AlgoMetrics — Indian Stock Market Dashboard

A professional, AI-powered financial analysis dashboard for NSE and BSE listed stocks. Built with Python and deployed on Render.

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Features

Market Intelligence

• Today's Market Movers — scans Nifty 50 every 15 minutes to surface the top gainer and loser, powered by AI-generated context from Groq (Llama 3-70B)
• Candlestick Chart — interactive OHLCV chart with configurable Moving Average overlays (SMA) and range selector buttons (1M / 3M / 6M / 1Y / All)
• 20-Day Rolling Volatility — visualises risk as a standard deviation of daily returns
• Daily Returns — green/red bar chart of daily percentage moves
• Cumulative Return — total compounded gain/loss from any chosen start date

AI Analysis

• Analyst Notes — every chart has a dynamic interpretation panel that reads the actual data and generates a contextual signal (Bullish / Bearish / Mixed, Golden Cross, Death Cross, volatility regime)
• ArthBot — a Senior Quant Analyst chatbot restricted to Indian financial markets, powered by NVIDIA NIM (Llama 3-70B). Context-aware: automatically reads the currently loaded stock's price, volatility, and return on first message

Data & Search

• Full NSE equity list — live-fetched from NSE archives (~2000+ stocks), with a comprehensive fallback list if the server is unreachable
• Full BSE equity list — fetched from BSE API
• Smart search — type a company name to get a filtered recommendation list, or paste a direct ticker
• Custom date ranges — 1Y / 2Y / 5Y or fully custom start/end dates
• Excel download — export the full computed dataset (OHLCV + indicators) as .xlsx

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Project Structure

algometrics/
├── app.py                  # Main Streamlit application
├── chatbot_engine.py       # ArthBot conversation logic (legacy layer)
├── render.yaml             # Render deployment config
├── requirements.txt        # Python dependencies
└── src/
    ├── __init__.py
    ├── ai_services.py      # Centralized AI service layer (Groq + NVIDIA NIM)
    ├── faq.py              # FAQ section renderer
    ├── legal.py            # Legal disclaimers renderer
    └── utils.py            # Resilient yfinance wrapper with session_state fallback

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Tech Stack

Layer	Technology
Frontend	Streamlit + custom CSS (IBM Plex Sans)
Charts	Plotly (interactive candlestick, line, bar, area)
Market Data	yfinance (Yahoo Finance)
AI — Movers	Groq API · llama3-70b-8192
AI — Chatbot	NVIDIA NIM · meta/llama3-70b-instruct
Deployment	Render (Web Service)

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Ticker Format Reference

Exchange	Format	Example
NSE	TICKER.NS	RELIANCE.NS
BSE	SCRIP_CODE.BO	500325.BO
Nifty 50	^NSEI	^NSEI
Sensex	^BSESN	^BSESN
Nifty Bank	^NSEBANK	^NSEBANK
Nifty IT	^CNXIT	^CNXIT

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Environment Variables

Set these in Render → your service → Environment:

Variable	Required	Source
NVIDIA_API_KEY	Yes	build.nvidia.com
GROQ_API_KEY	Yes	console.groq.com

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Run Locally

# 1. Clone the repo
git clone https://github.com/gitritam06/Stock-Ticker.git
cd Stock-Ticker

# 2. Install dependencies
pip install -r requirements.txt

# 3. Set environment variables
export NVIDIA_API_KEY="nvapi-xxxxxxxxxxxx"
export GROQ_API_KEY="gsk_xxxxxxxxxxxx"

# 4. Run
streamlit run app.py

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Deploy on Render

1. Fork or push this repo to GitHub
2. Go to render.com → New → Web Service
3. Connect your GitHub repo — Render auto-detects render.yaml
4. Add NVIDIA_API_KEY and GROQ_API_KEY under Environment
5. Click Deploy — live in ~3 minutes at your-app.onrender.com

To update: git push — Render redeploys automatically.

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Data Notes

• Stock data is sourced from Yahoo Finance via yfinance — subject to a 15–20 minute delay
• NSE closes at 3:30 PM IST — run after 4 PM for the latest complete trading day
• Market Movers refresh every 15 minutes during trading hours
• If Yahoo Finance rate-limits a request, src/utils.py serves the last successful fetch from session_state with a non-blocking warning instead of crashing

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Disclaimer

AlgoMetrics is an independent educational tool and is not registered with or endorsed by SEBI. All content is for informational purposes only and does not constitute investment advice. See the in-app Privacy Policy & Terms of Use section for full details.

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Built with Python · Streamlit · NVIDIA NIM · Groq

Deployed on Render Cloud

[Live App →](https://algo-metrics.onrender.com)