# shashankvemuri/Finance

150+ quantitative finance Python programs to help you gather, manipulate, and analyze stock market data

Repository: https://github.com/shashankvemuri/Finance
Canonical: https://ross.abutalabs.com/products/finance
Language: Python
License: MIT
License Family: permissive
Topics: stocks, stock-market, finance, python, machine-learning, data-science, technical-indicators, quantitative-finance, pandas, algorithmic-trading, stock, trading-strategies
Last push: 2026-03-26T06:24:50+00:00

## Health v2 (maintenance only)
Score: 66/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 74, release rhythm 35, longevity 100
- inputs: {"age_days": 2397, "days_push": 160, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 4193, forks 361 (observed 2026-08-28T04:08:38.831771+00:00)

## What it is
A collection of 150+ standalone Python programs for gathering, manipulating, and analyzing stock market data. It covers stock screening, machine learning for prediction, portfolio strategies, technical indicators, and data collection via APIs and web scraping.

## Use cases
- screen stocks based on technical and fundamental analysis
- predict stock prices with machine learning
- backtest trading strategies and portfolio simulations
- visualize technical indicators like RSI, MACD, and Bollinger Bands
- scrape and collect stock price and company data
- learn quantitative finance programming in Python

## When to choose
- you want ready-made example scripts for quantitative finance tasks
- you are learning Python for stock market analysis
- you need standalone programs for stock screening, indicators, or data collection

## When to avoid
- you need a production trading system or a maintained library with an API
- you require professional investment advice or guaranteed returns
- you need a single cohesive package rather than independent scripts

## Facets
- artifact type: learning-resource
- maturity: active
- function: data-science, machine-learning, web-scraping, data-visualization, trading
- domain: fintech, data-science, machine-learning, analytics
- platform: python, cross-platform
- tags: quantitative-finance, stock-market, algorithmic-trading, technical-indicators, educational, script-collection

## Member repositories
- shashankvemuri/Finance (main) score 66

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:38.831771+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T18:22:35.730292+00:00, confidence not recorded.
  - readme: https://github.com/shashankvemuri/Finance (fetched 2026-08-28T04:08:38.831771+00:00, sha 0a6445be7a5c)
- Data as of 2026-08-30T08:39:29.467469+00:00.