About US Regulatory Alerts - Financial Sector

The US Regulatory Alerts dataset by RegAlytics tracks US regulatory changes within the financial services sector. The data covers 400,000 alerts, starts from January 2020, and is delivered on a daily basis. This dataset is created by sourcing information from over 5,000 regulators and using proprietary technology to gather and structure the regulatory data. Once prepared, the data is thoroughly reviewed by RegAlytics' team of regulatory experts and delivered each morning by 8AM for industry use.

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 RegAlytics

RegAlytics was founded by Mary Kopczynski, Aaron Heisler, Alexander Appugliese, and Werner Pauliks in 2019 with the goal of significantly reducing the time and cost required to mitigate regulatory risk. RegAlytics provides access to accurate and clean regulatory data from all global regulators in all sectors that is enriched by regulatory experts for risk and compliance teams everywhere. Please come to RegAlytics directly if you would like data on other sectors or countries!

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About QuantConnect

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Algorithm Example

class RegalyticsDataAlgorithm(QCAlgorithm): 
    negative_sentiment_phrases = ["emergency rule", "proposed rule change", "development of rulemaking"]
    def Initialize(self) -> None:
        self.SetStartDate(2022, 7, 10)
        self.SetEndDate(2022, 7, 15)
        self.symbol = self.AddEquity("SPY", Resolution.Daily).Symbol
        # Requesting data
        self.regalyticsSymbol = self.AddData(RegalyticsRegulatoryArticles, "REG").Symbol
        # Historical data
        history = self.History(self.regalyticsSymbol, 7, Resolution.Daily)
        self.Debug(f"We got {len(history)} items from our history request")

    def OnData(self, slice: Slice) -> None:
        data = slice.Get(RegalyticsRegulatoryArticles)
        if data:
            for articles in data.values():
                if any([p in article.Title.lower() for p in self.negative_sentiment_phrases for article in articles]):
                    self.SetHoldings(self.symbol, -1)
                    self.SetHoldings(self.symbol, 1)

Example Applications

The US Regulator Alters dataset enables you to accurately design strategies while mitigating regulatory risk. Examples include the following strategies: