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The goal of the project is to learn the trends in stock price and perform a series of trades over a period of time and end with a profit using reinforcement learning [Q-Learning] ๐Ÿ“Š

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q-learning reinforcement-learning automation data-science nvda stock-trading

automated_stock_trading-reinforcement_learning's Introduction

Automated Stock trading using Reinforcement Learning [Q-Learning] ๐Ÿ“Š

The goal of the project is to learn the trends in stock price and perform a series of trades over a period of time and end with a profit. In each trade, Bot can either buy/sell/hold. Bot will start with an investment capital of $100,000 and it's performance is measured as a percentage of the return on investment.

Q-Learning algorithm is implemented from scratch which is used for reinforcement learning to train an agent to learn the trends in stock price and perform a series of trades.

Code and Environment exlaination, Bot performance and other information can be found in the Process.pdf

Performance ๐Ÿš€

References

  • Environment of the bot was provided by TA's of course CSE 574 at University at Buffalo in Fall 2021.

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