Web Scraping in Finance using Python

Abstract

: The objective of this paper is to highlight different ways to extract financial data ( Balance Sheet, Income Statement and Cash Flow) of different companies from Yahoo finance and present an elaborate model to provide an economical, reliable and, a time-efficient tool for this purpose. It aims at aiding business analysts who are not well versed with coding but need quantitative outputs to analyse, predict, and make market decisions, by automating the process of generation of financial data. A python model, which scrapes the required data from Yahoo finance and presents it in an articulate manner in the form of an Excel sheet is implemented, along with a web application build using python with a minimalistic and simple user interface to facilitate this process. This proposed method not only removes any chances of human error caused due to manual extraction of data but also improves the overall productivity of analysts by drastically reducing the time it takes to generate the data and thus saves a substantial amount of human hours for the consumer. We also discuss different methods of scraping online data, the legal aspect of web scraping and the importance of data mining and scraping technologies in the finance industry which is highly dependent on data to analyse and make decisions.