About US Congress Trading

The US Congress Trading dataset by Quiver Quantitative tracks US Equity trades made by members of Congress in the Senate and the House of Representatives. The data covers 1,800 US Equities, starts in January 2016, and is delivered on a daily frequency. This dataset is created by scraping SEC reports.

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 *
class QuiverCongressDataAlgorithm(QCAlgorithm):

    def Initialize(self) -> None:
        self.SetStartDate(2019, 1, 1)
        self.SetEndDate(2020, 6, 1)
        self.SetCash(100000)

        # Requesting data
        aapl = self.AddEquity("AAPL", Resolution.Daily).Symbol
        quiver_congress_symbol = self.AddData(QuiverCongress, aapl).Symbol

        # Historical data
        history = self.History(QuiverCongress, quiver_congress_symbol, 60, Resolution.Daily)
        self.Debug(f"We got {len(history)} items from our history request");

    def OnData(self, slice: Slice) -> None:
        points = slice.Get(QuiverCongress)
        
        # Determine net direction of Congress trades for each security
        net_quantity_by_symbol = {}
        for point in points.Values:
            symbol = point.Symbol.Underlying
            if symbol not in net_quantity_by_symbol:
                net_quantity_by_symbol[symbol] = 0
            net_quantity_by_symbol[symbol] += (1 if point.Transaction == OrderDirection.Buy else -1) * point.Amount
            
        for symbol, net_quantity in net_quantity_by_symbol.items():
            # Buy when Congress members have bought
            if net_quantity > 0:
                self.SetHoldings(symbol, 1)
        
            # Short sell when Congress members have sold
            else:
                self.SetHoldings(symbol, -1)

Example Applications

The US Congress Trading dataset enables you to take immediate action on trades made by informed Members of Congress. Examples include the following strategies: