Machine learning in trading: theory, models, practice and algo-trading - page 3685
You are missing trading opportunities:
- Free trading apps
- Over 8,000 signals for copying
- Economic news for exploring financial markets
Registration
Log in
You agree to website policy and terms of use
If you do not have an account, please register
RTX 4090 24gb
...
Is it possible to somehow apply methods "from there" to let the agent into the chart.
The agent will see constantly an infinite pattern pattern picture "lots of input data (essentially a bare chart), but somehow learn to "win" in this environment.
Come to think of it.
What do we see in the real world around us? Trees, houses, and lots of other things. This world has its own physical laws, gravity, inertia of bodies, laws of wave refraction, and many others. Now, trees and houses are not laws, they are data. Roughly speaking, by the location of trees and houses on the current street and several previous ones, try to predict the location of trees and houses on the next street. Is that absurd? - Of course it is. But that's exactly what happens in most cases when applying MO to market data - trying to predict trees on the next street (whatever you want, price values or increments, direction or range) is in no way revealing laws in cvr. And they even go as far as "here, if you slightly undertrain to predict trees and houses on the next street, then you will definitely get a generalisation and will be able to calculate the law of gravity in this flat world of the price chart...". No, it won't.
So yes, an agent like this on a graph should see "trees" as effects, not cause - laws. Must literally live and improve his skills by learning and navigating the laws of this candlestick world.
There don't seem to be any fixed price patterns at all. I can't say for sure, but it's like looking for familiar shapes in the sky formed by clouds (they are just clots of vapour, there are no patterns in the shape). The patterns are different - temperature, pressure and humidity, that's what forms the clouds.