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")
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Release files for quiverquant 0.2.6
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-0.2.6.tar.gz | 5.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| quiverquant-0.2.6-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 10.8 kB
Release files / quiverquant-0.2.6.tar.gz
| Download URL | quiverquant-0.2.6.tar.gz |
|---|---|
| Size | 5.3 kB |
| Tags | Source |
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Release files / quiverquant-0.2.6-py3-none-any.whl
| Download URL | quiverquant-0.2.6-py3-none-any.whl |
|---|---|
| Size | 5.5 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
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| 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
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