A web scraping framework for stock price modelling using deep learning methods

Abstract

This work aims to shed light to the process of web scraping, emphasizing its importance in the new ’Big Data’ era with an illustrative application of such methods in financial markets.The work essentially focuses on different scraping methodologies that can be used to obtain large quantities of heterogenous data in real time. Automatization of data extraction systems is one of the main objectives pursued in this work, immediately followed by the development of a framework for predictive modelling. Applying neural networks and deep learning methods to the data obtained through web scraping.The goal pursued is to provide the reader with some remarkable notes on how these models work while allowing room for further research and improvements on the models presented