Fund Manager Rotation Analysis
Budget: $250 – $750 AUD
I need a clear, repeatable way to study the monthly returns of roughly six to ten fund managers side-by-side with their relevant benchmarks. My goal is to spot those familiar cycles of outperformance and drawdowns so I know when to trim winners and when to start accumulating positions in managers who have recently lagged.
Please focus the work around interactive line charts; that is the view I rely on most for recognising momentum shifts and reversion patterns. The source files will show each manager’s monthly return history plus the corresponding benchmark figures—nothing more, nothing less—so the solution should ingest, clean, and plot that data, then allow me to slice by date ranges or highlight a specific manager at will.
Deliverables
• A fully working visualisation (Python, R, Power BI or similar—whichever you are strongest in) that plots monthly returns and benchmark comparisons for 6-10 managers.
• Simple controls to toggle individual managers on/off and zoom into specific periods.
• Exportable summary that flags prolonged outperformance or underperformance streaks (for example, rolling 12- or 24-month excess return bands).
Acceptance criteria
The charts load from a flat file I provide, display without errors, and clearly show each manager’s performance versus benchmark on the same time axis. Interaction must remain smooth when switching between managers or time frames.
If you have questions about formats or want a data sample before starting, just let me know—otherwise I’m ready to move ahead as soon as you are.
Please focus the work around interactive line charts; that is the view I rely on most for recognising momentum shifts and reversion patterns. The source files will show each manager’s monthly return history plus the corresponding benchmark figures—nothing more, nothing less—so the solution should ingest, clean, and plot that data, then allow me to slice by date ranges or highlight a specific manager at will.
Deliverables
• A fully working visualisation (Python, R, Power BI or similar—whichever you are strongest in) that plots monthly returns and benchmark comparisons for 6-10 managers.
• Simple controls to toggle individual managers on/off and zoom into specific periods.
• Exportable summary that flags prolonged outperformance or underperformance streaks (for example, rolling 12- or 24-month excess return bands).
Acceptance criteria
The charts load from a flat file I provide, display without errors, and clearly show each manager’s performance versus benchmark on the same time axis. Interaction must remain smooth when switching between managers or time frames.
If you have questions about formats or want a data sample before starting, just let me know—otherwise I’m ready to move ahead as soon as you are.
Related categories:
Python
Data Processing
Algorithm
Statistics
Statistical Analysis
Data Visualization
Data Analysis
Power BI