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Creating Financial Database for Education and Research: Using WEB SCRAPING Technique
Dalarna University, School of Technology and Business Studies, Microdata Analysis.
Dalarna University, School of Technology and Business Studies, Microdata Analysis.
2020 (Esperanto)Independent thesis Advanced level (degree of Master (Two Years)), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

Our objective of this thesis is to expand the microdata database of publicly available corporate information of the university by web scraping mechanism. The tool for this thesis is a web scraper that can access and concentrate information from websites utilizing a web application as an interface for client connection. In our comprehensive work we have demonstrated that the GRI text files approximately consist of 7227 companies; from the total number of companies the data is filtered with “listed” companies. Among the filtered 2252 companies some do not have income statements data. Hence, we have finally collected data of 2112 companies with 36 different sectors and 13 different countries in this thesis. The publicly available information of income statements between 2016 to 2020 have been collected by GRI of microdata department. Collecting such data from any proprietary database by web scraping may cost more than $ 24000 a year were collecting the same from the public database may cost almost nil, which we will discuss further in our thesis.In our work we are motivated to collect the financial data from the annual financial statement or financial report of the business concerns which can be used for the purpose to measure and investigate the trading costs and changes of securities, common assets, futures, cryptocurrencies, and so forth. Stock exchange, official statements and different business-related news are additionally sources of financial data that individuals will scrape. We are helping those petty investors and students who require financial statements from numerous companies for several years to verify the condition of the economy and finance concerning whether to capitalise or not, which is not possible in a conventional way; hence they use the web scraping mechanism to extract financial statements from diverse websites and make the investment decisions on further research and analysis.Here in this thesis work, we have indicated the outcome of the web scraping is to keep the extracted data in a database. The gathered data of the resulted database can be implemented for the required goal of further research, education, and other purposes with the further use of the web scraping technique.

Place, publisher, year, edition, pages
2020.
Keywords [en]
Web Scraping, GRI Text Files, Proprietary Database, Public Database, Financial Report, Financial Statement, Financial Data, Extracted Data.
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:du-36010OAI: oai:DiVA.org:du-36010DiVA, id: diva2:1525821
Available from: 2021-02-04 Created: 2021-02-04 Last updated: 2025-10-09

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Microdata Analysis
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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • chicago-author-date
  • chicago-note-bibliography
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf