IDEAS home Printed from https://ideas.repec.org/a/blg/reveco/v69y2017i3p19-28.html
   My bibliography  Save this article

Estimating The Return Of The Financial Titles Of The Companies From The Manufacturing Industry, Listed On The Bucharest Stock Exchange

Author

Listed:
  • BALTES Nicolae

    (Lucian Blaga University of Sibiu)

  • DRAGOE Alexandra-Gabriela-Maria

    (Lucian Blaga University of Sibiu)

Abstract

The paper presents a method of estimating the maximum expected loss of value that can be recorded by holding a portfolio of financial titles for a certain period of time, through the VaR model, using Monte Carlo simulation method. The research was based on the closing prices of 33 companies from the manufacturing industry in Romania, listed on the Bucharest Stock Exchange. The results of the paper showed that, for a portfolio composed of the financial titles of the 33 studied companies, in which it will be invested an amount of 1.000.000 lei, the maximum daily loss, estimated during the studied period of 01.01.2016-31.12.2016, was 2.513,47 lei.

Suggested Citation

  • BALTES Nicolae & DRAGOE Alexandra-Gabriela-Maria, 2017. "Estimating The Return Of The Financial Titles Of The Companies From The Manufacturing Industry, Listed On The Bucharest Stock Exchange," Revista Economica, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 69(3), pages 19-28, August.
    • Handle: RePEc:blg:reveco:v:69:y:2017:i:3:p:19-28
    as

    Download full text from publisher

    File URL: http://economice.ulbsibiu.ro/revista.economica/archive/69302baltes&dragoe.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2013. "Financial Risk Measurement for Financial Risk Management," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1127-1220, Elsevier.
    2. David E. Allen & Robert Powell, 2009. "Transitional credit modelling and its relationship to market value at risk: an Australian sectoral perspective," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 49(3), pages 425-444, September.
    3. Miguel A. Ferreira, 2005. "Evaluating Interest Rate Covariance Models Within a Value-at-Risk Framework," Journal of Financial Econometrics, Oxford University Press, vol. 3(1), pages 126-168.
    4. Engle, Robert F. & Manganelli, Simone, 2001. "Value at risk models in finance," Working Paper Series 75, European Central Bank.
    5. Francis X. Diebold (ed.), 2012. "Financial Risk Measurement and Management," Books, Edward Elgar Publishing, number 14102, December.
    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. Victor Olkhov, 2021. "To VaR, or Not to VaR, That is the Question," Papers 2101.08559, arXiv.org, revised Apr 2024.
    2. Kyle Jurado & Sydney C. Ludvigson & Serena Ng, 2015. "Measuring Uncertainty," American Economic Review, American Economic Association, vol. 105(3), pages 1177-1216, March.
    3. Serena Ng & Jonathan H. Wright, 2013. "Facts and Challenges from the Great Recession for Forecasting and Macroeconomic Modeling," Journal of Economic Literature, American Economic Association, vol. 51(4), pages 1120-1154, December.
    4. Massacci, Daniele, 2014. "A two-regime threshold model with conditional skewed Student t distributions for stock returns," Economic Modelling, Elsevier, vol. 43(C), pages 9-20.
    5. F. Lilla, 2017. "High Frequency vs. Daily Resolution: the Economic Value of Forecasting Volatility Models - 2nd ed," Working Papers wp1099, Dipartimento Scienze Economiche, Universita' di Bologna.
    6. F. Lilla, 2016. "High Frequency vs. Daily Resolution: the Economic Value of Forecasting Volatility Models," Working Papers wp1084, Dipartimento Scienze Economiche, Universita' di Bologna.
    7. Dias, Alexandra, 2013. "Market capitalization and Value-at-Risk," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 5248-5260.
    8. Takahashi, Makoto & Watanabe, Toshiaki & Omori, Yasuhiro, 2016. "Volatility and quantile forecasts by realized stochastic volatility models with generalized hyperbolic distribution," International Journal of Forecasting, Elsevier, vol. 32(2), pages 437-457.
    9. Hassan Belkacem Ghassan & Abdelkrim Ahmed Guendouz, 2019. "Panel modeling of z-score: evidence from Islamic and conventional Saudi banks," International Journal of Islamic and Middle Eastern Finance and Management, Emerald Group Publishing Limited, vol. 12(3), pages 448-468, July.
    10. Christophe Boucher & Benjamin Hamidi & Patrick Kouontchou & Bertrand Maillet, 2012. "Une évaluation économique du risque de modèle pour les investisseurs de long terme," Revue économique, Presses de Sciences-Po, vol. 63(3), pages 591-600.
    11. Szubzda Filip & Chlebus Marcin, 2019. "Comparison of Block Maxima and Peaks Over Threshold Value-at-Risk models for market risk in various economic conditions," Central European Economic Journal, Sciendo, vol. 6(53), pages 70-85, January.
    12. Chkili, Walid & Aloui, Chaker & Nguyen, Duc Khuong, 2012. "Asymmetric effects and long memory in dynamic volatility relationships between stock returns and exchange rates," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(4), pages 738-757.
    13. Fong Chan, Kam & Gray, Philip, 2006. "Using extreme value theory to measure value-at-risk for daily electricity spot prices," International Journal of Forecasting, Elsevier, vol. 22(2), pages 283-300.
    14. Lima, Luiz Renato & Néri, Breno Pinheiro, 2007. "Comparing Value-at-Risk Methodologies," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 27(1), May.
    15. Allen, David E. & Amram, Ron & McAleer, Michael, 2013. "Volatility spillovers from the Chinese stock market to economic neighbours," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 94(C), pages 238-257.
    16. Caporin, Massimiliano & McAleer, Michael, 2014. "Robust ranking of multivariate GARCH models by problem dimension," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 172-185.
    17. Enrico Zaninotto & Alessandro Rossi & Loris Gaio, 1999. "Stochastic learning in coordination games: a simulation approach," Quaderni DISA 015, Department of Computer and Management Sciences, University of Trento, Italy, revised 29 Jun 2003.
    18. Francis X. Diebold, 2020. ""Big Data" and its Origins," Papers 2008.05835, arXiv.org, revised Jan 2021.
    19. de Goeij, Peter & Marquering, Wessel, 2009. "Stock and bond market interactions with level and asymmetry dynamics: An out-of-sample application," Journal of Empirical Finance, Elsevier, vol. 16(2), pages 318-329, March.
    20. 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.

    More about this item

    Keywords

    financial titles; Value at Risk (VaR); Monte Carlo method; closing price; market risk;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

    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:blg:reveco:v:69:y:2017:i:3:p:19-28. 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: Eduard Alexandru Stoica (email available below). General contact details of provider: https://edirc.repec.org/data/feulbro.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.