News Overview:
The most recent data for each symbol. This data is no older than the beginning of the previous trading day.
Attributes:Sample - Access data attribute
md.news.headline
Name | Type | Special | Information |
---|---|---|---|
headline | string | "" | News headline. |
hyperlink | string | "" | Web URL to the news story. |
provider_name | string | "" | Name of the news story provider. |
source_instructions | string | "" | Source instructions of news story. |
story_codes | string | "" | Unique identifier for the news story. |
symbols | list | None | List of symbols related to the news story. |
synopsis | string | "" | Summary of the news story. |
timestamp | muts | 0 | Timestamp of the last news event |
wire_description | string | "" | Human-readable version of the provider_name field. |
- Date ranges?
- There is a chance that the 'timestamp' field may not fall on a trading day: for example, if the previous calendar day of the simulation was not a trading day (e.g. on Mondays, or the day after market-holidays, etc) the simulator may prime the simulation with news events that happened during non-trading days simply because they happened more recently than the previous trading day. If two NewsEvent objects concerning the same symbol also have the same timestamps, they will occur in the order that the news data vendor provided them to gr8py.
from cloudquant.interfaces import Strategy
class NewsExample(Strategy):
@classmethod
def on_strategy_start(cls, md, service, account):
print service.time_to_string(service.system_time, '%Y-%m-%d')
@classmethod
def is_symbol_qualified(cls, symbol, md, service, account):
return symbol == 'SPY'
def on_start(self, md, order, service, account):
print self.symbol
def on_news(self, event, md, order, service, account):
print '\nin on_news\n\t%s\n' % service.time_to_string(service.system_time, '%H:%M:%S.%f')
print '\n\nmd.news\n'
print ' md.news.headline - ', md.news.headline
print ' md.news.hyperlink - ', md.news.hyperlink
print ' md.news.provider_name - ', md.news.provider_name
print ' md.news.source_instructions - ', md.news.source_instructions
print ' md.news.story_codes - ', md.news.story_codes
print ' md.news.symbols - ', md.news.symbols
print ' md.news.synopsis - ', md.news.synopsis
print ' md.news.timestamp - ', md.news.timestamp
print ' md.news.wire_description - ', md.news.wire_description
service.terminate()
Console
2015-03-31 XLF in on_news() 10:36:46.403000 md.news md.news.headline - Financial Select Sector: Pivot points md.news.hyperlink - md.news.provider_name - FLYWALL_ md.news.source_instructions - md.news.story_codes - IC/mveh.retl;IC/mveh;NI/Automotive;XC/NYSEArca;XC/any.US;XC/any.company;XC/any.public;MC/HOT;MC/HOT;NT/NEC;PS/p.FLYWALL_;PS/s.USEQUITY;PC/t.150330084507374;PS/Live_News_Feed;PS/src.4001.2;PS/.Live_News_Feed;SU/Technical_Analys; md.news.symbols - [] md.news.synopsis - The following are the pivot points for XLF. Pivot High: $23.960, Pivot Low: $23.810. These were calculated using the DeMark method. md.news.timestamp - 1427733907783000 md.news.wire_description - TheFlyOnTheWall
The image below shows AAPL's news from the start of the news data April 2013 until May 2018.
It shows the number of on_news calls and breaks them down by md.news.provider_name
![AAPL News](https://app.cloudquant.com/docstatic/AAPL.png)