Stock Market Trading Agent Using Deep Reinforcement Learning

## Project Request

The project aims to develop a Stock Market Trading Agent using Deep Reinforcement Learning.

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| Field | Description |
| ------ | --------------------------------- |
| About | Develop a Stock Market Trading Agent using Deep Reinforcement Learning. |
| Github | ayush-09 |
| Email | ayushvarshney43@gmail.com |
| Label | Project Request |

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**Define You**

- [x] GSSOC Participant
- [x] Contributor

# Stock Market Trading Agent using Deep Reinforcement Learning

## Description

The project involves developing an intelligent trading agent that utilizes Deep Reinforcement Learning techniques to make trading decisions in the stock market. The agent will learn from historical stock price data and use a reinforcement learning algorithm to optimize its trading strategy. The goal is to create a robust and profitable trading agent that can adapt to changing market conditions and make informed trading decisions.

## Scope

Data preprocessing: The historical stock price data will be preprocessed to extract relevant features for training the trading agent.

Reinforcement Learning model: A Deep Reinforcement Learning model will be implemented to train the trading agent. The model will learn to maximize cumulative rewards by making buy/sell decisions based on the input features.

Trading strategy optimization: The trading agent will continuously optimize its trading strategy by adjusting its actions based on feedback from the market. This will involve exploring different trading policies and evaluating their performance.

Evaluation and analysis: The performance of the trading agent will be evaluated using various metrics, such as profitability, risk-adjusted returns, and comparison with benchmark strategies. The project will also include an analysis of the agent's behavior and decision-making process.

## Timeline

End Date: as soon as possible(after assigned it to me)