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Generative Adversarial Network for Market Hourly Discrimination

Author

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  • Grilli, Luca
  • Santoro, Domenico

Abstract

In this paper, we consider 2 types of instruments traded on the markets, stocks and cryptocurrencies. In particular, stocks are traded in a market subject to opening hours, while cryptocurrencies are traded in a 24-hour market. What we want to demonstrate through the use of a particular type of generative neural network is that the instruments of the non-timetable market have a different amount of information, and are therefore more suitable for forecasting. In particular, through the use of real data we will demonstrate how there are also stocks subject to the same rules as cryptocurrencies.

Suggested Citation

  • Grilli, Luca & Santoro, Domenico, 2020. "Generative Adversarial Network for Market Hourly Discrimination," MPRA Paper 99846, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:99846
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    File URL: https://mpra.ub.uni-muenchen.de/99846/1/MPRA_paper_99846.pdf
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    References listed on IDEAS

    as
    1. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    2. Gorr, Wilpen L., 1994. "Editorial: Research prospective on neural network forecasting," International Journal of Forecasting, Elsevier, vol. 10(1), pages 1-4, June.
    3. 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.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Grilli, Luca & Santoro, Domenico, 2020. "How Boltzmann Entropy Improves Prediction with LSTM," MPRA Paper 100578, University Library of Munich, Germany.

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    More about this item

    Keywords

    Neural Network; Price Forecasting; Cryptocurrencies; Market Hours; Generative Model;
    All these keywords.

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • F17 - International Economics - - Trade - - - Trade Forecasting and Simulation
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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