Generative Adversarial Network for Market Hourly Discrimination

Luca Grilli and Domenico Santoro

MPRA Paper from University Library of Munich, Germany

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.

Keywords: Neural Network; Price Forecasting; Cryptocurrencies; Market Hours; Generative Model (search for similar items in EconPapers)
JEL-codes: C45 E37 F17 G17 (search for similar items in EconPapers)
Date: 2020-04-24
New Economics Papers: this item is included in nep-cmp, nep-mac and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:99846

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