IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/47708.html
   My bibliography  Save this paper

To the problem of evaluation of market risk of global equity index portfolio in global capital markets

Author

Listed:
  • Ledenyov, Dimitri O.
  • Ledenyov, Viktor O.

Abstract

Thinking about the development of the unifying mathematical approach to solve the problem on the evaluation of market risk of the global equity index portfolio in the highly volatile global capital markets, the authors focus their attention to an increasing necessity of application of the dynamic assessment of the financial systems with the use of the continuous system representation models, which allows to make the accurate characterization of the Returns on Investments (ROI) of the diversified global equity index portfolio. In our view, the creation of the complex computer models to accurately characterize the financial system’s operating modes results in ability by the investors to find the categorical behaviour properties of the financial system and to predict its dynamic properties precisely. In our opinion, in the periods of the challenging turbulent economic conditions in Bernanke (1995), the process of extraction of useful knowledge from the big streams of financial data from the various capital markets with the aim to make the virtuous investment decisions requires a deep understanding of the cognitive modeling techniques in application to the investment decision making as far as the global equity index portfolio is concerned. We analyzed the nature of the current financial and economic crises in the USA, presenting the views by the American business leaders, academicians and politicians, which were publicly expressed at The Economic Club of Washington in Washington, District Columbia in the USA. We highlighted the fact that it is important for the institutional and private investors to diversify their investments, and create the global equity index portfolio, aiming to increase the Return on Investment (ROI) and to accumulate the wealth in the course of the wealth management process at a global scale. Also, we considered the standard approach, which can be used to evaluate the market risk of a hypothetical global equity index portfolio with the Monte Carlo simulation technique, using the Student's t copula and the Extreme Value Theory (EVT) in Matlab (R2012). We proposed a conceptual framework, based on the suggestion that the application of the dynamic analysis of the nonlinear interactions between of the global capital flows can significantly leverage the effective investment control strategies in the researched case of the global equity index portfolio.

Suggested Citation

  • Ledenyov, Dimitri O. & Ledenyov, Viktor O., 2013. "To the problem of evaluation of market risk of global equity index portfolio in global capital markets," MPRA Paper 47708, University Library of Munich, Germany, revised 20 Jun 2013.
    • Handle: RePEc:pra:mprapa:47708
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/47708/1/MPRA_paper_47708.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dimitri O. Ledenyov & Viktor O. Ledenyov, 2012. "On the Risk Management with Application of Econophysics Analysis in Central Banks and Financial Institutions," Papers 1211.4108, arXiv.org.
    2. Viktor O. Ledenyov & Dimitri O. Ledenyov, 2012. "Shaping the international financial system in century of globalization," Papers 1206.2022, arXiv.org.
    3. Bernanke, Ben & Parkinson, Martin, 1989. "Unemployment, Inflation, and Wages in the American Depression: Are There Lessons for Europe?," American Economic Review, American Economic Association, vol. 79(2), pages 210-214, May.
    4. Dimitri O. Ledenyov & Viktor O. Ledenyov, 2013. "To the problem of turbulence in quantitative easing transmission channels and transactions network channels at quantitative easing policy implementation by central banks," Papers 1305.5656, arXiv.org, revised May 2013.
    5. Dimitri O. Ledenyov & Viktor O. Ledenyov, 2013. "On the accurate characterization of business cycles in nonlinear dynamic financial and economic systems," Papers 1304.4807, arXiv.org.
    6. McNeil, Alexander J. & Frey, Rudiger, 2000. "Estimation of tail-related risk measures for heteroscedastic financial time series: an extreme value approach," Journal of Empirical Finance, Elsevier, vol. 7(3-4), pages 271-300, November.
    7. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    8. Dimitri O. Ledenyov & Viktor O. Ledenyov, 2013. "On the optimal allocation of assets in investment portfolio with application of modern portfolio and nonlinear dynamic chaos theories in investment, commercial and central banks," Papers 1301.4881, arXiv.org, revised Feb 2013.
    9. Dimitri O. Ledenyov & Viktor O. Ledenyov, 2012. "On the new central bank strategy toward monetary and financial instabilities management in finances: Econophysical analysis of nonlinear dynamical financial systems," Papers 1211.1897, arXiv.org.
    10. Bernanke, Ben S, 1995. "The Macroeconomics of the Great Depression: A Comparative Approach," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 27(1), pages 1-28, February.
    11. Viktor O. Ledenyov & Dimitri O. Ledenyov, 2012. "Designing the new architecture of international financial system in era of great changes by globalization," Papers 1206.2778, arXiv.org.
    12. Bouye, Eric & Durlleman, Valdo & Nikeghbali, Ashkan & Riboulet, Gaël & Roncalli, Thierry, 2000. "Copulas for finance," MPRA Paper 37359, University Library of Munich, Germany.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ledenyov, Dimitri O. & Ledenyov, Viktor O., 2013. "On the Stratonovich – Kalman - Bucy filtering algorithm application for accurate characterization of financial time series with use of state-space model by central banks," MPRA Paper 50235, University Library of Munich, Germany.
    2. Ledenyov, Dimitri O. & Ledenyov, Viktor O., 2015. "Wave function method to forecast foreign currencies exchange rates at ultra high frequency electronic trading in foreign currencies exchange markets," MPRA Paper 67470, University Library of Munich, Germany.
    3. Ledenyov, Dimitri O. & Ledenyov, Viktor O., 2013. "Some thoughts on accurate characterization of stock market indexes trends in conditions of nonlinear capital flows during electronic trading at stock exchanges in global capital markets," MPRA Paper 49921, University Library of Munich, Germany.

    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. Ledenyov, Dimitri O. & Ledenyov, Viktor O., 2013. "On the Stratonovich – Kalman - Bucy filtering algorithm application for accurate characterization of financial time series with use of state-space model by central banks," MPRA Paper 50235, University Library of Munich, Germany.
    2. Ledenyov, Dimitri O. & Ledenyov, Viktor O., 2015. "Wave function method to forecast foreign currencies exchange rates at ultra high frequency electronic trading in foreign currencies exchange markets," MPRA Paper 67470, University Library of Munich, Germany.
    3. Ledenyov, Dimitri O. & Ledenyov, Viktor O., 2013. "Some thoughts on accurate characterization of stock market indexes trends in conditions of nonlinear capital flows during electronic trading at stock exchanges in global capital markets," MPRA Paper 49921, University Library of Munich, Germany.
    4. Dimitri O. Ledenyov & Viktor O. Ledenyov, 2013. "On the theory of firm in nonlinear dynamic financial and economic systems," Papers 1302.6721, arXiv.org, revised Mar 2013.
    5. Dimitri O. Ledenyov & Viktor O. Ledenyov, 2013. "To the problem of turbulence in quantitative easing transmission channels and transactions network channels at quantitative easing policy implementation by central banks," Papers 1305.5656, arXiv.org, revised May 2013.
    6. Dimitri O. Ledenyov & Viktor O. Ledenyov, 2013. "On the accurate characterization of business cycles in nonlinear dynamic financial and economic systems," Papers 1304.4807, arXiv.org.
    7. Dimitri O. Ledenyov & Viktor O. Ledenyov, 2012. "On the Risk Management with Application of Econophysics Analysis in Central Banks and Financial Institutions," Papers 1211.4108, arXiv.org.
    8. Dimitri O. Ledenyov & Viktor O. Ledenyov, 2013. "On the optimal allocation of assets in investment portfolio with application of modern portfolio and nonlinear dynamic chaos theories in investment, commercial and central banks," Papers 1301.4881, arXiv.org, revised Feb 2013.
    9. Lan-Ya Ma & Zi-Yu Li, 2017. "Research on the Effect of Chinese Margin Trading on Market Risk: Based on GJR Model and Filtered Historical Simulation," Applied Economics and Finance, Redfame publishing, vol. 4(4), pages 84-93, July.
    10. Bernard, Carole & Czado, Claudia, 2015. "Conditional quantiles and tail dependence," Journal of Multivariate Analysis, Elsevier, vol. 138(C), pages 104-126.
    11. Torben G. Andersen & Tim Bollerslev & Peter Christoffersen & Francis X. Diebold, 2007. "Practical Volatility and Correlation Modeling for Financial Market Risk Management," NBER Chapters, in: The Risks of Financial Institutions, pages 513-544, National Bureau of Economic Research, Inc.
    12. Gonzalo Cortazar & Alejandro Bernales & Diether Beuermann, 2005. "Methodology and Implementation of Value-at-Risk Measures in Emerging Fixed-Income Markets with Infrequent Trading," Finance 0512030, University Library of Munich, Germany.
    13. Nikolaos Antonakakis & Ioannis Chatziantoniou & David Gabauer, 2021. "The impact of Euro through time: Exchange rate dynamics under different regimes," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 1375-1408, January.
    14. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2006. "Vector Multiplicative Error Models: Representation and Inference," NBER Technical Working Papers 0331, National Bureau of Economic Research, Inc.
    15. Turan Bali & Panayiotis Theodossiou, 2007. "A conditional-SGT-VaR approach with alternative GARCH models," Annals of Operations Research, Springer, vol. 151(1), pages 241-267, April.
    16. Buhlmann, Peter & McNeil, Alexander J., 2002. "An algorithm for nonparametric GARCH modelling," Computational Statistics & Data Analysis, Elsevier, vol. 40(4), pages 665-683, October.
    17. Wu, Qi & Yan, Xing, 2019. "Capturing deep tail risk via sequential learning of quantile dynamics," Journal of Economic Dynamics and Control, Elsevier, vol. 109(C).
    18. Xin Chen & Zhangming Shan & Decai Tang & Biao Zhou & Valentina Boamah, 2023. "Interest rate risk of Chinese commercial banks based on the GARCH-EVT model," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-11, December.
    19. Tim Bollerslev, 2008. "Glossary to ARCH (GARCH)," CREATES Research Papers 2008-49, Department of Economics and Business Economics, Aarhus University.
    20. Alfonso ARPAIA & Nicola CURCI, "undated". "EU labour market behaviour during the Great Recession," Working Papers wp2010-6, Department of the Treasury, Ministry of the Economy and of Finance.

    More about this item

    Keywords

    investment portfolio; risk evaluation; econophysics; econometrics; nonlinearities; nonlinear dynamic chaos theory; nonlinear dynamic financial and economic systems.;
    All these keywords.

    JEL classification:

    • A10 - General Economics and Teaching - - General Economics - - - General
    • C0 - Mathematical and Quantitative Methods - - General
    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Econometric and Statistical Methods; Specific Distributions
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

    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:47708. 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.