IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/55430.html
   My bibliography  Save this paper

Editorial for the Special Issue on 'Computational Methods for Russian Economic and Financial Modelling'

Author

Listed:
  • Fantazzini, Dean

Abstract

This double-issue contains 11 papers invited for the first special issue on “Computational methods for Russian economic and financial modelling”. It was an attempt to explore and bring together practical, state-of-the-art applications of computational techniques with a particular focus on Russia and the Commonwealth of Independent States. The response was beyond expectations and managed to cover a wide range of issues, so that a double-issue was considered: the first dealing with Finance and the second with Economics.

Suggested Citation

  • Fantazzini, Dean, 2014. "Editorial for the Special Issue on 'Computational Methods for Russian Economic and Financial Modelling'," MPRA Paper 55430, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:55430
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/55430/1/MPRA_paper_55430.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dean Fantazzini & Nikita Fomichev, 2014. "Forecasting the real price of oil using online search data," International Journal of Computational Economics and Econometrics, Inderscience Enterprises Ltd, vol. 4(1/2), pages 4-31.
    2. Anna Sokolova, 2014. "Are inflation expectations in Russia forward-looking?," International Journal of Computational Economics and Econometrics, Inderscience Enterprises Ltd, vol. 4(1/2), pages 254-268.
    3. Oxana Malakhovskaya & Alexey Minabutdinov, 2014. "Are commodity price shocks important? A Bayesian estimation of a DSGE model for Russia," International Journal of Computational Economics and Econometrics, Inderscience Enterprises Ltd, vol. 4(1/2), pages 148-180.
    4. Vladimir I. Malugin & Natalia V. Hryn & Aleksandr Y. Novopoltsev, 2014. "Statistical analysis and econometric modelling of the creditworthiness of non-financial companies," International Journal of Computational Economics and Econometrics, Inderscience Enterprises Ltd, vol. 4(1/2), pages 130-147.
    5. Alexey I. Balaev, 2014. "Modelling financial returns and portfolio construction for the Russian stock market," International Journal of Computational Economics and Econometrics, Inderscience Enterprises Ltd, vol. 4(1/2), pages 32-81.
    6. N.P. Pilnik & I.G. Pospelov & S.A. Radionov & A.A. Zhukova, 2014. "The intertemporal general equilibrium model of the economy with the product, money and stock markets," International Journal of Computational Economics and Econometrics, Inderscience Enterprises Ltd, vol. 4(1/2), pages 207-233.
    7. Anatoly Peresetsky, 2014. "What drives the Russian stock market: world market and political shocks," International Journal of Computational Economics and Econometrics, Inderscience Enterprises Ltd, vol. 4(1/2), pages 82-95.
    8. Olga Demidova, 2014. "How Russian and Ukrainian citizens perceive the role of immigrants in their country: a comparison with European residents," International Journal of Computational Economics and Econometrics, Inderscience Enterprises Ltd, vol. 4(1/2), pages 181-206.
    9. M.A. Khokhlov & I.G. Pospelov & L.Ya. Pospelova, 2014. "Technology of development and implementation of realistic (country-specific) models of intertemporal equilibrium," International Journal of Computational Economics and Econometrics, Inderscience Enterprises Ltd, vol. 4(1/2), pages 234-253.
    10. Henry Penikas & Anastasia Petrova, 2014. "An empirical analysis of growth and consolidation in banking: a Markovian approach for the case of Russia," International Journal of Computational Economics and Econometrics, Inderscience Enterprises Ltd, vol. 4(1/2), pages 112-129.
    11. Evgeny A. Ivin & Alexey N. Kurbatskiy & Alexandr V. Slovesnov, 2014. "Time aspects of a fund manager appraisal," International Journal of Computational Economics and Econometrics, Inderscience Enterprises Ltd, vol. 4(1/2), pages 96-111.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. J. Pinkovetskaya & ЮЛИЯ Пиньковецкая СЕМЕНОВНА, 2016. "Анализ Отраслевой Локализации Малого И Среднего Предпринимательства В Регионах // Industrial Localization Analysis Of Small And Medium Entrepreneurship In The Regions," Управленческие науки // Management Science, ФГОБУВО Финансовый университет при Правительстве Российской Федерации // Financial University under The Government of Russian Federation, vol. 6(2), pages 70-82.
    2. Jorge Fornero & Markus Kirchner & Andrés Yany, 2015. "Terms of Trade Shocks and Investment in Commodity-Exporting Economies," Central Banking, Analysis, and Economic Policies Book Series, in: Rodrigo Caputo & Roberto Chang (ed.),Commodity Prices and Macroeconomic Policy, edition 1, volume 22, chapter 5, pages 135-193, Central Bank of Chile.
    3. Markus Kirchner & Malte Rieth, 2021. "Sovereign Default Risk, Macroeconomic Fluctuations and Monetary–Fiscal Stabilization," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 69(2), pages 391-426, June.
    4. Lukas Vogel & Stefan Hohberger & Bernhard Herz, 2015. "Should Commodity Exporters Peg to the Export Price?," Review of Development Economics, Wiley Blackwell, vol. 19(3), pages 486-501, August.
    5. Zeynalov, Ayaz, 2014. "Nowcasting Tourist Arrivals to Prague: Google Econometrics," MPRA Paper 60945, University Library of Munich, Germany.
    6. Huntington, Hillard G. & Barrios, James J. & Arora, Vipin, 2019. "Review of key international demand elasticities for major industrializing economies," Energy Policy, Elsevier, vol. 133(C).
    7. Zubarev, Andrey (Зубарев, Андрей) & Polbin, Andrey (Полбин, Андрей), 2017. "Scenario Analysis of the Impact of Reducing the Export Duty on Oil on the Russian Economy within the Framework of the General Equilibrium Model [Сценарный Анализ Влияния На Российскую Экономику Сни," Working Papers 051734, Russian Presidential Academy of National Economy and Public Administration.
    8. Artamonov, Nikita & Voronina, Anna & Emelyanov, Nikita & Kurbatskii, Aleksei, 2020. "Estimation of interest rates’ impact on mutual funds’ performance in the USA," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 58, pages 55-75.
    9. Dean Fantazzini & Julia Pushchelenko & Alexey Mironenkov & Alexey Kurbatskii, 2021. "Forecasting Internal Migration in Russia Using Google Trends: Evidence from Moscow and Saint Petersburg," Forecasting, MDPI, vol. 3(4), pages 1-30, October.
    10. Diagne, Youssoupha Sakrya & Thiam, Dame, 2020. "La résilience de l'économie sénégalaise : Quelles politiques publiques en réponses aux chocs exogènes? [Resillience of the senegalese economy; What policy responses to exogenous shocks?]," MPRA Paper 114018, University Library of Munich, Germany.
    11. Fantazzini, Dean & Toktamysova, Zhamal, 2015. "Forecasting German car sales using Google data and multivariate models," International Journal of Production Economics, Elsevier, vol. 170(PA), pages 97-135.
    12. Andrej Drygalla, 2023. "Monetary policy in an oil-dependent economy in the presence of multiple shocks," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 159(1), pages 185-214, February.
    13. S. Ozornov, 2015. "Validity Of Fama And French Model On Rts Index," Review of Business and Economics Studies // Review of Business and Economics Studies, Финансовый Университет // Financial University, vol. 3(4), pages 22-43.
    14. Vernikov, Andrei, 2017. "Структурные Или Институциональные Сдвиги? Попытка Измерения На Примере Банковского Сектора [Structural change, institutional change and their measurement: The case of banking]," MPRA Paper 79978, University Library of Munich, Germany.
    15. O. Malakhovskaya., 2016. "DSGE-based forecasting: What should our perspective be?," VOPROSY ECONOMIKI, N.P. Redaktsiya zhurnala "Voprosy Economiki", vol. 12.
    16. Daniil Lomonosov, 2023. "Shocks of Business Activity and Specific Shocks to Oil Market in DSGE Model of Russian Economy and Their Influence Under Different Monetary Policy Regimes," Russian Journal of Money and Finance, Bank of Russia, vol. 82(4), pages 44-79, December.
    17. Fantazzini, Dean & Shangina, Tamara, 2019. "The importance of being informed: forecasting market risk measures for the Russian RTS index future using online data and implied volatility over two decades," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 55, pages 5-31.
    18. Lycheva, Maria & Mironenkov, Alexey & Kurbatskii, Alexey & Fantazzini, Dean, 2022. "Forecasting oil prices with penalized regressions, variance risk premia and Google data," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 68, pages 28-49.
    19. Zeynalov, Ayaz, 2017. "Forecasting Tourist Arrivals in Prague: Google Econometrics," MPRA Paper 83268, University Library of Munich, Germany.
    20. Рубинштейн Александр Яковлевич, "undated". "Рациональность & Иррациональность: Эволюция Смыслов [Rationality & Irrationality: Evolution of the Senses]," Working papers a:pru175:ye:2017:1, Institute of Economics.

    More about this item

    Keywords

    Forecasting; oil price; Google; Russian stock market; T-distribution with vector degrees of freedom; portfolio management; Fund manager; Russian banking sector; Credit Risk; DSGE; Russia; Immigrants; Intertemporal general equilibrium model; Intertemporal equilibrium; Inflation; Inflation expectations;
    All these keywords.

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C68 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computable General Equilibrium Models
    • E5 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit
    • G1 - Financial Economics - - General Financial Markets
    • G2 - Financial Economics - - Financial Institutions and Services
    • J0 - Labor and Demographic Economics - - General
    • J1 - Labor and Demographic Economics - - Demographic Economics

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:55430. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.