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Float Point Errors in Python when Calculating Indicators


I've been learning the basics of Python over at DataCamp in preparation for heading over here to Quantopian.

As an early project I downloaded some historical data and wrote some python code to calculate the RSI for said data.

When I ran the code and checked it against the same calculations in Excel, however, I noticed that Excel and Python were returning quite different final results. I traced the issue back to what I believe to be float-point rounding differences/errors in the moving averages stage, that continue to get compounded and end up making a fairly large difference in the final RSI calculation (differences as large as 10 or more in some cases).

I had similar results with MACD calculations.

My question then is, how do you deal with rounding point issues, and how do you know when your numbers are correct? Having numbers slightly off wouldn't be a major issue, but being 10 points off on an RSI calculation can be quite a problem.


2 responses

Welcome to Quantopian.

It's possible that there are float-point differences, but I'd be surprised if that is the actual cause of the difference. RSI and MACD both have built-in assumptions about duration and period, and are path-dependent. My first guess would be that you have a lurking formula or data difference that you haven't discovered yet.

Perhaps if you share a Notebook with Python, and Google Sheet, we can debug them.


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Hi Dan,

That would be awesome, thank you!

I've attached the Notebook and the link for the Google Sheet is:

The Google sheet contains three pages. The first are the calculations, the second and third are the comparison between the Excel and Python outputs.

Let me know if there is anything else you need.

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