登录 注册

Fast-Vollib: A Fast Implied Volatility Library for Pythonwith PyTorch, JAX, and CUDA Fused-Kernel Backends

🔗 访问原文
🔗 Access Paper

📝 摘要
Abstract

We present fast-vollib, an open-source Python library that provides high-performance European option pricing, implied volatility (IV) computation, and Greeks under the Black-76, Black-Scholes, and Black-Scholes-Merton models. The library is designed as a drop-in alternative to the de-facto-standard py_vollib and py_vollib_vectorized packages, with pluggable PyTorch and JAX execution backends, a CUDA fused-kernel Triton contribution for batched IV workloads, and a compatibility-first public API. In addition to a vectorized Halley-method IV solver, fast-vollib ships an experimental, fully-vectorized implementation of Jäckel's "Let's Be Rational" (LBR) algorithm with NumPy/Numba, torch.compile, JAX, and Triton single-pass GPU kernels for batched option chains. This note announces the library and describes its public API surface, with source, documentation, and packaging artifacts available at: GitHub (https://github.com/raeidsaqur/fast-vollib), Docs (https://raeidsaqur.github.io/fast-vollib/), PyPI (https://pypi.org/project/fast-vollib/).

📊 文章统计
Article Statistics

基础数据
Basic Stats

145 浏览
Views
0 下载
Downloads
8 引用
Citations

引用趋势
Citation Trend

阅读国家分布
Country Distribution

阅读机构分布
Institution Distribution

月度浏览趋势
Monthly Views

相关关键词
Related Keywords

影响因子分析
Impact Analysis

6.20 综合评分
Overall Score
引用影响力
Citation Impact
浏览热度
View Popularity
下载频次
Download Frequency

📄 相关文章
Related Articles

海洋智能分析Ocean AI Analysis

正在分析中,请稍候…Analyzing, please wait…
海洋智能体 🌊
海洋智能体
AI科研助手 · 2270篇文献
我看到你正在阅读一篇文献,需要我帮你解读摘要、推荐相关论文,或者分析研究方法论吗?