Skip to main content

Quiver Quantitative Alternative Data

Project description

Quiver Quantitative Alternative Data

This package allows you to access several alternative data sources which are updated daily and mapped to tickers. These include:

  • Trading by US congressmen
  • Corporate Lobbying
  • Government Contracts
  • Insider Transactions
  • Hedge Fund Moves
  • Executive Compensation
  • Corporate Election Donations
  • Patents
  • Off-exchange short volume
  • Companies' Wikipedia page views
  • Discussion on Reddit's r/wallstreetbets
  • Companies' Twitter followings
  • Flights by corporate private jets

This data can be used for backtesting and implementing trading strategies.

You can find full documentation on the Quiver Quantitative API here.

Receiving API Token

You can sign up for a Quiver API token here.

The pricing starts at $30/month, please e-mail me if that is an issue and I may be able to help cover.

Getting Started

Prerequisites

  • Python version 3 installed locally
  • Pip installed locally

Installation

The package can easily be installed in your terminal by entering

pip install quiverquant

Usage

#Import the package
import quiverquant

#Connect to the API using your token
#Replace <TOKEN> with your token
quiver = quiverquant.quiver("<TOKEN>")




#Get the most recent stock news (across all tickers)
dfNews = quiver.news()


#Get the most recent Oracle stock news
dfNews_oracle = quiver.news(ticker="ORCL")


#Get recent trades by members of U.S. Congress
dfCongress = quiver.congress_trading()

#Get trades of a Tesla by members of congress
dfCongress_Tesla = quiver.congress_trading("TSLA")

#Get trades made by U.S. Senator Richard Burr
dfCongress_Burr = quiver.congress_trading("Richard Burr", politician=True)

#Get data on recent insider transactions
dfInsiders = quiver.insiders()

#Get data on recent insider transactions by Tesla insiders
dfInsiders_Tesla = quiver.insiders("TSLA")


#Get data on recent hedge fund moves in Amazon
df13F_Amazon = quiver.sec13FChanges(ticker="AMZN")

#Get data on holdings in Situational Awareness' portfolio
df13F_fund = quiver.sec13F(owner="Situational Awareness LP")


#Get data on the top Walmart shareholders
dfShareholders_Walmart = quiver.top_shareholders(ticker="WMT")

#Get data on executive compensation at Nvidia
dfCompensation_Nvidia = quiver.executive_compensation(ticker='NVDA')

#Get data on election donations by Chevron
dfDonations_Chevron = quiver.corporate_donors(ticker="CVX")


#Get recent corporate lobbying
dfLobbying = quiver.lobbying()

#Get corporate lobbying by Apple
dfLobbying_Apple = quiver.lobbying("AAPL")

#Get data on government contracts
dfContracts = quiver.gov_contracts()

#Get data on government contracts to Lockheed Martin
dfContracts_Lockheed = quiver.gov_contracts("LMT")

#Get data on off-exchange short volume
dfOTC = quiver.offexchange()

#Get data on off-exchange short volume for AMC
dfOTC_AMC = quiver.offexchange("AMC")

#Get data on Wikipedia page views
dfWiki = quiver.wikipedia()

#Get data on Wikipedia page views of Microsoft
dfWiki_Microsoft = quiver.wikipedia("MSFT")


#Get data on patents by Apple
dfPatents_Apple = quiver.patents("AAPL")

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

quiverquant-0.2.6.tar.gz (5.3 kB view details)

Uploaded Source

Built Distribution

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

quiverquant-0.2.6-py3-none-any.whl (5.5 kB view details)

Uploaded Python 3

File details

Details for the file quiverquant-0.2.6.tar.gz.

File metadata

  • Download URL: quiverquant-0.2.6.tar.gz
  • Upload date:
  • Size: 5.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.6.1 requests/2.31.0 setuptools/51.1.1 requests-toolbelt/0.9.1 tqdm/4.62.0 CPython/3.7.6

File hashes

Hashes for quiverquant-0.2.6.tar.gz
Algorithm Hash digest
SHA256 fcd92eb2d42c6a362e82709eb1760c27c0779a1b43e65168a2dcb02e0651d8d6
MD5 5de863531923074cb8b49733dcb4903b
BLAKE2b-256 6ddb22bf0cf8d2818d98e74cf4901379334fd5bb2334c97e162b603e6855b2ae

See more details on using hashes here.

File details

Details for the file quiverquant-0.2.6-py3-none-any.whl.

File metadata

  • Download URL: quiverquant-0.2.6-py3-none-any.whl
  • Upload date:
  • Size: 5.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.6.1 requests/2.31.0 setuptools/51.1.1 requests-toolbelt/0.9.1 tqdm/4.62.0 CPython/3.7.6

File hashes

Hashes for quiverquant-0.2.6-py3-none-any.whl
Algorithm Hash digest
SHA256 89c1635bb8e5cb6462dd92a1e25b64e7bc2bb302dbd0d491929fe620a8e231cf
MD5 8c88cf02b4cbd5654eba024533350cde
BLAKE2b-256 36d74d2d5d9c9e3493095adb92767344d4780b5cf88a6b97f1bcdd7c3d184921

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