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Digitalization of data analysis tools as the key for success in the online trading markets

Author

Listed:
  • Andrii ROSKLADKA

    (Kyiv National University of Trade and Economics, Kyiv, Ukraine)

  • Roman BAIEV

    (Kyiv National University of Trade and Economics, Kyiv, Ukraine)

Abstract

Digitalization is the process, which takes places in the contemporary world, severe competition in all markets, growing demand for new and easy technologies, changing software user preferences, and much more. For the past decades of years, the share of online forex trades that had place in the world accounted for more than 90% of all forex deals. This article discusses the main points of the online trading, the prospects of this industry and key factors that may affect the industry; also, the crucial attention was paid to the online trading tools segment, as a part of the immense market in general and as a tool in the portfolio of every modern online trading specialist. The online commerce industry is one of the largest and fastest growing sectors of the world economy. It creates jobs and assets, makes people richer and provides truly equal access for all. An analysis of existing online trading tools, such as the MT4 platform, was conducted. The main characteristics of online trade in European countries and the problems of its development in Ukraine are studied. The main components of trade in the supply area were studied in detail. Based on the research of the authors, the algorithmic rules of the automated trading system (expert advisor) were described and its software implementation is created. Similar automated systems are especially helpful when specialists need to work with many charts and timeframes at once, because the system might indicate the proper market situation better, and the system won’t have any human-biased feelings, just pure strategies and algorithms.

Suggested Citation

  • Andrii ROSKLADKA & Roman BAIEV, 2021. "Digitalization of data analysis tools as the key for success in the online trading markets," Access Journal, Access Press Publishing House, vol. 2(3), pages 222-233, September.
    • Handle: RePEc:aip:access:v:2:y:2021:i:3:p:222-233
    DOI: 10.46656/access.2021.2.3(2)
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    References listed on IDEAS

    as
    1. Eddelbuettel, Dirk & Sanderson, Conrad, 2014. "RcppArmadillo: Accelerating R with high-performance C++ linear algebra," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 1054-1063.
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    More about this item

    Keywords

    innovations; online trading; algorithmic trading; strategies; stocks; forex; digital economics;
    All these keywords.

    JEL classification:

    • C19 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Other
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications

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