Ingo over at the Rapid-I blog found this link from a Rapid-I forum member about using R and Rapidminer for Trading. Â It’s a pretty wild process developed by Neural Concepts, and he goes into detail about the the win/loss ratios for the system! Â An utterly fascinating read and a job well done indeed!
It goes to show you that the application Rapidminer, and the growing plugin list, makes this software very flexible indeed for ANY application you need!
Ugly over at Uglychart.com just posted a link about research that sentiment mined over 10 million tweets from 2008 and was able to predict daily market behavior to an accuracy of 87.6%Â . Â While the post is vastly interesting from a text & sentiment miningÂ perspectiveÂ using social media, and the application of it to the stock market, I’m not 100% convinced its very viable.
Why? Well I tend to echo some of the comments left by readers at the bottom of the original post. Â For example, once this “edge” is discovered by general market participants, it tends to get discounted and the edge goes away. Â So what we read here today is probably already discounted by the market and is just routine “business as usual.”
Now, I certainly don’t mean we should abandon text & sentiment mining for the markets but rather we should continue to use these tools to develop our own secret edges and evolve them as the market changes. Â Follow the advice of poker players and underarmÂ deodorantÂ manufacturers, Â never show your hand and never let them see you sweat.
I found and installed the ECSPY evolutionary computation package and fiddled around with it. Considering I learned how to define and use functions in Python now, the example code (txt) for this Particle Swarm Optimiztation (PSO) chart below is beginning to make sense.
Long time Neural Market Trends readers might be wondering why I’m suddenly posting about Python and not Rapidminer? It’s a valid question and I do have answers.
First off, I always wanted to learn a programming language because I’ve felt that not knowing a programming language has held me back career wise, especially when I’m manipulating and data mining oodles of financial data.
Second, Python is a great way to get my feet wet learning programming! Its fun and easy so far! Ultimately the goal is to learn Java so I can truly extend Rapidminer by creating custom operators, but learning Java at this stage of the game is like swallowing a whole elephant at once; not going to happen! So I’ll start with eating a Python first.