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CASE STUDY / 05Data Analytics

Stock Market Analysis Dashboard

NSE-focused analysis: live quotes, technicals, fundamentals, forecasts.

Stock Market Analysis Dashboard interface preview
FIELD
Capital markets · Data analytics · Retail investing tools
TYPE
Data Analytics
YEAR
2025
STATUS
Open source

The idea behind it.

StockVision is a professional-grade stock analysis dashboard for the Indian market (NSE). It consolidates live quotes, technical indicators, financial statements, and short-horizon price forecasts in one dark, data-dense interface.

Analysts can pull any NSE ticker (e.g. RELIANCE.NS, TCS.NS), inspect intraday and multi-timeframe charts, compare normalized performance across tickers, and review fundamentals, quarterly results, balance sheet, cash flow, and key ratios.

Predictions use linear regression for a simple 5-day forward view — useful as a teaching and prototyping layer alongside classic technicals (SMA, RSI, Bollinger Bands).

What it does

  • Live quotes: price, OHLC, volume, % change for NSE tickers
  • Intraday candlesticks and 1W / 1M / 3M / 1Y history
  • Technical overlays: SMA 20/50, RSI, Bollinger Bands
  • Normalized multi-ticker comparison charts
  • Company fundamentals and key financial ratios
  • Quarterly results, balance sheet, cash flow, income statement
  • 5-day linear-regression price forecast
  • Auto-refresh every 5 minutes + manual refresh

Where it fits

  • Retail traders screening NSE names with technical + fundamental context
  • Students learning how market data APIs feed interactive dashboards
  • Analysts comparing two tickers on a shared percentage scale
  • Quick research before deeper due diligence in a full brokerage terminal

The challenges

  • Handling missing or delayed market data gracefully
  • Keeping a dense multi-panel UI readable without clutter
  • Separating educational forecasts from production trading signals

What I took away

  • Dashboard layout and refresh strategy matter as much as indicators
  • Financial statement views need careful null handling from free APIs
  • Simple models are fine when framed as exploratory, not guarantees
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