Domain > vollib.org

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Date	IP Address
2015-02-22	219.118.71.30 (ClassC)
2023-12-19	185.199.110.153 (ClassC)
2024-07-11	185.199.109.153 (ClassC)
2024-11-04	185.199.111.153 (ClassC)

HTTP/1.1 200 OKConnection: keep-aliveContent-Length: 4445Server: GitHub.comContent-Type: text/html; charsetutf-8Last-Modified: Sat, 09 Dec 2023 04:31:45 GMTAccess-Control-Allow-Origin: *ETag: 6573edb1

!DOCTYPE html>html langen>head>    meta charsetUTF-8>    title>Welcome to vollib/title>    link relstylesheet hrefstyles.css>    meta nameviewport contentwidthdevice-width, initial-scale1, shrink-to-fitno>    !-- script typetext/javascript srcjs/index.js>/script> -->/head>body>    header>        div classlogo_area>            img srcimages/vollib-logo.svg width200px/>        /div>        div classnav>            a href# classactive>Home/a>            a hrefsource.html>Source/a>            a hrefdocumentation.html>Documentation/a>            a hrefinstallation.html>Installation/a>            a hreflicense.html>License/a>        /div>        div classsubheader>            h2 classsubheader-headline>Blazingly Fast & Accurate/h2>            p classsubheader-body>                Option Pricing • Implied Volatility • Greeksbr/>                Python • Java • TypeScript • WASM • Kotlinbr/>            /p>        /div>    /header>    div classflex>        div>            p>            Vollib is a collection of libraries for calculating option prices, implied volatility and greeks.            What makes vollib special is that it is built around Peter Jäckels LetsBeRational, an extremely            fast and accurate technique for obtaining Blacks implied volatility.            /p>            p>            LetsBeRational can obtain implied volatility from option prices with as little as two iterations            to maximum attainable precision on standard (64 bit floating point) hardware for all possible inputs.            /p>            p>            Another advantage of LetsBeRational is its fast and accurate implementation of the cumulative normal            distribution function. Jäckels implementation provides better accuracy across a wider range of inputs,            while being two orders of magnitude faster than its equivalent in scipy.stats.            /p>            p>            Building on this solid foundation, vollib provides functions to calculate option prices, implied

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