Monday, February 19, 2018

Easily track prevailing sentiment for over 2500 securities -

Please note: this is a free service and will continue to be. I also have no money for good hosting and have absolutely no idea whether it will be able to handle a significant spike in traffic... hoping for the best!

Website: https://quikfo.com/

I made a system which tracks article headlines & social media posts for the SP500, Russell 2000, and some top market-cap cryptos, then keeps track of word association vs next-day performance, and finally uses Bayesian classification to come up with a score for each asset or security, based upon its current headlines, which indicates the likelihood that the price will rise or fall over the next day.

You can also follow the system on Twitter @myQuikfo, it posts long and short picks every morning at ~7:30am. Please keep in mind this whole thing is in beta though, so when an aspect of my system crashes shit can hit the fan and the twitter may post nonsense.

The radius of the bubble is the frequency of occurrence of a word, the hue of the bubble is the positive or negative severity (green being good, red being bad).

The system works quite well so far. Looking back on the SP500, for example, the optimal trading strategy has been to buy at market open and sell at market close anything which is scored >=85. This strategy would have returned >12.5% since trading began on 12/1.

I'll be building out a full API for developers who want to use this data themselves. Bear with me on that.

And yes, I'm aware that some of the positive/negative word associations seem crazy. How can a good word be bad or a bad word be good, one might ask. Well all this does is indicate that when a word appears, it more often than not leads to a specific market movement. One could notice that 'Fraud' is particularly green...perhaps this is because when everyone is talking about fraud, then it's already priced in and may have found a bottom. The question of why can't really be answered by the system, that's more up to the inferences of the user.

Looking for feedback from the community, please let me know what you think. There is tons of data being collected that I haven't even gotten around to building a front-end interface for. The possibilities are endless and I would love to tailor the project based upon the direction that this, and other communities, would like to see.

Thank you!



Submitted February 19, 2018 at 02:53PM by TheLoneDonut http://ift.tt/2ojvlzJ

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