yfinance-data
Fetch financial and market data with the yfinance Python library (Yahoo Finance). Use this skill whenever the user wants stock data: current quotes and price history, financial statements (income statement, balance sheet, cash flow), options chains, dividends and splits, earnings and analyst estimates, price targets and ratings, institutional and insider holdings, news, multi-ticker comparisons, stock screens, or sector and industry data. Use it even when the user gives only a ticker symbol (AAPL, MSFT, TSLA) and the intent has to be inferred. For earnings previews or recaps, estimate revisions, valuation, correlation, liquidity, or ETF premium analysis, prefer the dedicated skill.
Resumen
yfinance Data Skill
Fetches financial and market data from Yahoo Finance using the yfinance Python library.
Important: yfinance is not affiliated with Yahoo, Inc. Data is for research and educational purposes.
Step 1: Ensure yfinance Is Available
Current environment status:
!`python3 -c "exec('try:\n import yfinance\n print(\'yfinance \' + yfinance.__version__ + \' installed\')\nexcept Exception:\n print(\'YFINANCE_NOT_INSTALLED\')')"`If YFINANCE_NOT_INSTALLED, install it before running any code:
import subprocess, sys
subprocess.check_call([sys.executable, "-m", "pip", "install", "-q", "yfinance"])If yfinance is already installed, skip the install step and proceed directly.
Step 2: Identify What the User Needs
Match the user's request to one or more data categories below, then use the corresponding code from references/api_reference.md.
| User Request | Data Category | Primary Method |
|---|---|---|
| Stock price, quote | Current price | ticker.info or ticker.fast_info |
| Price history, chart data | Historical OHLCV | ticker.history() or yf.download() |
| Balance sheet | Financial statements | ticker.balance_sheet |
| Income statement, revenue | Financial statements | ticker.income_stmt |
| Cash flow | Financial statements | ticker.cashflow |
| Dividends | Corporate actions | ticker.dividends |
| Stock splits | Corporate actions | ticker.splits |
| Options chain, calls, puts | Options data | ticker.option_chain() |
| Earnings, EPS | Analysis | ticker.earnings_history |
| Analyst price targets | Analysis | ticker.analyst_price_targets |
| Recommendations, ratings | Analysis | ticker.recommendations |
| Upgrades/downgrades | Analysis | ticker.upgrades_downgrades |
| Institutional holders | Ownership | ticker.institutional_holders |
| Insider transactions | Ownership | ticker.insider_transactions |
| Company overview, sector | General info | ticker.info |
| Compare multiple stocks | Bulk download | yf.download() |
| Screen/filter stocks | Screener | yf.screen() + yf.EquityQuery |
| Sector/industry data | Market data | yf.Sector / yf.Industry |
| News | News | ticker.news |
Step 3: Write and Execute the Code
General pattern
import yfinance as yf
ticker = yf.Ticker("AAPL")
# ... use the appropriate method from the referenceKey rules
- Always wrap in try/except — Yahoo Finance may rate-limit or return empty data
- Use
yf.download()for multi-ticker comparisons — it's faster with multi-threading - For options, list expiration dates first with
ticker.optionsbefore callingticker.option_chain(date) - For quarterly data, use
quarterly_prefix:ticker.quarterly_income_stmt,ticker.quarterly_balance_sheet,ticker.quarterly_cashflow - For large date ranges, be mindful of intraday limits — 1m data only goes back ~7 days, 1h data ~730 days
- Print DataFrames clearly — use
.to_string()or.to_markdown()for readability, or select key columns - Timezone handling — yfinance returns tz-aware datetime indices (e.g.,
America/New_York). When comparing dates, always usepd.Timestamp(..., tz=...)or strip timezones with.tz_localize(None). See the reference file for details.
Valid periods and intervals
| Periods | 1d, 5d, 1mo, 3mo, 6mo, 1y, 2y, 5y, 10y, ytd, max |
|---|---|
| Intervals | 1m, 2m, 5m, 15m, 30m, 60m, 90m, 1h, 1d, 5d, 1wk, 1mo, 3mo |
Step 4: Present the Data
Answer with the numbers the user asked for first, then the supporting table (markdown, or a trimmed DataFrame with the key columns). Call out anything notable in the data — an earnings beat or miss, unusual volume, a dividend change — and add context such as sector averages, historical ranges, or analyst consensus where it changes how the numbers read. If the user wants a chart, pair the data with a visualization.
Reference Files
references/api_reference.md— Complete yfinance API reference with code examples for every data category
Read the reference file when you need exact method signatures or edge case handling.
Archivos 3 archivos
Instálala a mano
Deska ejecuta esto por ti, para cada agente que elijas. Para ejecutarlo tú en una terminal:
npx skills add himself65/finance-skills --skill yfinance-dataMás de himself65
- options-payoffhimself65Render an interactive options payoff chart — expiry P&L plus Black-Scholes theoretical value — with sliders for strikes, premium, IV, DTE, and spot. Use this skill whenever the user describes or shares an options position or strategy and wants to see how it makes or loses money: vertical, calendar, diagonal, or ratio spreads, butterflies, condors and iron condors, straddles, strangles, covered calls, protective or naked puts, or any multi-leg structure. This includes pasted strikes, premiums, and expiries, requests like "show me the payoff" or "draw the P&L curve", and broker screenshots (IBKR, TastyTrade, Robinhood). Use it even when details are partial — defaults fill the gaps.3,200 instalaciones en skills.sh0
- stock-correlationhimself65Analyze how stocks move together using Yahoo Finance price history (yfinance): find correlated peers for a ticker, measure correlation, beta, and spread between specific tickers, cluster a group into a correlation matrix, and track rolling or regime-dependent correlation. Use this skill whenever the user asks what moves with a stock, what else drops when it drops, related tickers or sympathy plays, sector or supply-chain peers, pair trading or hedging pairs, beta or relative performance, correlation matrices, co-movement, or rolling/realized correlation — including well-known pairs like AMD/NVDA, GOOGL/AVGO, or LITE/COHR. With a single ticker, assume the user wants its correlated peers.3,200 instalaciones en skills.sh0
- earnings-previewhimself65Build a pre-earnings briefing for a stock from Yahoo Finance data (yfinance): the upcoming report date and timing, consensus EPS and revenue estimates with their range, the beat/miss track record, analyst ratings and price targets, and what to watch in the print. Use this skill whenever the user is preparing for an upcoming earnings report or asks what the street expects — consensus or whisper numbers, EPS expectations, whether a company will beat, an earnings setup, or an earnings-season preview — and whenever a ticker comes up in the context of upcoming earnings, even without the word "preview". For results that are already out, use earnings-recap.3,100 instalaciones en skills.sh0
- company-valuationhimself65Estimate a public company's intrinsic value with DCF, relative (peer multiple), and sum-of-the-parts (SOTP) methods, then blend them into an implied share price with upside/downside vs the market price, a WACC and terminal-growth sensitivity grid, and bull/base/bear scenarios. Use this skill whenever the user asks what a company or ticker is worth: fair value, intrinsic value, implied share price, a price target from fundamentals, whether it is overvalued or undervalued, building a DCF (WACC, terminal value, discounted cash flow), EV/EBITDA or P/E based targets, peer comparison valuation, or SOTP and conglomerate discounts. Run the model rather than answering valuation questions from memory.3,000 instalaciones en skills.sh0
- earnings-recaphimself65Analyze a company's most recent (or a specified past) earnings report from Yahoo Finance data (yfinance): actual vs estimated EPS, surprise size, revenue and margin trends, and the stock's price reaction. Use this skill whenever the user asks how earnings went — beat or miss, earnings surprise, quarterly results, the post-earnings move, or an earnings call recap — including casual references to a past report such as "AMZN reported last night" or "how did they do". For an upcoming report, use earnings-preview.3,000 instalaciones en skills.sh0
