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Creating an algorithm that uses fundamental data
Kane Walter
posted

The way I trade/invest is by using a stock scanner to find companies with various fundamentals (for example with return on assets greater than 20% etc) and then look at past financial reports to decide whether I think the company is a good buy. It's a fully manual process where I research offline then login to interactive brokers to submit my orders.

I want to try and turn my method into an algorithm to save time but don't know how to start. I haven't used python before but I'm sure I can pick it up quickly as I'm good with other scripting languages, plus R and Excel.

The first step for me would be to automate the scanning step of my method. Is this possible using Python and Quantopian? As a simple example could I use an algorithm to scan all stocks on the NASDAQ and select those that have zero long term debt for purchase?

or is it more the case in algorithmic trading that I would continue doing my analysis manually and code up the part that does the actual buying?

I'm new to algorithmic trading and not sure what the capabilities are.

Let me know if this question is too broad or not stated well.

Thanks any help appreciated.

1 response
Kane Walter

I did some more digging and found what I was looking for.

If anyone else is interested in building an algorithm using fundamental data you can pull in data from Quandl. Still not sure if I can fully automate what I do yet but at least there is a way to pull in fundamental data.

Check out the following:

https://www.quantopian.com/posts/using-the-fetcher-with-quandl

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