Benzinga

Benzinga was founded by Jason Raznick in 2010 with goal of connecting the world with news, data, and education that makes the path to financial prosperity easier for everyone, everyday. Benzinga provides access to real-time news for individual investors.

The following snippet demonstrates how to request data from the Benzinga News Feed dataset:

from QuantConnect.DataSource import *

self.aapl = self.add_equity("AAPL", Resolution.DAILY).symbol
self.dataset_symbol = self.add_data(BenzingaNews, self.symbol).symbol

using QuantConnect.DataSource;

_symbol = AddEquity("AAPL", Resolution.Daily).Symbol;
_datasetSymbol = AddData<BenzingaNews>(_symbol).Symbol;

The following table describes the dataset properties:

The Benzinga News Feed enables you to accurately design strategies harnessing real-time news releases. Examples include the following strategies:

• Creating a dictionary of sentiment scores for various words and assigning a sentiment score to the content of each news release
• Calculating the sentiment of news releases with Natural Language Processing (NLP)
• Trading securities when their news releases that Benzinga tags with current buzzwords

For more example algorithms, see Examples.

The Benzinga News Feed dataset provides BenzingaNews objects, which have the following attributes:

To add Benzinga News Feed data to your algorithm, call the AddDataadd_data method. Save a reference to the dataset Symbol so you can access the data later in your algorithm.

class BenzingaNewsDataAlgorithm(QCAlgorithm):
    def initialize(self) -> None:
        self.set_start_date(2021, 1, 1)
        self.set_end_date(2021, 6, 1)
        self.set_cash(100000)
        
        self.aapl = self.add_equity("AAPL", Resolution.MINUTE).symbol
        self.dataset_symbol = self.add_data(BenzingaNews, self.symbol).symbol

namespace QuantConnect.Algorithm.CSharp.AltData
{
    public class BenzingaNewsDataAlgorithm : QCAlgorithm
    {
        private Symbol _symbol, _datasetSymbol;
        
        public override void Initialize()
        {
            SetStartDate(2021, 1, 1);
            SetEndDate(2021, 6, 1);
            SetCash(100000);
            
            _symbol = AddEquity("AAPL", Resolution.Minute).Symbol;
            _datasetSymbol = AddData<BenzingaNews>(_symbol).Symbol;
        }
    }
}

To get the current Benzinga News Feed data, index the current Slice with the dataset Symbol. Slice objects deliver unique events to your algorithm as they happen, but the Slice may not contain data for your dataset at every time step. To avoid issues, check if the Slice contains the data you want before you index it.

def on_data(self, slice: Slice) -> None:
    if slice.contains_key(self.dataset_symbol):
        article = slice[self.dataset_symbol]
        self.log(f"{self.dataset_symbol} title at {slice.time}: {article.title}")

public override void OnData(Slice slice)
{
    if (slice.ContainsKey(_datasetSymbol))
    {
        var article = slice[_datasetSymbol];
        Log($"{_datasetSymbol} title at {slice.Time}: {article.Mentions}");
    }
}

To iterate through all of the dataset objects in the current Slice, call the Getget method.

def on_data(self, slice: Slice) -> None:
    for dataset_symbol, article in slice.get(BenzingaNews).items():
        self.log(f"{dataset_symbol} title at {slice.time}: {article.title}")

public override void OnData(Slice slice)
{
    foreach (var kvp in slice.Get<BenzingaNews>())
    {
        var datasetSymbol = kvp.Key;
        var article = kvp.Value;
        Log($"{datasetSymbol} title at {slice.Time}: {article.Title}");
    }
}

To get historical Benzinga News Feed data, call the Historyhistory method with the dataset Symbol. If there is no data in the period you request, the history result is empty.

# DataFrame
history_df = self.history(self.dataset_symbol, 100, Resolution.DAILY)

# Dataset objects
history_bars = self.history[BenzingaNews](self.dataset_symbol, 100, Resolution.DAILY)

var history = History<BenzingaNews>(_datasetSymbol, 100, Resolution.Daily);

For more information about historical data, see History Requests.

To remove a subscription, call the RemoveSecurityremove_security method.

self.remove_security(self.dataset_symbol)

RemoveSecurity(_datasetSymbol);

If you subscribe to Benzinga News Feed data for assets in a dynamic universe, remove the dataset subscription when the asset leaves your universe. To view a common design pattern, see Track Security Changes.

The Benzinga News Feed enables you to accurately design strategies harnessing real-time news releases. Examples include the following strategies:

• Creating a dictionary of sentiment scores for various words and assigning a sentiment score to the content of each news release
• Calculating the sentiment of news releases with Natural Language Processing (NLP)
• Trading securities when their news releases that Benzinga tags with current buzzwords

For more example algorithms, see Examples.