For the longest time I had a goal to automate Neural Market Trends with financial innovation(s) and broadcast the results to my readers. I wanted to use Rapidminer Server/Studio to build predictions using financial data, spit it out to my blog and/or twitter, lather, rinse, and repeat.
I had this goal years ago but never got around to it because I was working in a different industry. However, since that time a lot has changed. Amazon EC2 and S3 is out now, Rapidminer can live in the Cloud, new Financial Econ extensions are available, Python has continued to march forward with packages like Pandas, and Julia is on the horizon.
The fact that I’m beginning to use Python, or rather the Twython package, to finally realize my goal is cool. Right now I’m automatically posting a Tweet at 4:05PM, 5:05PM, and 6:05PM that shows my entry price and closing price for VSLR, INTC, and EWG. For the EWG post I even add the 30 day historical volatility in the Tweet. This might be super simple for a Python hacker, but for me it’s a fun tinkerish project.
Oh, did I mention that I’m doing all this via a Raspberry Pi? Yes, the Pi is perfect for stuff like this.
My next goal is to resurrect my historical volatility prediction process, automate it, and then use the Pi to mash the Rapidminer results together with an implied volatility calculation and tweet the appropriate option strategy for the upcoming week.
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