Yauheniya Shynkevich

Researcher

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Biography

Yauheniya Shynkevich is a data scientist at Almax Analytics. She has completed her PhD in quantitative data science at Ulster University in 2016, the focus of her research work is on stock price forecasting using machine learning and natural-language processing. Yauheniya obtained a Financial Risk Manager (FRM) designation in 2016. Prior to starting her PhD, she worked for Allied Testing, a financial software testing company, and led projects for Deutsche Bank and Thomson Reuters as a financial engineering and QA team lead.

Selected publications

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Shynkevich, Y., Mcginnity, T., Coleman, S. & Belatreche, A. Forecasting movements of Health-Care stock prices based on different categories of news articles using multiple kernel learning. Decision Support Systems 85, 74--83 (2016). http://doi.org/10.1016/j.dss.2016.03.001
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Shynkevich, Y., Mcginnity, T., Coleman, S. & Belatreche, A. Predicting Stock Price Movements Based on Different Categories of News Articles. in (IEEE Press, 2015). http://doi.org/10.1109/SSCI.2015.107
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Shynkevich, Y., Mcginnity, T., Coleman, S. & Belatreche, A. Stock price prediction based on stock-specific and sub-industry-specific news articles. in (IEEE Press, 2015). http://doi.org/10.1109/IJCNN.2015.7280517
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Shynkevich, Y., Mcginnity, T., Coleman, S., Li, Y. & Belatreche, A. Forecasting stock price directional movements using technical indicators: Investigating window size effects on one-step-ahead forecasting. in (IEEE Press, 2014). http://doi.org/10.1109/CIFEr.2014.6924093