Stock Portfolio Tracker in Google Docs Spreadsheet

One of the best ways to manage your money is to use a spreadsheet program such as Excel or Google Docs to create a personal portfolio tracker.

For people who are used to Excel, there was a great plugin called MSN MoneyCentral Stock Quotes Add-in which worked great for many people. However over the past few weeks the plugin doesn’t work. There is a new Stock Quotes in Excel Plugin that is working well for people. This plugin comes at a small cost but is worth purchasing. There is a 25% discount exclusively for FinanceTrain users. Get the Stock Quotes in Excel Add-in.

However, if you don’t want to spend and are open to moving from Excel to Google Spreadsheets, then you’re in luck. Google Spreadsheets come with in-built functions to help you get stock quotes and build a reliable stock portfolio. The spreadsheet gets updated automatically and can be downloaded on a need basis.

One of our readers, Roger, was kind enough to share a copy of his stock portfolio tracking spreadsheet that he built using Google Spreadsheets.

You can access the spreadsheet from the below link:

https://docs.google.com/spreadsheet/ccc?key=0AvwJ4YKNr03kdG9FbkpVY3JacEd3dnJOZXhHSU81SFE#gid=3

You need to have a Google account to use it. To save a copy into your own account, follow the following steps.

Once saved, you can modify the spreadsheet as you wish to suite your requirements.

You can also read this interesting blog post about Alternative Stock Quotes Solutions.

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Data Science in Finance: 9-Book Bundle

Data Science in Finance Book Bundle

Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.

What's Included:

  • Getting Started with R
  • R Programming for Data Science
  • Data Visualization with R
  • Financial Time Series Analysis with R
  • Quantitative Trading Strategies with R
  • Derivatives with R
  • Credit Risk Modelling With R
  • Python for Data Science
  • Machine Learning in Finance using Python

Each book comes with PDFs, detailed explanations, step-by-step instructions, data files, and complete downloadable R code for all examples.