📅 2024-12-04 — Session: Developed Rolling Correlation Analysis and Trading Strategies
🕒 14:30–17:45
🏷️ Labels: Rolling Correlation, Trading Strategies, Python, Financial Analysis, Hedge Funds
📂 Project: Business
⭐ Priority: MEDIUM
Session Goal
The session aimed to develop and refine rolling correlation analysis techniques and trading strategies, particularly for hedge fund applications and interview preparation.
Key Activities
- Rolling Correlation Analysis: Expanded plans and executed action plans for rolling correlation analysis tailored for hedge fund strategies, including data preparation, calculation, and visualization using Python and Streamlit.
- Interview Preparation: Developed visualizations and coding tasks for interview readiness, focusing on rolling correlations and financial data visualization.
- Python Code Enhancement: Improved Python scripts for asset price trend visualization, incorporating dynamic insights, color map updates, and better handling of datetime objects.
- Investment Strategy Planning: Recalibrated metrics for CCM’s investment strategy, focusing on time scales, cross-asset dependencies, and probabilistic scenario analysis.
- Correlation and Trading Analysis: Analyzed high correlation in asset prices, relative performance ratios, and developed strategies for mean reversion and pairs trading.
- Financial Data Analysis: Set up yfinance for data analysis, calculated correlation matrices, and expanded benchmark space with uncorrelated tickers.
Achievements
- Completed detailed plans and execution strategies for rolling correlation analysis.
- Enhanced Python scripts for financial data visualization.
- Developed comprehensive trading strategies using mean reversion and pairs trading.
- Successfully fetched data and calculated correlation matrices for benchmark assets.
Pending Tasks
- Further analysis and visualization improvements for relative performance ratios and trading strategies.
- Finalize presentation structure for correlation dynamics and pairs trading.
- Explore Bayesian reasoning applications in correlation-based trading strategies.