Benzinga
Benzinga News Feed
Introduction
The Benzinga News Feed dataset by Benzinga tracks US Equity news releases. The data covers about 1,250 articles per day across 8,000 Equities, starts in January 2016, and is delivered on a second frequency. This dataset is created by structuring the content produced by Benzinga's editorial team.
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.
For more information about the Benzinga News Feed dataset, including CLI commands and pricing, see the dataset listing.
Getting Started
The following snippet demonstrates how to request data from the Benzinga News Feed dataset:
from QuantConnect.DataSource import *
self.symbol = self.AddEquity("AAPL", Resolution.Daily).Symbol
self.dataset_symbol = self.AddData(BenzingaNews, self.symbol).Symbol using QuantConnect.DataSource;
_symbol = AddEquity("AAPL", Resolution.Daily).Symbol;
_datasetSymbol = AddData<BenzingaNews>(_symbol).Symbol;
Requesting Data
To add Benzinga News Feed data to your algorithm, call the AddData 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.SetStartDate(2021, 1, 1)
self.SetEndDate(2021, 6, 1)
self.SetCash(100000)
self.symbol = self.AddEquity("AAPL", Resolution.Minute).Symbol
self.dataset_symbol = self.AddData(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;
}
}
}
Accessing Data
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 OnData(self, slice: Slice) -> None:
if slice.ContainsKey(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($"{_datasetSymbol} title at {slice.Time}: {article.Mentions}");
}
}
To iterate through all of the dataset objects in the current Slice, call the Get method.
def OnData(self, slice: Slice) -> None:
for dataset_symbol, article in slice.Get(BenzingaNews).items():
self.Log(f"{dataset_symbol} title at {slice.Time}: {article.Title}")
public override void OnData(Slice slice)
{
foreach (var kvp in slice.Get<BenzingaNews>())
{
var datasetSymbol = kvp.Key;
var article = kvp.Value;
Log($"{datasetSymbol} title at {slice.Time}: {article.Title}");
}
}
Historical Data
To get historical Benzinga News Feed data, call the History 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.
Remove Subscriptions
To remove a subscription, call the RemoveSecurity method.
self.RemoveSecurity(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.
Example Applications
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
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