Financial ROI analysis of MBG.DE stock (2020-2022) using Python and AI-optimized code
Advanced Financial Data Analytics | Full-Cycle Investment Strategy
This project demonstrates a high-precision financial analysis of the Mercedes-Benz Group (MBG.DE) during a period of extreme market volatility (2020-2022). By leveraging Python-driven data science, I identified a strategic entry point during a market correction and timed a liquidation at the cyclical peak, resulting in top-tier capital appreciation.
- Return on Investment (ROI): +345% absolute growth.
- Capital Multiplier: 4.6x initial equity deployment.
- Net Realized Profit: €3,456.50 (based on a standard €1,000 position).
- Alpha Generation: Outperformed sector benchmarks through data-driven timing.
- Execution Price: €17.48 (March 2020).
- Analysis: Identified a historical support level during the global market sell-off. The technical indicators suggested an asymmetric risk-reward ratio, providing a safe but highly profitable entry window.
- Execution Price: €77.90 (February 2022).
- Analysis: Captured the peak of the automotive sector recovery. Liquidation was executed prior to the 2022 inflationary correction, preserving maximum capital gains.
To achieve these results, I developed an automated pipeline in Python:
- Data Wrangling: Processing historical OHLCV data using
Pandas. - Financial Visualization: Custom
Matplotlibdashboards for price delta and capital accumulation tracking. - Dividend Integration: Analysis of
Adj Closeto account for total shareholder return (TSR). - AI-Optimized Code: Implementation of efficient algorithms for real-time portfolio performance auditing.
The included Jupyter Notebook contains high-fidelity visualizations:
- Investment Performance Delta: Comparative analysis between entry and exit capital.
- Stock Performance Trends: Tracking the 23-month growth trajectory.
Contact & Collaboration: If you are looking for data-driven financial insights or AI-augmented market analysis, feel free to explore my repository or reach out.