Skip to main content

Quantmod Python Package

Project description

The quantmod package is inspired by the popular R package of the same name but reimagined for the modern Python data stack. It’s designed to support data scientists, analysts, and AI researchers with tools for fast, flexible data exploration and visualization. Whether you're working with time series, building machine learning pipelines, or prototyping data-driven ideas, quantmod offers a clean, intuitive interface that helps you move quickly from data to insight.

Installation

The easiest way to install quantmod is using pip:

pip install quantmod

Modules

Quickstart

# Retrieves market data & ticker object 
from quantmod.markets import getData, getTicker

# Charting module
import quantmod.charts

# Option price
from quantmod.models import OptionInputs, BlackScholesOptionPricing, MonteCarloOptionPricing

# Risk measures
from quantmod.risk import RiskInputs, ValueAtRisk, ConditionalVaR, VarBacktester

# Calculates price return of different time period.
from quantmod.timeseries import *

# Technical indicators
from quantmod.indicators import ATR

# Derivatives functions
from quantmod.derivatives import maxpain

# Datasets functions
from quantmod.datasets import fetch_historical_data

Note: quantmod is currently under active development, and anticipate ongoing enhancements and additions. The aim is to continually improve the package and expand its capabilities to meet the evolving needs of the community.

Examples

Refer to the examples section for more details.

Changelog

The list of changes to quantmod between each release can be found here

Community

Join the quantmod server to share feature requests, report bugs, and discuss the package.

Legal

quatmod is distributed under the Apache Software License. See the LICENSE.txt file in the release for details.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

quantmod-0.0.9.tar.gz (435.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

quantmod-0.0.9-py3-none-any.whl (446.7 kB view details)

Uploaded Python 3

File details

Details for the file quantmod-0.0.9.tar.gz.

File metadata

  • Download URL: quantmod-0.0.9.tar.gz
  • Upload date:
  • Size: 435.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.10.14

File hashes

Hashes for quantmod-0.0.9.tar.gz
Algorithm Hash digest
SHA256 8418c0f6f35d427af40d6bf05f724052869197050dbf3b292e128f6bb1568f82
MD5 932bb265f97d9f40a167cb6327a91f0a
BLAKE2b-256 871e54199e262e471efb573f10562afe0a7c66a1c25b05b1229cc5c8bfdc3e0a

See more details on using hashes here.

File details

Details for the file quantmod-0.0.9-py3-none-any.whl.

File metadata

  • Download URL: quantmod-0.0.9-py3-none-any.whl
  • Upload date:
  • Size: 446.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.10.14

File hashes

Hashes for quantmod-0.0.9-py3-none-any.whl
Algorithm Hash digest
SHA256 a86388df1644e70409af395b84b69d7248080f55f65e5ce59c8e73b50fab9d18
MD5 32394422f076a09812fb66f9ef46e66b
BLAKE2b-256 2fa8ed5f2f3dcf46fa964ccb3a07ad8138192ae444837d9820e05c80c4988c45

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page