Stock Volatility Analyzer App
Budget: ₹1,500 – ₹12,500 INR
I need a small Windows-based utility that can automatically pull end-of-day price data from NSE for any user-defined time window (for example the last 15 trading days or a full month). The universe will always be one of the standard index baskets—Nifty 100, Nifty 200, or Nifty 500—selected at run-time.
Once the data is fetched the program should:
• calculate daily returns, average return, and the standard deviation of those returns for every stock in the chosen universe;
• rank the results from lowest to highest standard deviation so I can instantly see the least and most volatile names, with a quick option to display only the top or bottom 20;
• compute momentum for the same look-back period using the formula Momentum = Current Close − Close n periods ago;
• produce a second ranking list from highest to lowest momentum.
All raw data as well as the two ranking tables must be exported to a neatly formatted Excel workbook so I can audit or share the results without further manipulation.
A clean GUI is welcome but not mandatory—functionality and accuracy matter most. If you are experienced with Python (pandas, yfinance, openpyxl) or any other Windows-friendly stack that can hit NSE data endpoints reliably, I’m happy to hear your proposal.
Once the data is fetched the program should:
• calculate daily returns, average return, and the standard deviation of those returns for every stock in the chosen universe;
• rank the results from lowest to highest standard deviation so I can instantly see the least and most volatile names, with a quick option to display only the top or bottom 20;
• compute momentum for the same look-back period using the formula Momentum = Current Close − Close n periods ago;
• produce a second ranking list from highest to lowest momentum.
All raw data as well as the two ranking tables must be exported to a neatly formatted Excel workbook so I can audit or share the results without further manipulation.
A clean GUI is welcome but not mandatory—functionality and accuracy matter most. If you are experienced with Python (pandas, yfinance, openpyxl) or any other Windows-friendly stack that can hit NSE data endpoints reliably, I’m happy to hear your proposal.