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Algorithms for Noisy and Nonstationary Data: Advances in Financial Time Series Forecasting and Pattern Detection with Machine Learning

Zlicar, Blaz; (2018) Algorithms for Noisy and Nonstationary Data: Advances in Financial Time Series Forecasting and Pattern Detection with Machine Learning. Doctoral thesis (Ph.D), UCL (University College London).

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Abstract

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Type: Thesis (Doctoral)
Qualification: Ph.D
Title: Algorithms for Noisy and Nonstationary Data: Advances in Financial Time Series Forecasting and Pattern Detection with Machine Learning
Event: UCL (University College London)
Language: English
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10043123
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