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This project uses reinforcement learning to automatically hedge financial positions and reduce risk. The AI agent is trained on real stock market data from 2020 to 2023 to learn how hedging decisions change with market prices. The model is evaluated on new data to measure its performance. This project is for learning and research only.

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preettrank53/Derivative-Hedging-Using-RL

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Derivative Hedging Using Reinforcement Learning

What is This Project?

This project teaches a computer to protect investments from losing money. When people invest in stocks or options, prices can go up or down unpredictably. This creates risk. Our project builds an intelligent system that learns how to reduce this risk automatically.

The Problem We Solve

Imagine you bought something that might become more or less valuable tomorrow. You want to protect yourself from big losses. Professional traders do this by buying or selling other things that move in the opposite direction - this is called "hedging."

Doing this manually is hard because:

  • Markets change every second
  • You need to make quick decisions
  • Human emotions can lead to bad choices
  • It requires constant attention

Our Solution

We created an AI agent that learns to hedge by practicing on real stock market data. Just like a person learns to ride a bicycle by trying and falling, our AI learns to hedge by making thousands of practice trades and learning from its mistakes.

The AI practices on historical data from real companies like Tesla, NVIDIA, and Apple from 2020 to 2023. After enough practice, it learns patterns and strategies that help reduce investment risk.

What the Project Includes

  1. A training system where the AI practices and improves
  2. A dashboard to watch the AI learn in real-time
  3. Tools to test how well the AI performs on new market data
  4. A risk calculator that shows important investment numbers

Key Results

After training, the AI agent shows improvement in reducing hedging errors. The system successfully learns from real market conditions including volatile periods like the 2020 market crash and the 2022 tech selloff.

Who Can Use This

  • Students learning about finance and artificial intelligence
  • Researchers exploring machine learning in finance
  • Anyone interested in how computers can help manage investment risk

Note

This is an educational project. Real trading involves significant financial risk and requires proper licensing and expertise.

About

This project uses reinforcement learning to automatically hedge financial positions and reduce risk. The AI agent is trained on real stock market data from 2020 to 2023 to learn how hedging decisions change with market prices. The model is evaluated on new data to measure its performance. This project is for learning and research only.

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