Investment Performance Analytics
Reliable reporting starts before the chart.
A Python, SQL, and Power BI workflow for validating portfolio inputs and analyzing performance, exposure, and risk.
Trust the inputs before the returns.
The problem
Portfolio reporting can be misleading when holdings and pricing data do not agree. Duplicate records, missing prices, or mismatched ticker/date pairs need attention before downstream returns and risk measures are interpreted.
A validation layer
SQL checks identify duplicate records, missing ticker-and-date combinations, invalid price fields, and mismatches between holdings and available prices. Python/Pandas workflows standardize the datasets and prepare validated outputs.
The reporting layer
Power BI views cover portfolio returns, benchmarks, sector exposure, volatility, and drawdowns. The project documents validation rules, KPI definitions, calculation assumptions, and reporting procedures so the analysis can be reviewed and repeated.
Scope
The emphasis is on analytical workflow and input reliability. This project is not presented as a live trading platform or evidence of investment returns. Public code and demo links are not currently available.