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Assessing the Investment Risk of Virtual IT Company Based on Machine Learning

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Data Stream Mining & Processing (DSMP 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1158))

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Abstract

A module for assessing the investment risks of a virtual IT company has been developed. It enables to reduce the time spent on assessing the inves-tor’s risks of a virtual IT company. A detailed justification of each selected risk parameter that influences on the success of the investment project of the virtual IT Company has done. A developed algorithm for assessing the investment risk of the virtual IT company is based on machine learning and using the expert scoring method (10 experts from 20 implemented projects were involved) by 23 risk parameters. Forecasting of investment risk assess-ment modeling of the virtual IT company using machine learning is based on eight methods: Support Vector Classifier, Stochastic Gradient Decent Classifier, Random Forest Classifier, Decision Tree Classifier, Gaussian Na-ive Bayes, K-Neighbors Classifier, Ada Boost Classifier, Logistic Regression. In addition, a module was developed to support decision-making based on three methods with the best forecast, namely: Support Vector Classifier, Random Forest Classifier, K-Neighbors Classifier.

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Author information

Authors and Affiliations

  1. Ternopil National Economic University, Lvivska Str., 11, Ternopil, 46000, Ukraine

    Hrystyna Lipyanina, Valeriya Maksymovych, Anatoliy Sachenko, Taras Lendyuk & Ivan Kit

  2. Dnipropetrovsk State University of Internal Affairs, Gagarin Avenue 26, Dnipro, Ukraine

    Andrii Fomenko

Authors
  1. Hrystyna Lipyanina
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  2. Valeriya Maksymovych
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  3. Anatoliy Sachenko
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  4. Taras Lendyuk
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  5. Andrii Fomenko
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  6. Ivan Kit
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Corresponding author

Correspondence to Taras Lendyuk .

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Editors and Affiliations

  1. Department of Informatics, Univerzita Jana Evangelisty Purkyně v Ústí nad Labem, Ústí nad Labem, Czech Republic

    Sergii Babichev

  2. GeoGuard, Kharkiv, Ukraine

    Dmytro Peleshko

  3. Kharkiv National University of Radio Electronics, Kharkiv, Ukraine

    Olena Vynokurova

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Lipyanina, H., Maksymovych, V., Sachenko, A., Lendyuk, T., Fomenko, A., Kit, I. (2020). Assessing the Investment Risk of Virtual IT Company Based on Machine Learning. In: Babichev, S., Peleshko, D., Vynokurova, O. (eds) Data Stream Mining & Processing. DSMP 2020. Communications in Computer and Information Science, vol 1158. Springer, Cham. https://doi.org/10.1007/978-3-030-61656-4_11

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  • DOI: https://doi.org/10.1007/978-3-030-61656-4_11

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