In this mini-course we will study artificial neural networks as a tool for time series classification and forecasting. We will review theoretical concepts of feedforward, convolutional and recurrent neural networks, their modern architectures and implement them in Python. The emphasis of the mini-course is on practical applications, so we will use before mentioned algorithms to forecast stock prices movements and build a real asset trading strategy and backtest it. After attending this course, students will understand basic pipeline of machine learning based time series analysis: data preprocessing, fitting the model, evaluation of results and will be able to use their own models for building algorithmic trading strategies.
Strada le Grazie 15
Partita IVA 01541040232
Codice Fiscale 93009870234
© 2018 | Università degli studi di Verona | Credits