A stock analysis tool for quants
Project description
quantitativelib
A simple Python library for quantitative finance.
This functions mainly as a test to learn how packages are made, and hopefully to develop a customised quantitative finance library suited to my needs. Lots more to be added.
Installation
pip install quantitativelib
Features
Core Functionality Fetches historical stock data, computes returns and volatility, and generates basic price and return plots with summary statistics.
Options Pricing Implements Black–Scholes pricing for calls, puts, forwards, and binary options. Computes all standard Greeks with support for dividend yield and parameter validation.
Stochastic Calculus Simulations Supports simulation of SDEs using Euler–Maruyama and Milstein schemes. Includes built-in models such as GBM, CIR, OU, Heston, and Merton jump diffusion, with a unified interface for simulation, plotting, and statistical output.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file quantitativelib-0.3.3.tar.gz.
File metadata
- Download URL: quantitativelib-0.3.3.tar.gz
- Upload date:
- Size: 12.3 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.12.10
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
9f9c5d20e0b4b50e323b04d0606cb74e0b737813a8e6c0ac06f53d99d6223843
|
|
| MD5 |
b18031a41dfaab59a00f9060cda7d4e0
|
|
| BLAKE2b-256 |
9265c55ade04a5f485ebe4be98245e0676567482ddf33bb6a3b2c1d984263376
|
File details
Details for the file quantitativelib-0.3.3-py3-none-any.whl.
File metadata
- Download URL: quantitativelib-0.3.3-py3-none-any.whl
- Upload date:
- Size: 14.1 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.12.10
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
ce0e9ce47f8e1b0556cd53334a6464223ab951820f746c4bea617a42aa3d59a5
|
|
| MD5 |
eb8dde1d163f8b58855e321b8edfc247
|
|
| BLAKE2b-256 |
386ba7b0dd50140f334545e6cddf8da026f920ce0ebd0bd2aec5b30b824392d2
|