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
- Patents
- Off-exchange short volume
- Companies' Wikipedia page views
- Discussion on Reddit's r/wallstreetbets
- Discussion on Reddit's r/SPACs
- Companies' Twitter followings
- Flights by corporate private jets
- Political Beta
- Insider Transactions
This data can be used for backtesting and implementing trading strategies.
Receiving API Token
You can sign up for a Quiver API token here.
The pricing starts at $10/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 data on WallStreetBets discussion
dfWSB = quiver.wallstreetbets()
#Get data on WallStreetBets discussion of GameStop
dfWSB_GameStop = quiver.wallstreetbets("GME")
#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 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 companies' Twitter following
dfTwitter = quiver.twitter()
#Get data on GE's Twitter following
dfTwitter_GE = quiver.twitter("GE")
#Get data on r/SPACs discussion
dfSPACs = quiver.spacs()
#Get data on r/SPACs discussion of CCIV
dfSPACs_CCIV = quiver.spacs("CCIV")
#Get data on recent corporate private jet flights
dfFlights = quiver.flights()
#Get data on private jet flights by Target
dfFlights_Target = quiver.flights("TGT")
#Get data on patents by Apple
dfPatents_Apple = quiver.patents("AAPL")
#Get data on recent insider transactions
dfInsiders = quiver.insiders()
#Get data on recent insider transactions by Tesla insiders
dfInsiders_Tesla = quiver.insiders("TSLA")
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
quiverquant-0.2.2.tar.gz
(4.9 kB
view details)
Built Distribution
File details
Details for the file quiverquant-0.2.2.tar.gz
.
File metadata
- Download URL: quiverquant-0.2.2.tar.gz
- Upload date:
- Size: 4.9 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.3.0 pkginfo/1.6.1 requests/2.27.1 setuptools/51.1.1 requests-toolbelt/0.9.1 tqdm/4.62.0 CPython/3.7.6
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 200d06187c4095f695a6b6628695a409bf3fff078b80c20bff0bc7c713845b7f |
|
MD5 | c333adf3e1e71d6f586c9a345d3ee469 |
|
BLAKE2b-256 | 5ca53bedc2ee4fddc6954c94f5a76a945c91e49914f5224224f7d705d2951dad |
File details
Details for the file quiverquant-0.2.2-py3-none-any.whl
.
File metadata
- Download URL: quiverquant-0.2.2-py3-none-any.whl
- Upload date:
- Size: 5.1 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.3.0 pkginfo/1.6.1 requests/2.27.1 setuptools/51.1.1 requests-toolbelt/0.9.1 tqdm/4.62.0 CPython/3.7.6
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | db00130cd3e9d2d56f883069d1bfa6258509b32a65a51279279f8df076016555 |
|
MD5 | 6e192610c8db1d263ba92fc5ef8109ab |
|
BLAKE2b-256 | a5925ff16d86a94f5c23ac9cfb811e97f8c2a49e3efb64a32b1ab90d0b4c7f4a |