
Financial Time Series Forecasting with Deep Learning
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In this episode of the Data Exchange I speak with Murat Özbayoğlu, Chair of Artificial Intelligence Engineering at TOBB University of Economics and Technology in Ankara, Turkey. I wanted Murat on to discuss two survey papers he and his colleagues wrote on the use of deep learning in finance.
I’ve long been fascinated with finance and trading. My first job after I left academia was as the lead quant in a hedge fund, and ever since, I’ve tried to stay abreast of what tools and techniques quants and data scientists in finance are using. Forecasting in this setting usually means price prediction or price movement (trend) prediction. Output of forecasting models are used to inform investment decisions. What makes finance particularly challenging is that many people are using the same underlying data (time series of prices/values), and thus as Murat notes, many firms use alternative data sources (such as text) as potential sources of additional signal.
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