Semantic news analysis is how I develop more than half my trading models. I'll have one posted, and running in real-time, within one month. I've got a webpage dedicated to the people and organizations doing this work at: www.marketpsych.com/news_language_analysis.php
News algorithms?
- Thread starter dancingphil
- Start date
In terms of news algo:
I'm not an expert but it's been around for a while. Because most of the Reuters and Bloomberg news txts have a simple txt template for news, I tried developing a system out of it. Obviously, the market reacts to a similar news differently. The impact of the news differs based on the underlying market condition and it became a big task at hand to figure it out.
I'm not an expert in liguistics or computer science (and smart) so I didn't get into the rocket science stuff but I did find a few edges while researching and brainstorming to make the news system work. My conclusion became that the newsfeed itself was a form of a trigger with edge, and the significance lies with the setup part. So I took the news trigger out and put in another trigger that worked better.
Though, it was interesting how a series of news affects the market gradually. Also, as a hypothesis, how it correlates with changing market condition. From my research, solely, the sematics of the news itself don't matter so much, it's more about quantifying(maybe symoblize is a better word) the news and deriving a "bias" from the series.
Again, I'm not an expert or academic. Hopefully, someone else can shed some light to the whole thing.
I'm not an expert but it's been around for a while. Because most of the Reuters and Bloomberg news txts have a simple txt template for news, I tried developing a system out of it. Obviously, the market reacts to a similar news differently. The impact of the news differs based on the underlying market condition and it became a big task at hand to figure it out.
I'm not an expert in liguistics or computer science (and smart) so I didn't get into the rocket science stuff but I did find a few edges while researching and brainstorming to make the news system work. My conclusion became that the newsfeed itself was a form of a trigger with edge, and the significance lies with the setup part. So I took the news trigger out and put in another trigger that worked better.
Though, it was interesting how a series of news affects the market gradually. Also, as a hypothesis, how it correlates with changing market condition. From my research, solely, the sematics of the news itself don't matter so much, it's more about quantifying(maybe symoblize is a better word) the news and deriving a "bias" from the series.
Again, I'm not an expert or academic. Hopefully, someone else can shed some light to the whole thing.
Well, here's a link for an explanation of AIS for the rest of us:
http://en.wikipedia.org/wiki/Artificial_Immune_System
Well, it's another entry in my "To-Do List"
So much to do... so little time...
http://en.wikipedia.org/wiki/Artificial_Immune_System
Well, it's another entry in my "To-Do List"
So much to do... so little time...
TSGannGalt,
Can you please explain it in another way?
Thanks !
Quote from nbates:
I'd skip all the parsing and AI rigamarole and simply jump straight to the equation;
"setup part (news) + another trigger" = works better
-jmho
Rigamarole - a long and complicated and confusing procedure; "all that academic rigmarole was a waste of time"
worldreference.com
Nope. That's not it. I'm sure that if you research about static newsfeed, you realize something similar to what I found out.
But in my opinion, don't listen or ask me advice. I would wait for acrary's post on this matter. Again... I am not an expert on news algos...