Daily Prediction of Foreign Exchange Rates Based on the Stock Marke

Bohdan Andrusyak, Thomas Kugi, Roman Kern

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review


The stock and foreign exchange markets are the two fundamental financial markets in the world and play acrucial role in international business. This paper examines the possibility of predicting the foreign exchangemarket via machine learning techniques, taking the stock market into account. We compare prediction modelsbased on algorithms from the fields of shallow and deep learning. Our models of foreign exchange marketsbased on information from the stock market have been shown to be able to predict the future of foreignexchange markets with an accuracy of over 60%. This can be seen as an indicator of a strong link between thetwo markets. Our insights offer a chance of a better understanding guiding the future of market predictions.We found the accuracy depends on the time frame of the forecast and the algorithms used, where deeplearning tends to perform better for farther-reaching forecasts
Original languageEnglish
Title of host publicationPEFnet 2017
Subtitle of host publicationProceedings
EditorsJana Stávková
PublisherMendel University Press
ISBN (Electronic)978-80-7509-555-8
Publication statusPublished - 12 Jun 2018
Event21st European Scientific Conference of Doctoral Students - Brno, Czech Republic
Duration: 30 Nov 2017 → …


Conference21st European Scientific Conference of Doctoral Students
Abbreviated titlePEFnet 2017
Country/TerritoryCzech Republic
Period30/11/17 → …

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