New Technologies in the Financial Market After the End of the Pandemic: Extrapolation or Innovation?

Svetlana Yu. Yanova (), Tatiana A. Fedorova (), Evgeny A. Konnikov () and Elena N. Klochkova ()
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Svetlana Yu. Yanova: Saint Petersburg State University of Economics
Tatiana A. Fedorova: Saint Petersburg State University of Economics
Evgeny A. Konnikov: Saint Petersburg State University of Economics
Elena N. Klochkova: Saint Petersburg State University of Economics

Chapter Chapter 15 in Post-COVID Economic Revival, Volume I, 2021, pp 219-234 from Springer

Abstract: Abstract This chapter “New technologies in the financial marketfinancial market after the end of the pandemic: extrapolation or innovationinnovation?” describes the author’s automated algorithm for the formation of mental maps is presented in relation to financial markets, so as to identify the main directions that the financial industryindustry’s innovative developments will take as a whole. The use of this algorithm made it possible to describe the properties of the content-thematic component of the innovative developmentdevelopment of the financial industry, the clustering of which made it possible to quantify the parameter of the selected properties’ severity in the array of natural digital informationinformation. The formation of this, on the basis of the indicated quantification parameter of the time series, made it possible to study the properties of its relationshiprelationship with a set of financial variables by means of regression analysis. This study’s significance will be felt by its generation of an automated algorithm for the formation of mental maps, as well as of a method for the quantitative interpretation of the presence of identified properties in an array of natural digital information; the significance is both practical and theoretical in nature. The relationship between the severity of the topic of the financial industry’s innovative development across an array of natural digital information and a set of certain financial variables is described using a whole set of regression models.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-83561-3_15

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DOI: 10.1007/978-3-030-83561-3_15

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