Stock Liquidity

⚠️ **Trading warning / Avertissement trading** : informational only, not investment advice. Liquidity figures are measurements and model estimates of trading costs, not a recommendation to trade or to avoid a stock. Curated by Skill Harbor: a liquidity workbench that answers the question quoted prices hide, namely what it actually costs to get in and out. Its dashboard combines the quoted bid-ask spread, average and median daily volume, average dollar volume, volume variability, turnover versus shares outstanding and free float, the Amihud illiquidity ratio, and a square-root market-impact estimate for an order of 1 percent of average daily volume, then rolls them into a plain-language liquidity grade from very high to very low. Focused routes cover spread analysis (including near-the-money options spreads as derivatives context), volume analysis (relative volume, trend, day-of-week profile), order-book depth proxies, market impact for a specific order size with a full impact curve across sizes, and turnover analysis with days-to-trade-the-float. It is especially pointed at small caps, penny stocks, and thin names, where these costs quietly eat returns. Data comes from Yahoo Finance through the free yfinance library. From the himself65/finance-skills repository (MIT). Honest caveats: you need Python 3 with pip (the skill installs yfinance, pandas, and numpy itself if missing); Yahoo Finance quotes are delayed about 15 minutes on most exchanges and show top of book only, never full Level 2 depth, and the skill says so instead of pretending otherwise; impact numbers come from the standard square-root model, a planning estimate whose real cost depends on execution strategy, timing, and market conditions; liquidity can disappear around halts, events, and extended hours. Skill Harbor never reviews the code, review it yourself before use.