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Theoretical aspects concerning the use of the statistical-econometric instruments the analysis of the financial assets

Author

Listed:
  • Constantin ANGHELACHE

    (Academia de Studii Economice, Bucuresti, Universitatea „Artifex” din Bucuresti)

  • Madalina Gabriela ANGHEL

    (Universitatea „Artifex” din Bucuresti)

Abstract

The econometric modelling of the financial variables aims to obtain models meant to forecast to the best their future values, taking into account the inertial character of the progress of the analysed processes as well as the relatively predictable character of their evolution in response to certain deviations from the observed past. The econometric regression models or those based on the use of the chronologic series allow us to do prognoses on the ground of the observations subject of the analysis. Although requiring a volume of work quit significant, the regression models allow the identification of certain functional dependences between the various components of the capital market which secures a real possibility to forecast the phenomena subject of the analysis over a time horizon well established.

Suggested Citation

  • Constantin ANGHELACHE & Madalina Gabriela ANGHEL, 2015. "Theoretical aspects concerning the use of the statistical-econometric instruments the analysis of the financial assets," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 63(9), pages 44-48, September.
    • Handle: RePEc:rsr:supplm:v:63:y:2015:i:9:p:44-48
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    References listed on IDEAS

    as
    1. Robert Engle, 2004. "Risk and Volatility: Econometric Models and Financial Practice," American Economic Review, American Economic Association, vol. 94(3), pages 405-420, June.
    2. Constantin ANGHELACHE & Mădălina Gabriela ANGHEL, 2014. "Using the regression model for the portfolios analysis and management," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 0(4(593)), pages 53-66, April.
    3. Tim Bollerslev, 2008. "Glossary to ARCH (GARCH)," CREATES Research Papers 2008-49, Department of Economics and Business Economics, Aarhus University.
    4. Giovanni Barone Adesi & Robert F. Engle & Loriano Mancini, 2014. "A GARCH Option Pricing Model with Filtered Historical Simulation," Palgrave Macmillan Books, in: Giovanni Barone Adesi (ed.), Simulating Security Returns: A Filtered Historical Simulation Approach, chapter 4, pages 66-108, Palgrave Macmillan.
    5. Mădălina Gabriela ANGHEL, 2014. "Econometric model used in the capital market analysis," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 0(10(599)), pages 59-70, October.
    6. repec:agr:journl:v:4(593):y:2014:i:4(593):p:53-66 is not listed on IDEAS
    7. Robert Engle, 2001. "GARCH 101: The Use of ARCH/GARCH Models in Applied Econometrics," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 157-168, Fall.
    8. repec:agr:journl:v:10(599):y:2014:i:10(599):p:59-70 is not listed on IDEAS
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Constantin ANGHELACHE & Janusz GRABARA & Alexandru MANOLE, 2016. "Using the Dynamic Model ARMA to Forecast the Macroeconomic Evolution," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 64(1), pages 3-13, January.
    2. Constantin ANGHELACHE & Alexandru MANOLE & Andreea MARINESCU, 2016. "Model of investment analysis in an uncertain environment," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 64(8), pages 77-84, August.
    3. Vergil VOINEAGU & Michal BALOG & Daniel DUMITRESCU & Diana SOARE (DUMITRESCU), 2016. "Managing Financial Instruments by Development Bank of Romania," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 64(1), pages 32-37, January.
    4. Gabriela Victoria ANGHELACHE & Madalina Gabriela ANGHEL & Marius POPOVICI, 2016. "Significant Aspects of Investment Dynamics," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 64(1), pages 64-69, January.

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