IDEAS home Printed from https://ideas.repec.org/a/rau/journl/v11y2016i4.1p54-73.html
   My bibliography  Save this article

Can Deep Machine Learning Outsmart The Market? A Comparison Between Econometric Modelling And Long- Short Term Memory

Author

Listed:
  • Eva DEZSI

    (Babes-Bolyai University - Faculty of Business of Cluj)

  • Ioan Alin NISTOR

    (Babes-Bolyai University - Faculty of Business of Cluj)

Abstract

Using long-short term memory (LSTM) recurrent neural network (RNN) architecture, we analyse data from the Romanian stock markets in the attempt to forecast its future trend. Then we try to compare the results using the classical statistical modelling tools, further employing back testing to prove our findings. We believe that the LSTM should be the next tool in balancing portfolios and reducing market risk.

Suggested Citation

  • Eva DEZSI & Ioan Alin NISTOR, 2016. "Can Deep Machine Learning Outsmart The Market? A Comparison Between Econometric Modelling And Long- Short Term Memory," Romanian Economic Business Review, Romanian-American University, vol. 11(4.1), pages 54-73, december.
    • Handle: RePEc:rau:journl:v:11:y:2016:i:4.1:p:54-73
    as

    Download full text from publisher

    File URL: http://www.rebe.rau.ro/RePEc/rau/journl/WI16S/REBE-WI16S-A7.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Andrew Ang & Geert Bekaert, 2007. "Stock Return Predictability: Is it There?," The Review of Financial Studies, Society for Financial Studies, vol. 20(3), pages 651-707.
    2. 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.
    3. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    4. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Working Papers 111, Princeton University, Department of Economics, Center for Economic Policy Studies..
    5. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Working Papers 111, Princeton University, Department of Economics, Center for Economic Policy Studies..
    6. repec:pri:cepsud:91malkiel is not listed on IDEAS
    7. Bollerslev, Tim, 1990. "Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 498-505, August.
    8. 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.
    9. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    10. Hedayati , Amin & Hedayati , Moein & Esfandyari, Morteza, 2016. "Stock market index prediction using artificial neural network," Journal of Economics, Finance and Administrative Science, Universidad ESAN, vol. 21(41), pages 89-93.
    11. Song, Yu & Akagi, Fumio, 2016. "Application of artificial neural network for the prediction of stock market returns: The case of the Japanese stock marketAuthor-Name: Qiu, Mingyue," Chaos, Solitons & Fractals, Elsevier, vol. 85(C), pages 1-7.
    12. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Journal of Economic Perspectives, American Economic Association, vol. 17(1), pages 59-82, Winter.
    13. Alexandru Todea & Anita Pleşoianu, 2011. "Testing The Hypothesis Of Martingale On Intraday Data: The Case Of Bet Index," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 5(5(558)(su), pages 344-351, July.
    14. Victor Dragota & Dragos Stefan Oprea, 2014. "Informational Efficiency Tests on the Romanian Stock Market: A Review of the Literature," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 6(1), pages 015-028, June.
    15. Wun-Hua Chen & Jen-Ying Shih & Soushan Wu, 2006. "Comparison of support-vector machines and back propagation neural networks in forecasting the six major Asian stock markets," International Journal of Electronic Finance, Inderscience Enterprises Ltd, vol. 1(1), pages 49-67.
    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. Omer Berat Sezer & Mehmet Ugur Gudelek & Ahmet Murat Ozbayoglu, 2019. "Financial Time Series Forecasting with Deep Learning : A Systematic Literature Review: 2005-2019," Papers 1911.13288, arXiv.org.

    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. Chia-Lin Chang & Jukka Ilomäki & Hannu Laurila & Michael McAleer, 2018. "Long Run Returns Predictability and Volatility with Moving Averages," Risks, MDPI, vol. 6(4), pages 1-18, September.
    2. Nathan Jensen, 2007. "International institutions and market expectations: Stock price responses to the WTO ruling on the 2002 U.S. steel tariffs," The Review of International Organizations, Springer, vol. 2(3), pages 261-280, September.
    3. Ishani Chaudhuri & Parthajit Kayal, 2022. "Predicting Power of Ticker Search Volume in Indian Stock Market," Working Papers 2022-214, Madras School of Economics,Chennai,India.
    4. Sheriffdeen A. Tella & Olumuyiwa G. Yinusa & Ayinde Taofeek Olusola & Saban Celik, 2011. "Global Economic Crisis And Stock Markets Efficiency: Evidence From Selected Africa Countries," Bogazici Journal, Review of Social, Economic and Administrative Studies, Bogazici University, Department of Economics, vol. 25(1), pages 139-169.
    5. Siddique, Maryam, 2023. "Does the Adaptive Market Hypothesis Exist in Equity Market? Evidence from Pakistan Stock Exchange," OSF Preprints 9b5dx, Center for Open Science.
    6. Stéphane Goutte & David Guerreiro & Bilel Sanhaji & Sophie Saglio & Julien Chevallier, 2019. "International Financial Markets," Post-Print halshs-02183053, HAL.
    7. Michele Costola & Massimiliano Caporin, 2016. "Rational Learning For Risk-Averse Investors By Conditioning On Behavioral Choices," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 11(01), pages 1-26, March.
    8. Yang, Yanlin & Hu, Xuemei & Jiang, Huifeng, 2022. "Group penalized logistic regressions predict up and down trends for stock prices," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    9. Nageri Kamaldeen Ibraheem & Abdulkadir Rihanat Idowu, 2019. "Is the Nigerian Stock Market Efficient? Pre and Post 2007-2009 Meltdown Analysis," Studia Universitatis „Vasile Goldis” Arad – Economics Series, Sciendo, vol. 29(3), pages 38-63, September.
    10. Heni Boubaker & Giorgio Canarella & Rangan Gupta & Stephen M. Miller, 2023. "A Hybrid ARFIMA Wavelet Artificial Neural Network Model for DJIA Index Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 62(4), pages 1801-1843, December.
    11. Kamal, Mona, 2014. "Studying the Validity of the Efficient Market Hypothesis (EMH) in the Egyptian Exchange (EGX) after the 25th of January Revolution," MPRA Paper 54708, University Library of Munich, Germany.
    12. Bórawski, Piotr & Bełdycka-Bórawska, Aneta & Szymańska, Elżbieta Jadwiga & Jankowski, Krzysztof Józef & Dunn, James W., 2019. "Price volatility of agricultural land in Poland in the context of the European Union," Land Use Policy, Elsevier, vol. 82(C), pages 486-496.
    13. repec:idn:journl:v:1:y:2019:i:sp1:p:1-26 is not listed on IDEAS
    14. 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].
    15. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    16. Elda du Toit & John Henry Hall & Rudra Prakash Pradhan, 2018. "The day-of-the-week effect: South African stock market indices," African Journal of Economic and Management Studies, Emerald Group Publishing Limited, vol. 9(2), pages 197-212, June.
    17. Jukka Ilomäki & Hannu Laurila & Michael McAleer, 2018. "Asymmetric Risk Impacts of Chinese Tourists to Taiwan," Documentos de Trabajo del ICAE 2018-05, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    18. Chia-Lin Chang & Jukka Ilomäki & Hannu Laurila & Michael McAleer, 2018. "Moving Average Market Timing in European Energy Markets: Production Versus Emissions," Energies, MDPI, vol. 11(12), pages 1-24, November.
    19. Kwangmin Jung & Donggyu Kim & Seunghyeon Yu, 2022. "Next generation models for portfolio risk management: An approach using financial big data," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 89(3), pages 765-787, September.
    20. Bernard Njindan Iyke, 2019. "A Test Of The Efficiency Of The Foreign Exchange Market In Indonesia," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 21(12th BMEB), pages 439-464, January.
    21. Aatola, Piia & Ollikka, Kimmo & Ollikainen, Markku, 2012. "Informational Efficiency of the EU ETS market – a study of price predictability and profitable trading," Working Papers 28, VATT Institute for Economic Research.

    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:rau:journl:v:11:y:2016:i:4.1:p:54-73. 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: Alex Tabusca (email available below). General contact details of provider: https://edirc.repec.org/data/ferauro.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.