About Corporate Lobbying

The Corporate Lobbying dataset by Quiver Quantitative tracks the lobbying activity of US Equities. The Lobbying Disclosure Act of 1995 requires lobbyists in the United States to disclose information about their activities, such as their clients, which issues they are lobbying on, and how much they are being paid. Quiver Quantiative scrapes this data and maps it to stock tickers to track which companies are spending money for legislative influence.

This dataset depends on the US Equity Security Master dataset because the US Equity Security Master dataset contains information on splits, dividends, and symbol changes.


About Quiver Quantitative

Quiver Quantitative was founded by two college students in February 2020 with the goal of bridging the information gap between Wall Street and non-professional investors. Quiver allows retail investors to tap into the power of big data and have access to actionable, easy to interpret data that hasn’t already been dissected by Wall Street.


About QuantConnect

QuantConnect was founded in 2012 to serve quants everywhere with the best possible algorithmic trading technology. Seeking to disrupt a notoriously closed-source industry, QuantConnect takes a radically open-source approach to algorithmic trading. Through the QuantConnect web platform, more than 50,000 quants are served every month.


Algorithm Example

from AlgorithmImports import *
from QuantConnect.DataSource import *

class QuiverLobbyingDataAlgorithm(QCAlgorithm):

    def initialize(self) -> None:
        self.set_start_date(2021, 10, 7)   #Set Start Date
        self.set_end_date(2022, 10, 11)    #Set End Date
        self.aapl = self.add_equity("AAPL", Resolution.DAILY).symbol
        # Subscribe to lobbying data for AAPL to generate trade signal
        self.dataset_symbol = self.add_data(QuiverLobbyings, self.symbol).symbol

        # history request
        history = self.history(self.dataset_symbol, 10, Resolution.DAILY)
        self.debug(f"We got {len(history)} items from historical data request of {self.dataset_symbol}.")

    def on_data(self, slice: Slice) -> None:
        # Trade only base on lobbying data
        for lobbyings in slice.Get(QuiverLobbyings).values():
            # Buy if over 50000 lobbying amount, suggesting a favored political prospect and sentiment
            if any([lobbying.amount > 50000 for lobbying in lobbyings]):
                self.set_holdings(self.symbol, 1)
            # Sell if below 10000 lobbying amount, suggesting a less favorable political prospect and sentiment
            elif any([lobbying.amount < 10000 for lobbying in lobbyings]):
                self.set_holdings(self.symbol, -1)

Example Applications

The Corporate Lobbying dataset enables you to create strategies using the latest information on lobbying activity. Examples include the following strategies: