Random Forest is easier to train because it is less prone to noise.
On Forex it is impossible to separate the noise from real data.
On Forex it is impossible to separate the noise from real data.
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DislikedRandom Forest is easier to train because it is less prone to noise. On Forex it is impossible to separate the noise from real data.Ignored
Disliked{quote} Can you elaborate this statement, please? By the way, do you prefer technical & fundamental both, or any specific one?Ignored
DislikedAnyone with any comment about application of reinforcement learning in trading?Ignored
DislikedHello fellow traders, I am starting this thread hoping to share with you some of my developments in the field of machine learning. Although I may not share with you exact systems or coding implementations (don't expect to get anything to "plug-and-play" and get rich from this thread) I will share with you ideas, results of my experiment and possibly other aspects of my work. I am starting this thread in the hopes that we will be able to share ideas and help each other improve our implementations. I will start with some simple machine learning strategies...Ignored
DislikedCurrently, reinforcement learning (RL) doesn't actually work in reality at least for Boston Dynamics.'' Apart from very very basic motor tasks or simple deterministic games, reinforcement learning doesn’t work at all outside of simulation'' https://www.quora.com/How-does-Bosto...chine-learning Anyone with any comment about application of reinforcement learning in trading?Ignored
Disliked{quote} Financial data exploitation using non-deterministic scenarios (environments) such as Forex data began using Monte Carlo prediction. The problem is that for high-dimensionality scenarios like Forex, it seems that Monte Carlo does not work well. https://medium.com/deep-math-machine-learning-ai For those who try to let a RL agent alone to learn FX, the environment has so many different dimensions (like trends, waves, candle combinations, relative price positions, momentum, etc...) that designing the different states information,...Ignored
Disliked{quote} Q-learning is not a good fit for forex as it is not fit for continuous tasks even with a neural network implementation such as DQN or DDQN (I actually have a DDQN+PER setup that I can plug in to my broker). I would go with policy gradient methods as they are more suited for stochastic environments and continuous tasks. If people are interested I could start a journal for my development of AI for the purpose of forex trading. I'm an university student doing my data science/software engineering degree with a minor in AI so I'm not sure how...Ignored
DislikedOne small detail you may not notice when checking the keras-rl repo. https://soygema.github.io/starcraftI...ne_learning/#0Ignored
Disliked{quote} Didn't even know Keras-rl was a thing haha. I prefer writing my own implementations (also kinda required when studying software engineering ).Ignored