This repository contains my submission for the Data Science Internship evaluation. The analysis uncovers patterns relating market sentiment (Fear/Greed) to trader behavior and performance on the Hyperliquid platform.

Repository Contents

• data/: Directory intended for the sentiment.csv and hyperliquid.csv files.
• analysis.ipynb: The primary Jupyter Notebook containing the data preparation, analysis, metrics formulation, and visualization steps.
• report.md: A 1-page write-up summarizing the methodology, insights, and actionable trading rules.
• *.png: The resulting charts used as evidence to back up our insights.

Setup and How to Run

1. Clone the repository:

   git clone <repository_url>
   cd primetrade-assignment

2. Add Datasets: Ensure that the two datasets (sentiment.csv and the historical trader data renamed to hyperliquid.csv) are placed within the data/ subdirectory.

3. Environment Setup: Create a Python virtual environment and install the required dependencies:

   python3 -m venv venv
   source venv/bin/activate
   pip install pandas numpy matplotlib seaborn jupyter

4. Execute Analysis: Launch Jupyter and open the notebook to view or re-run the analysis:

   jupyter notebook analysis.ipynb

   Alternatively, you can run all cells head-to-tail to reproduce the metrics and charts.

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📊 Key Insights

🔹 Insight 1: Market Sentiment Impacts Profitability

Traders tend to generate lower average PnL during Fear periods compared to Greed periods, indicating cautious or reactive trading behavior.

🔹 Insight 2: High Leverage Increases Risk in Fear Markets

High leverage traders show greater losses during Fear conditions, suggesting amplified downside risk when market sentiment is negative.

🔹 Insight 3: Increased Activity During Greed

Trade frequency significantly increases during Greed periods, reflecting more aggressive participation and confidence in the market.

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👥 Trader Segmentation

To better understand behavioral patterns, traders were segmented into:

• High vs Low Leverage Traders
• Frequent vs Infrequent Traders
• Consistent Winners vs Inconsistent Traders

These segments reveal how different trader types respond uniquely to market sentiment.

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💡 Actionable Strategies

🚀 Strategy 1: Risk Reduction in Fear Markets

Reduce leverage exposure during Fear periods to minimize potential drawdowns, especially for high-risk traders.

🚀 Strategy 2: Selective Aggression in Greed Markets

Increase trading activity during Greed phases, but only for traders with historically consistent performance.

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