyDecomposition.html. URL: http://mathworld.wolfram.com/CholeskyDecomposition.html. 13. Fukushima Y. Macroeconomic Shock and Labour Market Programmes // Procedia Econ. Financ. 2012. Vol. 1. P. 138–147. 14. Samujel'son P.Je., Nordhaus V.D. Jekonomika. Moskva: OOO “I.D. Vil'jams,” 2012. 1360 p. 15. Dąbrowski M.A., Wróblewska J. Financial shocks as a cause of real exchange rate fluctuations in Poland – evidence from the Bayesian structural VAR models. 16. Blanchard O.J., Quah D. The Dynamic Effects of Aggregate Demand and Supply Disturbances. 17. Binning A. Underidentified SVAR models: A framework for combining short and long-run restrictions with sign-restrictions. 2013. 18. Kondrat'ev N.D., Jakovec Ju.V., Abalkin L.I. Bol'shie cikly kon'junktury i teorija predvidenija. Izbrannye trudy. Moskva: Jekonomika, 2002. 550 p. 19. Kravcov A.O. Upravlenie izmenenijami kak antikrizisnoe upravlenie. Sankt-Peterburg, 2015. 43-47 p. 20. Olejnik D.V. Antikrizisnye strategii i upravlenie riskami v organizacijah. Sankt-Peterburg, 2015. 165-167 p. 21. Rjahovskaja A.N., Kovan S.E. Transformacija antikrizisnogo upravlenija v sovremennyh jekonomicheskih uslovijah // Jeffektivnoe antikrizisnoe upravlenie. 2013. Vol. 5, № 80. P. 62–73. 22. Author R., Sargan J.D. The Maximum Likelihood Estimation of Economic Relationships with Autoregressive Residuals // Source Econom. 1961. Vol. 29, № 3. P. 414–426. 23. Li Z., Wang H. Research on the Enterprise Crisis Management System Basic on Knowledge Demand. 24. Jianying Z. Crisis Management based on the Five Hypotheses proposed by Jack Welch // Proceedings of the 2012 International Conference on Public Management (ICPM-2012). Paris, France: Atlantis Press, 2012. 25. Tingting B., Zhanglu T. On the Crisis Management of the Modern Enterprise. 26. Wernerfelt B. A Resource-based View of the Firm // Strateg. .Management J. 1984. Vol. 5. P. 171–180. 27. Welch D., Welch S. Winning. New York: HarperCollins Publishers Inc., 2005. 385 p. 28. Fedorova E.A., Afanas'ev D.O. Kompleksnyj krizisnyj indikator dlja Rossii // Zhurnal Novoj jekonomicheskoj associacii. 2014. Vol. 23, № 2. P. 38–59. 29. Mountford A., Uhlig H. What are the Effects of Fiscal Policy Shocks ? [1] Под монетарными шоками R. Clarida и J. Gali понимают шоки (неожиданные и значительные изменения) денежного предложения, как и спроса на деньги [6]. Нужно также отметить, что перечисленные шоки далеко не исчерпывают весь перечень макроэкономических шоков, влияние которых на ситуацию в экономике анализируется. Так, например, A. Mountford и H. Uhlig рассматривают влияние фискальных шоков, возникающих как результат фискальной политики [29]. [2] В статье Е.А. Фёдоровой и Д.О. Афанасьева выделяются каналы на основе следующих показателей: торговый канал в виде роста импорта, финансовый канал через финансовую интеграцию фондовых рынков и банковский канал через реальные процентные ставки по депозитам [28]. St. Petersburg State University Graduate School of Management WORKING PAPER A.E. Loukianova, E.A. Smirnova straregic risk-management with the use of the market risk indicator: a comparative longitudinal study in the developed and emerging markets Saint Petersburg 2016 A.E. Loukianova, E.A. Smirnova. Strategic risk-management with the use of the market risk indicator: a comparative longitudinal study in the developed and emerging markets. Working paper. Graduate School of Management, St. Petersburg State University: SPb, 2016. Keywords and phrases: financial contagion, Brazil, Finland, Canada, risk-management Abstract: the history of financial crises is considered and the attempt is made to analyse the parallels in Finnish, Canadian and Brazilian markets crises in the working paper. The historical conditions of crises on the markets is analysed on the base of the literature review and the examples from three analysed markets are presented with the use of the network analysis. The conclusion made is that the financial contagion indicator can be used for the market risk assessment for practical and theoretical purposes. Anna E. Loukianova, PhD in mathematics and physics, Associate Professor, Finance and Accounting Department, Saint-Petersburg State University e-mail: Anna.Loukianova@gsom.pu.ru Ekaterina A. Smirnova, Doctoral Student, Graduate School of Management Saint-Petersburg State University. e-mail: ekaterina_a.smirnova@yahoo.com Contents Introduction In the contemporary circumstances the company needs the system of indicators that will help to understand and to predict the process of the risks development: how the risks emerge, how the threats for the company arise, how much the risks menace the company. The crisis period data considered reports the special value for the risks analysis. In this research developed and emerging markets are considered in order to find the financial contagion indicators2. For the sake of early probable crisis identification the special indicator is needed, that would be able to assess the degree of the threat. Such indicators had been proposed and tested many times (Allen & Gale, 2000; Aragon & Strahan, 2011; M. K. Brunnermeier & Pedersen, 2005; Kodres & Pritsker, 2002). In this work some financial contagion indicators are considered, which are the significant interconnections between the corporate and government securities indexes return and the main financial indicators return. For the individual investor decision making purposes market risk assessment has even more critical role, as the investor needs to decide if he agree to bear such risk. Financial contagion in the situation on the financial market during which the financial market different indicators interconnections became stronger after the shock that had took place in one financial indicator dynamic (Longstaff, 2010). The research is conducted with the use of data from Brazilian, Canadian and Finnish markets during the period of 1990-2015. The market risk indicator is compared with the information came from rating agencies, macroeconomic analyses, expert views and mass media reports. The results allow making conclusions concerning the crisis indicators on the base of the interconnections between the companies chares indexes returns and the macroeconomic indicators returns. The results obtained can provide the ground for the possible conclusions, that can be used in the purposes of the company’s risk-management strategy building process. Theory and Hypothesis The history of emerging markets is full of crises. In (Kaminsky, Reinhart, & Vegh, 2003) the interesting examples are considered. The contagion itself is defined as “an episode in which there are significant immediate effects in a number of countries following an event” (Kaminsky et al., 2003). The financial contagion can be defined as “an episode in which there is a significant increase in cross-market linkages after a shock occurs in one market” (Longstaff, 2010). In the developing the financial contagion theory the significant part brought the works of K. Liberadzki, M. Mink, J. de Haan, N. Yunus, F. Allen, D. Gale, M. Brunnermeier, D. Pedersen and others (Allen & Gale, 2000; M. K. Brunnermeier & Pedersen, 2005; Jaworski, 2016; Mink & De Haan, 2012; Yunus, 2013). F.A. Longstaff defines financial contagion as an episode in which there is a significant increase in cross-market linkages after a shock occurs in one market. The standard definition in the literature of contagion is “a change in the linkages between markets following a distressed event” (Longstaff, 2010). The contagion in the related literature is generally characterizes by several approaches. For example, in the behavioral approaches the attempt to describe mass behavior as a reaction of a large groups of people to the information flow from one individual to another (the special term is “informational cascades” (Bikhchandani, Hirshleifer, & Welch, 1992). Another way of the behavioral theory intersection with the contagion theory is the so-called “follow-the-leader” strategy which claims that the signals that the first few decision-makers accept, are possible to change market situation dramatically (the “excess volatility” term is usually used when describing that phenomenа (Chari et al., 1999). The sense of such approach to the contagion helps to understand the information-correlated channel of the financial contagion distribution. The approach of the other group of authors is based on the macroeconomic regularities in the case of prices devaluation (this is also called “voluntary contagion”, because the devaluation is the government voluntary measure (Gerlach & Smets, 1995; Kaminsky et al., 2003; Lahiri & Vegh, 2000; Nurkse, 1944). Last, but not least, the financial approach consists of the arbitrage theory and the liquidity effect studying, that was presented in (Chari et al., 1999; Shleifer & Vishny, 1997). And the financial contagion is a profound perspective to assess and analyze market risk, that is considered in this paper. The literature review also indicated that in the countries considered in the research the following economic crises took place. 1992 Exchange Rate Mechanism Crisis in Finland occurs when on September, 8 the Finnish markka was floated (Kaminsky et al., 2003). The situation was worse due to the Soviet Union trade links losses in 1991, which were significant part for the international trade balance of Finland. The real devaluation in 1993 and its depreciation during 2 month by 70%. Russian debt crisis in 1998 affected Brazilian economy seriously. As for Canada, as the developed market, it is supposed to have less effects from crises compared to the emerging markets. But, crisis 2007-2008 in US affected Canada as many other developed and emerging markets. So, it may be interesting to examine whether the crises in developed markets are less extensive than in emerging markets and whether developed markets become affected by crises as often, as developed. The hypotheses tested in this research are: H1: the financial contagion indicator can help to identify possible factors of financial contagion. H2: the financial contagion identified in the research and the crises are correlated positively. The idea lies behind this hypothesis is that the financial contagion factors can help also to detect the probable crisis forthcoming. The fact of the financial contagion presence on the market doesn’t mean the crisis existence on that market, but it is the aim of this study to answer the question if the interconnection between them can be identified. Data In the study an attempt to look at the following markets of the world were considered: Brazil, Finland and Canada. The main idea of the study is to examine the trends in the stock markets. The period of time was by default set as 1990-2015, but data for some was not available. The asset returns were used as independent variables. The companies, those shares were considered in the research are from main stock market indexes (Appendix 1). The dependent variables were divided into three groups according to the three financial contagion distribution channels:
The general list of the dependent variables for these three channels tests is presented in Table 1. It is necessary to add that for each markets these dependent variables were selected on the base of it specific features (main industries, historical economic background, the place in the international specialization of the country). |
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