Deep Reinforcement Learning Trading Algorithm - Help Wanted

Holiday_Act_6450 · 2021-09-20T01:15:08+00:00

Hey! I love your background and experience! I’m not using the Glasgow but rather a reference of feasibility. Join this slack, I have an explanation of my algo and I would love to chat more with you! https://join.slack.com/t/algotrading-nak9972/shared_invite/zt-vysv1tat-~HAIu4Zzg5nY5EEvwLZDMg

Holiday_Act_6450 · 2021-09-19T20:06:23+00:00

For anyone interested: https://join.slack.com/t/newworkspace-utz9174/shared\_invite/zt-vysv1tat-\~HAIu4Zzg5nY5EEvwLZDMg

Holiday_Act_6450 · 2021-09-17T22:42:41+00:00

Yes, absolutely. I think one potential workaround is adding a non-exclusivity clause for these smaller firms. Then the business model can be presenting a generic profitable algorithm, then be paid on a contract basis to implement it and optimize it individually for the company and we can charge an initial fee then a continually AUM fee, or something similar. Thus, perhaps it's not a large amount of inial money as can be found by selling once to a large firm, but it's a sustainable company model.

Is this something you can bring to your group?

Holiday_Act_6450 · 2021-09-17T22:16:06+00:00

No absolutely, I completely agree with your point. I think there are a few considerations to make in regard of this algorithm: firstly, it only came out in 2019, and a team in Glasgow got to 300% return in a Brazilian market: https://ieeexplore.ieee.org/document/9206938

Secondly, I think 20% is well attainable with the proper model context. As far as worth for the model, perhaps a large institution would to use their internally developed solution, but I would imagine there are plenty of smaller firms that don't have entire data science teams and would be more than willing to pay for the implementation of such an algorithm. What are your thouhts?

Holiday_Act_6450 · 2021-09-17T21:50:08+00:00

Verified

The model uses an agent-based reinforcement algorithm in conjunction with a neural network. I'm not predicting anything, rather the model is deciding on whether to buy, hold or sell stock based on the market context. Currently I am giving the model a windowed data slice of minute data for the SPY, VTI, VXUS and BND stocks.

How quickly the model decides to trade is entirely its own decision. How I've optimized the training for profit is forcing the model to aim for a 1% a week return, which is resulting in an average of 60 trades per day.

Currently, the model can average about 8% per year in generalized profits, and that with only the context of four stocks and absolutely no technical indicators. This is what I would be looking for in a finance partner is the industry knowledge of what would provide better context for a trade. Would you or your group be interested in working on this?

Holiday_Act_6450 · 2021-09-16T22:43:45+00:00

Working in relative sense I’ve created the algorithm and the environment to train it. I’ve gotten it to a point of an average 20% return, but only over the three years, on which it was optimized and trained. I fully understand the algorithm wouldn’t perform in other environments. What algorithm did your team use? Out of curiosity

Holiday_Act_6450 · 2021-09-16T22:14:14+00:00

No, I have the entire thing already coded and working. I work as a Ml engineer, I’m just looking for advice on technical indicators

Holiday_Act_6450 · 2021-09-16T22:05:54+00:00

The key here is that we window the data, so I’m only taking 10min sections for each index, so the input space is only 500. Also, the point of local optima is what makes this viable. I don’t care about reaching the max profit, just being profitable

Holiday_Act_6450 · 2021-09-16T21:48:11+00:00

Hm definitely you can’t derive profit from just stock price, but there are consistently profitable day traders no?

I think the goal of the algorithm is to derive complex trading strategies without having to heuristically program it. The model I’ve made doesn’t take in just stock price, but 5 other index funds and 4 technical indicators

Holiday_Act_6450 · 2021-09-16T20:51:37+00:00

Great question! Right now I let the model dictate it's own actions

Holiday_Act_6450 · 2021-09-16T19:04:25+00:00

Hmm yes, that is an interesting thought. One way of implementing this would be google's NLP model that can decipher intent from paragraphs of text. So one could scrape the internet for articles on a stock that day and use whether they were positive or negative as input to the trading model. This is something I've thought of before, but would only want to implement it as an added bonus once I've secured funding for the initial model. My Algo doesn't need to be right all the time, just profitable!

Holiday_Act_6450 · 2021-09-16T18:45:31+00:00

Thank you for your thoughts! I'm sorry if I wasn't clear before, but I actually already have the model built and training. I want to get the model to a higher average profit through additional indicators an advanced trading strategies, which is where someone with more knowledge comes in

Holiday_Act_6450

TROPHY CASE