IDEAS home Printed from https://ideas.repec.org/a/agr/journl/vxxiiiy2016i4(609)p19-42.html
   My bibliography  Save this article

Limitation of ARIMA models in financial and monetary economics

Author

Listed:
  • Andreea-Cristina PETRICĂ

    (Bucharest University of Economic Studies, Romania)

  • Stelian STANCU

    (Bucharest University of Economic Studies, Romania)

  • Alexandru TINDECHE

    (Bucharest University of Economic Studies, Romania)

Abstract

Abandoning the classical econometric modeling approach which consists in using explanatory variables (suggested by economic theory for prediction), we choose instead to use a sophisticated method developed by Box and Jenkins (1970) based solely on the past behavior of the variable being modeled/forecast. As we are in a data-rich environment and the economies and financial markets are more integrated than ever before, the quantitative methods in business and finance has increased substantially in recent years. This paper investigates the limitation of autoregressive integrated moving average (ARIMA) models in financial and monetary economics using the behavior of BET Index and EUR/RON exchange rates, respectively. Two important features discovered in the analysis of financial time series in this paper are fat-tails (large losses or gains are coming at a higher probability than the normal distribution would suggest) and volatility clustering, these empirical properties can’t be captured by integrated ARMA models, hence the limitation of these models.

Suggested Citation

  • Andreea-Cristina PETRICĂ & Stelian STANCU & Alexandru TINDECHE, 2016. "Limitation of ARIMA models in financial and monetary economics," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(4(609), W), pages 19-42, Winter.
  • Handle: RePEc:agr:journl:v:xxiii:y:2016:i:4(609):p:19-42
    as

    Download full text from publisher

    File URL: http://store.ectap.ro/articole/1222.pdf
    Download Restriction: no

    File URL: http://www.ectap.ro/articol.php?id=1222&rid=125
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dat Bue Lock, 2007. "The Taiwan stock market does follow a random walk," Economics Bulletin, AccessEcon, vol. 7(3), pages 1-8.
    2. Kon, Stanley J, 1984. "Models of Stock Returns-A Comparison," Journal of Finance, American Finance Association, vol. 39(1), pages 147-165, March.
    3. Liviu-Stelian BEGU & Silvia Spataru & Erika Marin, 2012. "Investigating The Evolution Of Ron/Eur Exchange Rate: The Choice Of Appropriate Model," Journal of Social and Economic Statistics, Bucharest University of Economic Studies, vol. 1(2), pages 23-39, DECEMBER.
    4. Christoffersen, Peter, 2011. "Elements of Financial Risk Management," Elsevier Monographs, Elsevier, edition 2, number 9780123744487.
    5. Andrew W. Lo, A. Craig MacKinlay, 1988. "Stock Market Prices do not Follow Random Walks: Evidence from a Simple Specification Test," The Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 41-66.
    6. Richard Meese & Kenneth Rogoff, 1983. "The Out-of-Sample Failure of Empirical Exchange Rate Models: Sampling Error or Misspecification?," NBER Chapters, in: Exchange Rates and International Macroeconomics, pages 67-112, National Bureau of Economic Research, Inc.
    7. R. Cont, 2001. "Empirical properties of asset returns: stylized facts and statistical issues," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 223-236.
    8. Kuo-Ping Chang & Kuo-Shiuan Ting, 2000. "A variance ratio test of the random walk hypothesis for Taiwan's stock market," Applied Financial Economics, Taylor & Francis Journals, vol. 10(5), pages 525-532.
    9. Mark, Nelson C, 1995. "Exchange Rates and Fundamentals: Evidence on Long-Horizon Predictability," American Economic Review, American Economic Association, vol. 85(1), pages 201-218, March.
    10. repec:ebl:ecbull:v:7:y:2007:i:3:p:1-8 is not listed on IDEAS
    11. Cristiana Tudor, 2008. "Modelarea volatilitatii seriilor de timp prin modele GARCH simetrice," Romanian Economic Journal, Department of International Business and Economics from the Academy of Economic Studies Bucharest, vol. 11(30), pages 183-208, (4).
    12. Muhammad Mansoor Baig & Waheed Aslam & Qaiser Malik & Muhammad Bilal, 2015. "Volatility of Stock Markets (an Analysis of South Asian and G8 Countries)," Acta Universitatis Danubius. OEconomica, Danubius University of Galati, issue 11(6), pages 58-70, December.
    13. Conrad, Jennifer & Kaul, Gautam & Nimalendran, M., 1991. "Components of short-horizon individual security returns," Journal of Financial Economics, Elsevier, vol. 29(2), pages 365-384, October.
    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. Addie, Ron & Taranto, Aldo, 2024. "Economic Similarities and their Application to Inflation," EconStor Preprints 283286, ZBW - Leibniz Information Centre for Economics.
    2. M. Godsoe & M. Ladd & R. Cox, 2019. "Assessing Canada’s disaster baselines and projections under the Sendai Framework for Disaster Risk Reduction: a modeling tool to track progress," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 98(1), pages 293-317, August.
    3. Saeed, Naima & Nguyen, Su & Cullinane, Kevin & Gekara, Victor & Chhetri, Prem, 2023. "Forecasting container freight rates using the Prophet forecasting method," Transport Policy, Elsevier, vol. 133(C), pages 86-107.
    4. Shalini Sharma & Víctor Elvira & Emilie Chouzenoux & Angshul Majumdar, 2021. "Recurrent Dictionary Learning for State-Space Models with an Application in Stock Forecasting," Post-Print hal-03184841, HAL.

    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. Andreea-Cristina PETRICĂ & Stelian STANCU & Alexandru TINDECHE, 2016. "Limitation of ARIMA models in financial and monetary economics," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(4(609), W), pages 19-42, Winter.
    2. Yen-Hsien Lee, 2010. "The Impact Of Deregulation On Stock Market Efficiency," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 4(2), pages 165-176.
    3. IORGULESCU Filip, 2012. "The Stylized Facts Of Asset Returns And Their Impact On Value-At-Risk Models," Revista Economica, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 0(4), pages 360-368.
    4. Sergio Da Silva, 2004. "International Finance, Levy Distributions, and the Econophysics of Exchange Rates," International Finance 0405018, University Library of Munich, Germany.
    5. Andreea – Cristina PETRICA & Stelian STANCU, 2017. "Empirical Results of Modeling EUR/RON Exchange Rate using ARCH, GARCH, EGARCH, TARCH and PARCH models," Romanian Statistical Review, Romanian Statistical Review, vol. 65(1), pages 57-72, March.
    6. Claudeci Da Silva & Hugo Agudelo Murillo & Joaquim Miguel Couto, 2014. "Early Warning Systems: Análise De Ummodelo Probit De Contágio De Crise Dos Estados Unidos Para O Brasil(2000-2010)," Anais do XL Encontro Nacional de Economia [Proceedings of the 40th Brazilian Economics Meeting] 110, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    7. repec:onb:oenbwp:y::i:28:b:1 is not listed on IDEAS
    8. Pernagallo, Giuseppe & Torrisi, Benedetto, 2020. "Blindfolded monkeys or financial analysts: Who is worth your money? New evidence on informational inefficiencies in the U.S. stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    9. Neely, Christopher J. & Weller, Paul, 2000. "Predictability in International Asset Returns: A Reexamination," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 35(4), pages 601-620, December.
    10. Sager, Michael & Taylor, Mark P., 2014. "Generating currency trading rules from the term structure of forward foreign exchange premia," Journal of International Money and Finance, Elsevier, vol. 44(C), pages 230-250.
    11. Massimiliano Giacalone & Demetrio Panarello, 2022. "A Nonparametric Approach for Testing Long Memory in Stock Returns’ Higher Moments," Mathematics, MDPI, vol. 10(5), pages 1-21, February.
    12. Michele Ca’ Zorzi & Jakub Muck & Michal Rubaszek, 2016. "Real Exchange Rate Forecasting and PPP: This Time the Random Walk Loses," Open Economies Review, Springer, vol. 27(3), pages 585-609, July.
    13. Gagnon, Louis & Karolyi, G. Andrew, 2009. "Information, Trading Volume, and International Stock Return Comovements: Evidence from Cross-Listed Stocks," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 44(4), pages 953-986, August.
    14. Bariviera, Aurelio F. & Font-Ferrer, Alejandro & Sorrosal-Forradellas, M. Teresa & Rosso, Osvaldo A., 2019. "An information theory perspective on the informational efficiency of gold price," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    15. Mark Kamstra & Moshe Milevsky, 2005. "Waiting for returns: using space-time duality to calibrate financial diffusions," Quantitative Finance, Taylor & Francis Journals, vol. 5(3), pages 237-244.
    16. Stephen P. Huffman & Cliff R. Moll, 2013. "An examination of the relation between asymmetric risk measures, prior returns and expected daily stock returns," Review of Financial Economics, John Wiley & Sons, vol. 22(1), pages 8-19, January.
    17. Christian Gabriel & Christian Lau, 2014. "On the distribution of government bond returns: evidence from the EMU," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 28(2), pages 181-203, May.
    18. Kilian, Lutz & Taylor, Mark P., 2003. "Why is it so difficult to beat the random walk forecast of exchange rates?," Journal of International Economics, Elsevier, vol. 60(1), pages 85-107, May.
    19. Monira Essa Aloud, 2016. "Profitability of Directional Change Based Trading Strategies: The Case of Saudi Stock Market," International Journal of Economics and Financial Issues, Econjournals, vol. 6(1), pages 87-95.
    20. Clarida, Richard H. & Sarno, Lucio & Taylor, Mark P. & Valente, Giorgio, 2003. "The out-of-sample success of term structure models as exchange rate predictors: a step beyond," Journal of International Economics, Elsevier, vol. 60(1), pages 61-83, May.
    21. Paul Docherty & Steve Easton, 2012. "Market efficiency and continuous information arrival: evidence from prediction markets," Applied Economics, Taylor & Francis Journals, vol. 44(19), pages 2461-2471, July.

    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:agr:journl:v:xxiii:y:2016:i:4(609):p:19-42. 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: Marin Dinu (email available below). General contact details of provider: https://edirc.repec.org/data/agerrea.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.