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Found 15 Skills
Get stock prices, quotes, fundamentals, earnings, options, dividends, and analyst ratings using Yahoo Finance. Uses yfinance library - no API key required.
Financial time series analysis method toolkit. Covers stocks / commodity futures / cryptocurrencies / ETFs / foreign exchange / indices, full process from data acquisition to high-level analysis. Built-in 70+ analysis methods, covering 8 major method domains: time series testing, predictive modeling, cross-asset relationships, volatility risk, portfolio optimization, state recognition, commodity-specific analysis and network analysis. Tushare MCP tool (A shares/Hong Kong stocks/US stocks/futures/funds/macro) is preferred for data acquisition, and yfinance scripts are used to supplement assets not covered by tushare such as commodity futures (CL=F) and crypto (BTC-USD).
Fetch financial and market data using the yfinance Python library. Use this skill whenever the user asks for stock prices, historical data, financial statements, options chains, dividends, earnings, analyst recommendations, or any market data. Triggers include: any mention of stock price, ticker symbol (AAPL, MSFT, TSLA, etc.), "get me the financials", "show earnings", "what's the price of", "download stock data", "options chain", "dividend history", "balance sheet", "income statement", "cash flow", "analyst targets", "institutional holders", "compare stocks", "screen for stocks", or any request involving Yahoo Finance data. Always use this skill even if the user only provides a ticker — infer intent from context.
In-depth research on stocks, industries, markets, and business models. Integrates Grok API (X/Web Search) and yfinance to generate comprehensive analytical reports.
Set up the Python environment for OpenAlgo indicator analysis. Installs openalgo, plotly, dash, streamlit, numba, yfinance, matplotlib, seaborn, and creates the project folder structure.
Check stock prices using yfinance library. No API key required.
Quickly fetch data and print key backtest stats for a symbol with a default EMA crossover strategy. No file creation needed - runs inline in a notebook cell or prints to console.
Collect real financial data for any US publicly traded company from free public sources (yfinance). Output structured JSON consumable by downstream financial skills (DCF modeling, comps analysis, earnings review). Handles market data (price, shares, beta), historical financials (income statement, cash flow, balance sheet), WACC inputs, and analyst estimates. Use when users request collect data for ticker, get financials for company, pull market data, gather DCF inputs, or any task requiring structured financial data before analysis. Also triggers on financial data, company data, stock data.
Generate a pre-earnings briefing for any stock using Yahoo Finance data. Use this skill whenever the user wants to prepare for an upcoming earnings report, understand what analysts expect, review a company's beat/miss track record, or get a quick overview before an earnings call. Triggers include: "earnings preview for AAPL", "what to expect from TSLA earnings", "MSFT reports next week", "earnings preview", "pre-earnings analysis", "what are analysts expecting for NVDA", "earnings estimates for", "will GOOGL beat earnings", "earnings beat/miss history", "upcoming earnings", "before earnings", "earnings setup", "consensus estimates", "earnings whisper", "EPS expectations", "what's the street expecting", "earnings season preview", any mention of preparing for or previewing an earnings report, or any request to understand expectations ahead of a company's earnings date. Always use this skill when the user mentions a ticker in context of upcoming earnings, even if they don't say "preview" explicitly.
Analyze stock liquidity using bid-ask spreads, volume profiles, order book depth, market impact estimates, and turnover ratios via Yahoo Finance data. Use this skill whenever the user asks about liquidity, trading costs, bid-ask spread, market depth, volume analysis, slippage, market impact, turnover ratio, or how easy/hard it is to trade a stock without moving the price. Triggers: "how liquid is AAPL", "bid-ask spread", "volume analysis", "order book depth", "market impact of a large order", "turnover ratio", "slippage estimate", "can I trade 100k shares without moving the price", "liquidity comparison", "spread analysis", "ADTV", "Amihud illiquidity", "dollar volume", "execution cost estimate", "liquidity score", penny stocks, small caps, or thinly traded securities.
Generate a post-earnings analysis for any stock using Yahoo Finance data. Use when the user wants to review what happened after earnings, understand beat/miss results, see stock reaction, or get an earnings recap. Triggers: "AAPL earnings recap", "how did TSLA earnings go", "MSFT earnings results", "did NVDA beat earnings", "post-earnings analysis", "earnings surprise", "what happened with GOOGL earnings", "earnings reaction", "stock moved after earnings", "EPS beat or miss", "revenue beat or miss", "quarterly results for", "how were earnings", "AMZN reported last night", "earnings call recap", or any request about a company's recent earnings outcome. Use this skill when the user references a past earnings event, even if they just say "AAPL reported" or "how did they do".
Analyze stock correlations to find related companies and trading pairs. Use this skill whenever the user asks about correlated stocks, related companies, sector peers, trading pairs, or how two or more stocks move together. Triggers include: "what correlates with NVDA", "find stocks related to AMD", "correlation between AAPL and MSFT", "what moves with", "sector peers", "pair trading", "correlated stocks", "when NVDA drops what else drops", "find me a pair for", "stocks that move together", "beta to", "relative performance", "which stocks follow AMD", "supply chain partners", "correlation matrix", "co-movement", "related tickers", "sympathy plays", "if GOOGL moves what else moves", "semiconductor peers", "compare correlation", "hedging pair", "sector clustering", "realized correlation", "rolling correlation", or any request about finding stocks that move in tandem or inversely. Also triggers when the user mentions well-known pairs like AMD/NVDA, GOOGL/AVGO, LITE/COHR and wants to understand or find similar relationships. Always use this skill even if the user only provides one ticker — infer that they want to find correlated peers.