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
- 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
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 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 WallStreetBets discussion of GameStop
dfWSB_GameStop = quiver.wallstreetbets("GME")
#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 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")
1 maintainer
Release files for quiverquant 0.1.24
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| quiverquant-0.1.24.tar.gz | 3.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| quiverquant-0.1.24-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 7.5 kB
Release files / quiverquant-0.1.24.tar.gz
| Download URL | quiverquant-0.1.24.tar.gz |
|---|---|
| Size | 3.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.3.0 pkginfo/1.6.1 requests/2.25.1 setuptools/51.1.1 requests-toolbelt/0.9.1 tqdm/4.42.1 CPython/3.7.6
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Release files / quiverquant-0.1.24-py3-none-any.whl
| Download URL | quiverquant-0.1.24-py3-none-any.whl |
|---|---|
| Size | 4.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.3.0 pkginfo/1.6.1 requests/2.25.1 setuptools/51.1.1 requests-toolbelt/0.9.1 tqdm/4.42.1 CPython/3.7.6
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