The vast majority of quantitative analysis I do these days is either in Matlab or via the spreadsheets of Google Drive. Less commonly I’ll use Python if I need to distribute heavy web scraping among web servers or C++ if I want to use OpenCL for something very specific.

Recently I’ve been experiment with the spreadsheets on Google Drive (formerly Google Docs) and finding a lot of success. The Google Doc’s spreadhseet is a cloud based Excel analogue. There are several major advantages

1. It is far easier for a non-programmer to use than scripting languages like Matlab or Python.
2. A simple google finance protocol is integrated.
3. Other web resources can be loaded and parsed through google’s servers, which mitigates connection flooding complaints and presumably creates caching opportunities which reduces overhead on the resource.
4. It has all of the advantages of being cloud based: auto-saving, backup, easy collaboration, and remote access.

The major downsides are

1. The number of calls to google finance or remote resources are limited.
2. As spreadsheets go, it is moderately watered down compared to Excel.

“Well that sounds nice, but what can I actually do with it?”  - possibilities include, but are not limited to :

• Automatically track the price of stocks and highlight those which reach a “buy” value you set.
• Load any value from recent financial statements, allowing you to create customized valuation metrics.
• Access historical price information about stock price.
• Create charts tracking the performance of a portfolio of stocks over time.
• Automatically load and update stock ratings from third parties (morningstar, motley fools’ CAPS)for a set of tickers.

During a series of forthcoming articles, I will explain how to achieve these effects in your own spreadsheets.