Financial analytics / Internship
Bluestock Mutual Fund Analytics Platform
Compare mutual-fund performance, investor activity and portfolio allocation across schemes and benchmark data.
Business question
How do fund performance, risk, investor segments and portfolio allocation vary across the schemes in the dataset?
Data
Fund master, NAV history, scheme performance, investor transactions, portfolio holdings and NIFTY 50 benchmark data.
Approach
- 01Raw data sources
- 02Cleaning and ETL
- 03MySQL data layer
- 04SQL and Python analysis
- 05Performance and risk metrics
- 06Power BI dashboards
Analysis
Built measures including CAGR, Sharpe Ratio, Sortino Ratio, Alpha, Beta and Maximum Drawdown. Compared scheme performance with NIFTY 50 and used a composite scorecard to compare funds.
What I builtFour Power BI views: Industry Overview, Fund Performance, Investor Analytics, and SIP & Market Trends.
Key findings
- 01
Equity funds represented 85% of the schemes in the analysis.
- 02
Lumpsum investments represented about 58.5% of transaction activity; SIP contributions represented 6.2%.
- 03
Investors aged 26-35 were the largest segment, while T30 regions contributed about 66% of investments.
- 04
The analysis found that higher returns did not always correspond to stronger risk-adjusted fund quality.
Business context
The comparison used risk-adjusted measures alongside returns so fund performance could be reviewed across more than one metric.
Project link
More analytics work
Browse all projects