IMC Prosperity 2 Trading Competition 2024

Competition Ranking

• World: 87th out of 13,500 teams.
• Canada: 12th

Overview

This repository showcases the algorithmic trading models created for the IMC Prosperity 2 Trading Competition. The models focus on real-time data processing, analysis, and decision-making based on quantitative techniques. The competition involved designing efficient trading strategies to perform in a simulated environment, competing against thousands of global teams.

Key Features

• Real-time Data Processing: The models use live market data feeds to make split-second trading decisions.
• Quantitative Analysis: Incorporates statistical methods, such as linear regression, to predict market trends.
• Optimization Techniques: Applied advanced optimization strategies to maximize profit while minimizing risk.
• Rank: Achieved a global ranking of 87th out of 13,500 teams (~Top 1%).

Strategy Overview

• Algorithmic Models: The core algorithms are based on linear regression for price prediction and technical analysis for market trend detection.
• Risk Management: Implemented a risk management system to avoid excessive losses while maximizing potential gains.
• Backtesting: Thoroughly tested trading strategies using historical data before deploying in the live environment.

Technologies Used

• Python
• NumPy, Pandas
• Scikit-learn for machine learning models
• API for real-time data feed