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Get Started Free →Yahoo Finance market data downloader. Stock prices, options chains, fundamentals, dividends, splits, earnings, institutional holders, and financial statements. Quick data ingestion for quant research and backtesting.
| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-02 | ✗→✓ | ▲ Improved | 3% | 0% |
| case-07 | ✗→✓ | ▲ Improved | -46% | 0% |
| case-03 | ✓→✓ | ＝ Same ✓ | -30% | 0% |
| case-04 | ✓→✓ | ＝ Same ✓ | -13% | 0% |
| case-05 | ✓→✓ | ＝ Same ✓ | -19% | 0% |
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yfinance downloads Yahoo Finance market data: stock prices, options chains, fundamentals, dividends, splits, earnings, institutional holders, and financial statements. The fastest path from ticker symbol to pandas DataFrame for quant research and backtesting.
bashuv pip install yfinance
pythonimport yfinance as yf msft = yf.download("MSFT", start="2024-01-01", end="2024-12-31") print(msft.head())
pythonticker = yf.Ticker("AAPL") info = ticker.info print(f"Market cap: {info['marketCap']:,}") print(f"PE ratio: {info['trailingPE']}") print(f"Dividend yield: {info.get('dividendYield', 0)*100:.2f}%") print(ticker.balance_sheet) print(ticker.financials)
pythonopt = ticker.option_chain(ticker.options[0]) print(opt.calls[["strike", "lastPrice", "impliedVolatility", "volume"]].head()) print(opt.puts[["strike", "lastPrice", "impliedVolatility", "volume"]].head())
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