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Page 1: Accern Python - readthedocs.org

Accern PythonRelease 0.1.0

Apr 03, 2019

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Contents

1 Overview 31.1 Installation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

1.1.1 Install from PyPI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31.2 Getting started . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31.3 API . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

1.3.1 Schema Class/ Object . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41.3.1.1 Get Fields . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41.3.1.2 Get field options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41.3.1.3 Build your schema . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51.3.1.4 Validate schema . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51.3.1.5 Select and add alias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

1.3.2 REST APIs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61.3.2.1 Create API Instance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61.3.2.2 Authenticate REST API Client . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61.3.2.3 Request Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

1.3.3 Streaming API Client . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91.3.3.1 Stream Listener . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91.3.3.2 Authenticate Stream Client . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91.3.3.3 Filter and select with schema . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

1.3.4 Historical Data Request . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101.3.4.1 Create Historical Instance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101.3.4.2 Set up a job . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101.3.4.3 Check your job history . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101.3.4.4 Select and Aggregations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

1.4 Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121.4.1 REST: Request with filters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121.4.2 REST: Get one week data for restaurants entities . . . . . . . . . . . . . . . . . . . . . . . 121.4.3 Streaming: Save to csv . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131.4.4 Streaming: Create output csv structure and seperate by hour . . . . . . . . . . . . . . . . . 131.4.5 Streaming: Save to mongo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141.4.6 Historical Data: Create one historical job . . . . . . . . . . . . . . . . . . . . . . . . . . . 151.4.7 Historical Data: Check the status of a historical job . . . . . . . . . . . . . . . . . . . . . . 151.4.8 Historical Data: Read the csv from the job’s download link . . . . . . . . . . . . . . . . . . 15

1.5 Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161.5.1 Field Filter Cookbook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161.5.2 Field Aggregate Function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

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1.5.3 Field Value List . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181.5.3.1 entity_sector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181.5.3.2 entity_industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181.5.3.3 event . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 231.5.3.4 event_group . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 231.5.3.5 story_type . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

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A python library to consume Accern’s V4 REST API for Titan streaming/historical data.

Contents 1

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2 Contents

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CHAPTER 1

Overview

Accern is a fast-growing NYC startup that is disrupting the way quantitative hedge funds can gain a competitiveadvantage using news and social media data. It currently has the world’s largest financial news coverage, coveringover 1 billion public news websites, blogs, financial documents, and social media websites. Furthermore, Accernderives proprietary analytics from each news story to help quantitative hedge funds make accurate trading decisions.

Accern consolidates multiple news data feeds into one to help drastically reduce costs of both small and large hedgefunds. With Accern proprietary data filters, we are able to deliver relevant articles to clients with a 99 percent accuracyrate. Accern’s delivery mechanism is a RESTful API where it delivers derived analytics from news articles, includingthe original article URLs so quantitative hedge funds can derive their own analytics in-house from the relevant articles.

The Accern library for Python helps users get fast, flexible data structures from Accern’s V4 Titan streaming/historicaldata.

1.1 Installation

1.1.1 Install from PyPI

Accern python can be installed via pip From PyPI.

pip install accern

1.2 Getting started

This is a short tutorial on how to use accern python library for new users. You can see complex usage in API.

1. Contact [email protected]. and inquire about an Accern API token.

2. To quickly start using the Accern API, create an API instance and pass your token:

3

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from accern import APItoken = 'YOUR TOKEN'Client = API(token)

3. Pass params to get filtered data and make an API request.

schema = {'filters': {

'entity_ticker': 'AAPL'}

}resp = Client.request(schema)

4. Specify the fields that your are looking for in the data and filter the results.

schema = {'select': [

{'field': 'entity_industry'

}, {'field': 'entity_ticker'

}, {'field': 'entity_relevance'

}]

}resp = Client.request(schema)

1.3 API

1.3.1 Schema Class/ Object

Accern Python Library allows user to filter and select Accern data in 3 different ways: REST API, streaming andhistorical data request. schema object is used in these three methods to convey user’s idea of how to slice data.

Schema class here will provide some help functions and validate functions to help user build a right one.

1.3.1.1 Get Fields

Get available fields in the data.

from accern import Schemaprint Schema.get_fields()

1.3.1.2 Get field options

For field type and available options.

Schema.get_options('event_group')

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1.3.1.3 Build your schema

schema = {'select': [

{'field': 'entity_ticker','alias': 'ticker'

}],'filters': {

'entity_sentiment': [[70, 100],[-100, -70]

]}

}

1.3.1.4 Validate schema

After drafting a schema, validate it along with the method you want to use.

Schema.validate_schema(method='api', schema=schema)

1.3.1.5 Select and add alias

To select only a few fields or rename the fields, pass the alias of the fields you want to schema.

schema = {'select': [

{'field': 'entity_ticker','alias': 'ticker'

}]

}

response = Client.request(schema)

The alias for the selected fields is optional and you can select multiple fields.

schema = {'select': [

{'field': 'entity_ticker','alias': 'ticker'

}, {'field': 'harvested_at'

}]

}

response = Client.request(schema)

If you want to filter the data, here is a list of available fields to filter by:

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Parameter Descriptionentity_competitors A list of ticker symbols of entity’s competitors.entity_country The parent country of the entity.entity_industry The industry in which the entity is listed.entity_region The region where the entity is traded.entity_sector The sector that the entity belongs to.entity_ticker The traded ticker symbols of the extracted entity.entity_type The type of entity, such as public equity, commodity, cryptocurrency, etc.event Financial events extracted from the stories.event_group The broader financial events category.from The eariliest timestamp allowed in the returned data.last_id The last id before the return data.story_type Where the stories are published and their mode of access.story_group_exposure The level of exposure for stories within a story group.

For the full list and available values, you can use the helper function menthioned above.

Pass the filters to schema. The value can be a single value or an array of values.

schema = {'filters': {

'entity_industry': ['Apparel', 'Food Chains'],'event': 'Accident'

}}

response = Client.request(schema)

A list of filter examples is available at Cookbook

1.3.2 REST APIs

To start with, we import the following:

from accern import API

1.3.2.1 Create API Instance

Create an API instance

Client = API()

1.3.2.2 Authenticate REST API Client

Authenticate your account when using the API token. Pass it into the REST Client and the library will pass it to everyrequest. An API request without a token will fail.

Your API tokens carry many privileges. Don’t share your secret API tokens in any public spaces like Github, client-side code, etc.

To authenticate, pass it through the constructor or assign your YOUR TOKEN to the API instance.

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token = 'YOUR TOKEN'Client = API(token)

or

token = 'YOUR TOKEN'Client.token = token

If token is not passed or invalid, an AuthenticateError will be raised

1.3.2.3 Request Data

The request method will send a GET request to retrieve data. The response will be the most recent 100 documents.

response = Client.request()

A response example.

{"first_id": 2714394,"last_id": 2742321,"total": 100,"signals": [

{"id": 2742321,"signal_id": "3c78ab00-c751-4e37-8e16-669bad2c7135","story_id": "5a283895a656f23864041346","new_story_group": false,"overall_author_republish_score": "0.0","overall_author_timeliness_score": "2.6805","overall_source_republish_score": "0.0","overall_source_timeliness_score": "2.5707","story_group_sentiment_avg": "16.8","story_group_sentiment_stdev": "27.1","story_sentiment": null,"templated_story_score": null,"author_id": 1265989,"source_id": 22210,"story_group_count": 4,"story_group_traffic_sum": 395006047,"story_traffic": 939796,"story_group_exposure": "high","story_group_id": "e956870a-10a6-45f7-b6c1-aca6f9425886","story_source": "bloog.pl","story_type": "blog","harvested_at": "2017-12-06T18:36:13.007Z","entity_sentiment": null,"event_sentiment": null,"entity_name": "Apple Inc.","entity_ticker": "AAPL","entity_exchange": "NASDAQ","entity_relevance": "100.0","entity_country": "United States","entity_indices": [

"S&P 500","Russell 1000","Russell 3000",

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"Wilshire 5000","BARRON'S 400","NASDAQ 100"

],"entity_industry": "Computer Manufacturing","entity_region": "North America","entity_sector": "Technology","entity_competitors": [

"005930","005935","6758","2357","HPQ","MSFT","IBM","CSCO","NOKIA","MSI"

],"entity_type": "US_EQUITY","entity_composite_figi": "BBG000B9XRY4","entity_exch_code": "UW","entity_figi": "BBG000B9Y5X2","entity_market_sector": "Equity","entity_security_description": "AAPL","entity_security_type": "Common Stock","entity_share_class_figi": "BBG001S5N8V8","entity_unique_id": "EQ0010169500001000","entity_unique_id_fut_opt": null,"entity_author_republish_score": "0.0","entity_author_timeliness_score": "0.01","entity_source_republish_score": "0.0","entity_source_timeliness_score": "0.009","event": "Product Development - General","event_group": "Product Development","event_relevance": "100.0","event_author_republish_score": "0.0013","event_author_timeliness_score": "42.7356","event_source_republish_score": "0.0013","event_source_timeliness_score": "42.6185","event_impact_pct_change_avg": "0.0073","event_impact_pct_change_stdev": "0.0715","event_impact_pos": "55.9012","event_impact_neg": "44.0988","event_impact_gt_mu_add_sigma": "0.0915","event_impact_lt_mu_sub_sigma": "0.0","event_impact_gt_mu_pos_add_sigma_pos": "0.0","event_impact_lt_mu_neg_sub_sigma_neg": "0.0","event_impact_gt_mu_pos_add_2sigma_pos": "0.0","event_impact_lt_mu_neg_sub_2sigma_neg": "0.0","event_impact_gt_1pct_pos": "5.3065","event_impact_lt_1pct_neg": "3.2022"

},...

]}

To select only a few fields or filter some fields, build your schema and pass it to the function.

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schema = {'select': [

{'field': 'entity_ticker','alias': 'ticker'

}]

}

response = Client.request(schema)

1.3.3 Streaming API Client

1.3.3.1 Stream Listener

Create a StreamListener and to handle streaming data.

from accern import Stream

myStreamListener = StreamListener()

Override the on_data function if you want to handle the data yourself.

By default, it returns the raw data.

class MyStreamListener(StreamListener):def on_data(self, data):

df = json.loads(data), orient='columns')print (df.head())

1.3.3.2 Authenticate Stream Client

from accern import StreamClienttoken = 'YOUR TOKEN'

stream = StreamClient(myStreamListener, token)

1.3.3.3 Filter and select with schema

from accern import StreamClient, StreamListener

schema = {'select': [

{'field': 'entity_ticker','name': 'ticker'

},{

'field': 'harvested_at','name': 'hour'

}],

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'filters': {'entity_ticker': [

'AAPL', 'AMZN']

}}stream = StreamClient(MyStreamListener(), token, schema)stream.performs()

1.3.4 Historical Data Request

Accern Historical Batch data request is available for user who has the permission to create a job(data request). Thedata can be downloaded when the job request is finished.

1.3.4.1 Create Historical Instance

Create an Historical instance

from accern import HistoricalClienttoken = 'YOUR TOKEN'Client = HistoricalClient(token)

1.3.4.2 Set up a job

name, description, filters and select are required field to create a job schema. For more detail of how towork with filters and select, please refer to the Schema.

schema = {'name': 'test','description': 'request 2017 November data','filters': [

{'harvested_at': [

['2017-11-01 00:00:00', '2017-11-30 23:59:59']],'entity_sentiment': [

[-100, 50]]

}],'select': [

{'field': 'entity_sentiment'},{'field': 'entity_ticker'},{'field': 'event'},{'field': 'harvested_at'}

]}

1.3.4.3 Check your job history

resp = Client.get_jobs()

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If you pass a job id to the get_jobs function, you will get the information of that job.

job_id = 'YOUR JOB ID'resp = Client.get_jobs(job_id)

1.3.4.4 Select and Aggregations

You can add minute, hour, day, week, or month aggregation function to the field harvested_at. The aliasfield should match the function name you choose.

schema = {'name': 'Month','description': 'Month Sentiment data','select': [

{'field': 'harvested_at','alias': 'month','function': 'month'

}]

}

The aggregation function will group signals based on the time interval you choose. If your data will contain otherfields, an aggregation function should be given. Otherwise, an API error will occur.

schema = {'name': 'Month','description': 'Month Sentiment data','filters': [

{'harvested_at': [

['2012-08-01 00:00:00', '2017-11-30 00:00:00']],'entity_sentiment': [

[-100, 50]],'entity_ticker': [

'AAPL','AMZN'

]}

],'select': [

{'field': 'entity_sentiment','function': 'sum'

},{

'field': 'entity_ticker','function': 'group'

},{

'field': 'harvested_at','alias': 'month','function': 'month'

}

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]}

A full list of the available aggregation functions can be found at Aggregation function

1.4 Examples

1.4.1 REST: Request with filters

from accern import APITOKEN = 'YOUR TOKEN'Client = API(TOKEN)

schema = {'select': [

{'field': 'entity_ticker','name': 'ticker'

},{

'field': 'harvested_at','name': 'time'

}],'filters': {

'entity_ticker': ["AAPL", "GOOG"

]}

}

resp = Client.request(schema)

1.4.2 REST: Get one week data for restaurants entities

from accern import APIfrom datetime import datetimeimport pandas as pdrestaurants = [

'DPZ', 'SONC', 'MCD', 'CMG', 'BWLD', 'DNKN', 'TXRH', 'PZZA','EAT', 'SHAK', 'CAKE', 'YUM', 'SBUX', 'WEN', 'JACK', 'PLAY', 'DFRG','TACO', 'DENN', 'HABT', 'LOCO', 'WING', 'BLMN', 'PBPB', 'RRGB', 'FRGI','FOGO', 'DRI'

]

schema = {'select': [

{'field': 'entity_ticker'

}, {'field': 'entity_sentiment'

}, {'field': 'harvested_at'

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}, {'field': 'entity_relevance'

}],'filters': {

'entity_relevance': [70, 100],'entity_ticker': restaurants,'harvested_at': ['2017-12-01 00:00:00', '2017-12-07 00:00:00']

}}

TOKEN = 'YOUR TOKEN'Client = API(TOKEN)

response = Client.request(schema)############### Get restaurants data ###############result = pd.DataFrame()while response['total'] > 0:

df = pd.DataFrame.from_dict(response['signals'], orient='columns')result = result.append(df, ignore_index=True)schema['filters']['last_id'] = response['last_id']response = Client.request(schema)

result = result.drop_duplicates().reset_index(drop=True)result.to_csv('restaurants.csv', index=False)

1.4.3 Streaming: Save to csv

from accern import StreamClient, StreamListenerfrom datetime import datetimeimport osimport pandas as pd

class MyStreamListener(StreamListener):def on_data(self, raw_data):

df = pd.DataFrame.from_dict(raw_data, orient='columns')print ("%s - Saving %s signals..." % (datetime.now(), len(df)))if not os.path.exists('output.csv'):

df.to_csv('output.csv', encoding='utf-8', index=False)else:

df.to_csv('output.csv', mode='a', header=False, encoding='utf-8',→˓index=False)

TOKEN = 'YOUR TOKEN'stream = StreamClient(MyStreamListener(), TOKEN)stream.performs()

1.4.4 Streaming: Create output csv structure and seperate by hour

from accern import StreamListener, StreamClientfrom datetime import datetime, timedeltaimport osimport pandas as pd

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from pymongo import MongoClient

record = datetime.now()record_time = datetime(year=record.year, month=record.month, day=record.day,→˓hour=record.hour - 1, minute=0, second=0, microsecond=0)

class MyStreamListener(StreamListener):def __init__(self):

self.db = MongoClient().accern

def on_data(self, raw_data):global record_timedf = pd.DataFrame.from_dict(raw_data, orient='columns')time = datetime.now()if (time - record_time).seconds / 60 > 60:

record_time = record_time + timedelta(hours=1)df.to_csv('./accern_stream/2017-12-01/%s.csv' % (record_time.strftime('%Y-

→˓%m-%dT%H:%M:%S')), index=False, encoding='utf-8')print ('Appended %s signals' % (len(df)))

else:df.to_csv('./accern_stream/2017-12-01/%s.csv' % (record_time.strftime('%Y-

→˓%m-%dT%H:%M:%S')), index=False, mode='a', header=False, encoding='utf-8')print ('Appended %s signals' % (len(df)))

myStreamListener = MyStreamListener()

TOKEN = 'YOUR TOKEN'Streamer = StreamClient(MyStreamListener(), TOKEN)

if not os.path.exists('./accern_stream'):os.mkdir('./accern_stream')

if not os.path.exists('./accern_stream/2017-12-01'):os.mkdir('./accern_stream/2017-12-01')

Streamer.performs()

1.4.5 Streaming: Save to mongo

from accern import StreamClient, StreamListenerfrom datetime import datetimeimport jsonfrom pymongo import MongoClient

class MyStreamListener(StreamListener):def __init__(self):

self.db = MongoClient()['accern'] # Replace with your db name

def on_data(self, raw_data):data_json = raw_dataprint ("%s - Saving %s signals..." % (datetime.now(), len(data_json)))# Replace with your db, collection namesself.db['accern']['stream'].insert_many(data_json)

TOKEN = 'YOUR TOKEN'stream = StreamClient(MyStreamListener(), TOKEN)stream.performs()

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1.4.6 Historical Data: Create one historical job

A full example can be found at Historical Job Example

from accern import HistoricalClient

TOKEN = 'YOUR TOKEN'Client = HistoricalClient(TOKEN)

schema = {'name': 'Daily Sentiment','description': 'Get Daily Sentiment data',"select": [

{"field": "entity_ticker","alias": "ticker"

}, {"field": "harvested_at"

}],"filters": [

{"entity_ticker": ["AAPL", "GOOG","MSFT"]

}]

}resp = Client.create_job(schema)

1.4.7 Historical Data: Check the status of a historical job

from accern import HistoricalClientimport ioimport requestsimport pandas as pd

token = 'YOUR TOKEN'Client = HistoricalClient(token)

resp = Client.get_jobs('YOUR JOB ID')print resp['job']

1.4.8 Historical Data: Read the csv from the job’s download link

from accern import HistoricalClientimport ioimport requestsimport pandas as pd

token = 'YOUR TOKEN'Client = HistoricalClient(token)

resp = Client.get_jobs('YOUR JOB ID')link = resp['job']['link']raw_data = requests.get(link).content

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data = pd.read_csv(io.StringIO(raw_data.decode('utf-8')))print data.head()

1.5 Appendix

1.5.1 Field Filter Cookbook

Here is a cookbook of how to filter fields by using our REST API.

from accern import API

TOKEN = 'YOUR TOKEN'Client = API()Client.token = TOKEN

Filter by single event.

schema = {'filters': {

'event': 'Analyst Ratings'}

}

resp = Client.request(schema)

Filter by a list of events.

schema = {'filters': {

'event': ['Analyst Ratings', 'Corporate Actions']}

}

Get only entity_type = US_EQUITY.

schema = {'filters': {

'entity_type': 'US_EQUITY'}

}

Get only story_type = news.

schema = {'filters': {

'story_type': 'news'}

}

Get articles with low story_group_exposure.

schema = {'filters': {

'story_group_exposure': 'low'

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}}

You can provide multiple fields in the filter (they will be AND’d).

schema = {'filters': {

'event': ['Analyst Ratings', 'Corporate Actions'],'story_group_exposure': 'low','story_type': 'news'

}}

You can filter date by either from or harvested_at. The time is in UTC.

schema = {'filters': {

'from': '2017-11-01'}

}

or

schema = {'filters': {

'harvested_at': ['2017-11-01 00:00:00', '2017-11-31 00:00:00']}

}

1.5.2 Field Aggregate Function

Field Functionsauthor_id countentity_author_republish_score average, count, max, min, sumentity_author_timeliness_score average, count, max, min, sumentity_country groupentity_exch_code groupentity_exchange groupentity_industry groupentity_relevance average, count, max, min, sumentity_sentiment average, count, max, min, sumentity_source_timeliness_score average, count, max, min, sumentity_source_republish_score average, count, max, min, sumentity_ticker groupentity_type groupevent_author_timeliness_score average, count, max, min, sumevent_author_republish_score average, count, max, min, sumevent_group groupevent_source_timeliness_score min, max, avg, sumevent_source_republish_score average, count, max, min, sumevent_impact_gt_1pct_pos groupevent_impact_gt_mu_add_sigma group

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Table 1.1 – continued from previous pageField Functionsevent_impact_gt_mu_pos_add_2sigma_pos average, count, max, min, sumevent_impact_gt_mu_pos_add_sigma_pos average, count, max, min, sumevent_impact_lt_1pct_neg average, count, max, min, sumevent_impact_lt_mu_sub_sigma average, count, max, min, sumevent_impact_lt_mu_sub_add_2sigma_pos average, count, max, min, sumevent_impact_lt_mu_sub_add_sigma_pos average, count, max, min, sumevent_impact_neg average, count, max, min, sumevent_impact_pct_change_avg average, count, max, min, sumevent_impact_pct_change_stdev average, count, max, min, sumevent_impact_pos average, count, max, min, sumevent_relevance average, count, max, min, sumevent_sentiment average, count, max, min, sumevent groupharvested_at minute, hour, day, week, monthoverall_author_timeliness_score average, count, max, min, sumoverall_author_republish_score average, count, max, min, sumoverall_source_timeliness_score average, count, max, min, sumoverall_source_republish_score average, count, max, min, sumstory_group_count average, count, max, min, sumstory_group_exposure groupstory_group_traffic_sum average, count, max, min, sumstory_traffic average, count, max, min, sumstory_type grouptemplated_story_score average, count, max, min, sum

1.5.3 Field Value List

1.5.3.1 entity_sector

1.5.3.2 entity_industry

entity_sector entity_industryBasic Industries Agricultural ChemicalsBasic Industries AluminumBasic Industries Containers/PackagingBasic Industries Electric Utilities: CentralBasic Industries Engineering & ConstructionBasic Industries Environmental ServicesBasic Industries Forest ProductsBasic Industries General Bldg Contractors - Nonresidential BldgsBasic Industries Home FurnishingsBasic Industries HomebuildingBasic Industries Major ChemicalsBasic Industries Metal FabricationsBasic Industries Military/Government/TechnicalBasic Industries Mining & Quarrying of Nonmetallic Minerals (No Fuels)Basic Industries MiscellaneousBasic Industries Other Specialty Stores

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Table 1.2 – continued from previous pageentity_sector entity_industryBasic Industries Package Goods/CosmeticsBasic Industries Paints/CoatingsBasic Industries PaperBasic Industries Precious MetalsBasic Industries Specialty ChemicalsBasic Industries Steel/Iron OreBasic Industries Telecommunications EquipmentBasic Industries TextilesBasic Industries Water SupplyCapital Goods AerospaceCapital Goods Auto ManufacturingCapital Goods Auto Parts:O.E.M.Capital Goods Automotive AftermarketCapital Goods Biotechnology: Laboratory Analytical InstrumentsCapital Goods Building MaterialsCapital Goods Building ProductsCapital Goods Construction/Ag Equipment/TrucksCapital Goods Containers/PackagingCapital Goods Electrical ProductsCapital Goods Electronic ComponentsCapital Goods Engineering & ConstructionCapital Goods Fluid ControlsCapital Goods HomebuildingCapital Goods Industrial Machinery/ComponentsCapital Goods Industrial SpecialtiesCapital Goods Marine TransportationCapital Goods Medical SpecialitiesCapital Goods Metal FabricationsCapital Goods Military/Government/TechnicalCapital Goods MiscellaneousCapital Goods Ordnance And AccessoriesCapital Goods Pollution Control EquipmentCapital Goods RailroadsCapital Goods Specialty ChemicalsCapital Goods Steel/Iron OreCapital Goods Tools/HardwareCapital Goods Wholesale DistributorsConsumer Durables Automotive AftermarketConsumer Durables Building ProductsConsumer Durables Consumer Electronics/AppliancesConsumer Durables Consumer SpecialtiesConsumer Durables Containers/PackagingConsumer Durables Diversified Electronic ProductsConsumer Durables Electrical ProductsConsumer Durables Electronic ComponentsConsumer Durables Home FurnishingsConsumer Durables Industrial Machinery/ComponentsConsumer Durables Industrial SpecialtiesConsumer Durables Metal Fabrications

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Table 1.2 – continued from previous pageentity_sector entity_industryConsumer Durables Miscellaneous manufacturing industriesConsumer Durables Office Equipment/Supplies/ServicesConsumer Durables PublishingConsumer Durables Specialty ChemicalsConsumer Durables Telecommunications EquipmentConsumer Non-Durables ApparelConsumer Non-Durables Beverages (Production/Distribution)Consumer Non-Durables Consumer Electronics/AppliancesConsumer Non-Durables Consumer SpecialtiesConsumer Non-Durables Electronic ComponentsConsumer Non-Durables Environmental ServicesConsumer Non-Durables Farming/Seeds/MillingConsumer Non-Durables Food ChainsConsumer Non-Durables Food DistributorsConsumer Non-Durables HomebuildingConsumer Non-Durables Meat/Poultry/FishConsumer Non-Durables Motor VehiclesConsumer Non-Durables Package Goods/CosmeticsConsumer Non-Durables Packaged FoodsConsumer Non-Durables Plastic ProductsConsumer Non-Durables Recreational Products/ToysConsumer Non-Durables Shoe ManufacturingConsumer Non-Durables Specialty FoodsConsumer Non-Durables Telecommunications EquipmentConsumer Non-Durables TextilesConsumer Non-Durables TobaccoConsumer Services AdvertisingConsumer Services Automotive AftermarketConsumer Services BooksConsumer Services BroadcastingConsumer Services Building operatorsConsumer Services Catalog/Specialty DistributionConsumer Services Clothing/Shoe/Accessory StoresConsumer Services Consumer Electronics/Video ChainsConsumer Services Consumer SpecialtiesConsumer Services Consumer: Greeting CardsConsumer Services Department/Specialty Retail StoresConsumer Services Diversified Commercial ServicesConsumer Services Electronics DistributionConsumer Services Farming/Seeds/MillingConsumer Services Food ChainsConsumer Services Home FurnishingsConsumer Services HomebuildingConsumer Services Hotels/ResortsConsumer Services Marine TransportationConsumer Services Military/Government/TechnicalConsumer Services MiscellaneousConsumer Services Motor VehiclesConsumer Services Movies/Entertainment

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Table 1.2 – continued from previous pageentity_sector entity_industryConsumer Services Newspapers/MagazinesConsumer Services Office Equipment/Supplies/ServicesConsumer Services Other Consumer ServicesConsumer Services Other Specialty StoresConsumer Services PaperConsumer Services Professional ServicesConsumer Services PublishingConsumer Services RETAIL: Building MaterialsConsumer Services Real EstateConsumer Services Real Estate Investment TrustsConsumer Services Recreational Products/ToysConsumer Services Rental/Leasing CompaniesConsumer Services RestaurantsConsumer Services Services-Misc. Amusement & RecreationConsumer Services Telecommunications EquipmentConsumer Services Television ServicesConsumer Services Transportation ServicesEnergy Coal MiningEnergy Consumer Electronics/AppliancesEnergy Electric Utilities: CentralEnergy Industrial Machinery/ComponentsEnergy Integrated oil CompaniesEnergy Metal FabricationsEnergy Natural Gas DistributionEnergy Oil & Gas ProductionEnergy Oil Refining/MarketingEnergy Oilfield Services/EquipmentFinance Accident &Health InsuranceFinance BanksFinance Business ServicesFinance Commercial BanksFinance Diversified Commercial ServicesFinance Diversified Financial ServicesFinance Finance CompaniesFinance Finance/Investors ServicesFinance Finance: Consumer ServicesFinance Investment Bankers/Brokers/ServiceFinance Investment ManagersFinance Life InsuranceFinance Major BanksFinance Property-Casualty InsurersFinance Real EstateFinance Savings InstitutionsFinance Specialty InsurersHealth Care Biotechnology: Biological Products (No Diagnostic Substances)Health Care Biotechnology: Commercial Physical & Biological ResarchHealth Care Biotechnology: Electromedical & Electrotherapeutic ApparatusHealth Care Biotechnology: In Vitro & In Vivo Diagnostic SubstancesHealth Care Hospital/Nursing Management

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Table 1.2 – continued from previous pageentity_sector entity_industryHealth Care Industrial SpecialtiesHealth Care Major PharmaceuticalsHealth Care Medical ElectronicsHealth Care Medical SpecialitiesHealth Care Medical/Dental InstrumentsHealth Care Medical/Nursing ServicesHealth Care Ophthalmic GoodsHealth Care Other PharmaceuticalsHealth Care Precision InstrumentsMiscellaneous Business ServicesMiscellaneous Industrial Machinery/ComponentsMiscellaneous Multi-Sector CompaniesMiscellaneous Office Equipment/Supplies/ServicesMiscellaneous Other Consumer ServicesMiscellaneous PublishingPublic Utilities Electric Utilities: CentralPublic Utilities Environmental ServicesPublic Utilities Natural Gas DistributionPublic Utilities Oil & Gas ProductionPublic Utilities Oil/Gas TransmissionPublic Utilities Power GenerationPublic Utilities Telecommunications EquipmentPublic Utilities Water SupplyTechnology AdvertisingTechnology Computer Communications EquipmentTechnology Computer ManufacturingTechnology Computer Software: Prepackaged SoftwareTechnology Computer Software: Programming, Data ProcessingTechnology Computer peripheral equipmentTechnology Diversified Commercial ServicesTechnology EDP ServicesTechnology Electrical ProductsTechnology Electronic ComponentsTechnology Industrial Machinery/ComponentsTechnology Professional ServicesTechnology Radio And Television Broadcasting And Communications EquipmentTechnology Retail: Computer Software & Peripheral EquipmentTechnology SemiconductorsTechnology Telecommunications EquipmentTransportation AerospaceTransportation Air Freight/Delivery ServicesTransportation Marine TransportationTransportation Oil Refining/MarketingTransportation Other TransportationTransportation RailroadsTransportation Transportation ServicesTransportation Trucking Freight/Courier Servicesn/a n/a

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1.5.3.3 event

1.5.3.4 event_group

event_group eventDisaster AccidentGeneral Business Actions AccomplishmentReal Estate AccountCompany Financials Company Financials - AccountingEconomy Economy - AccountingCompany Financials Accounting ProceduresMergers And Acquisitions Mergers And Acquisitions - AcquisitionLaws And Regulations ActContracts Contracts - ActionLegal Actions Legal Actions - ActionCorporate Governance Corporate Governance - Action PlanGeneral Business Actions General Business Actions - Action PlanMarket Performance ActivityGeneral Business Actions AdverseProduct Development AerospaceLaws And Regulations AgencyDisaster AggressionContracts Contracts - AgreementLegal Actions AllegationGeneral Business Actions General Business Actions - AnnouncementRumors Rumors - AnnouncementCompany Financials AnnualLegal Actions AntitrustReal Estate ArrangementInsurance Auto InsuranceProduct Development AutomotiveEconomy AwardsEconomy BailoutFinancial Securities Balloon PaymentBankruptcy Bankruptcy - BankFinancing Actions Financing Actions - BankLaws And Regulations BillsCriminal Actions BlackmailFinancial Securities Financial Securities - Bond AgreementFinancial Securities Financial Securities - Bond AgreementFinancial Securities Bond ComputationFinancial Securities Bond IndividualFinancial Securities Bond MethodFinancial Securities Bond PriceFinancial Securities Bond ProcessFinancial Securities Bond ReturnFinancial Securities Bond StatusFinancial Securities Bond SystemsFinancial Securities Bond TheoryFinancial Securities Bond Type

Continued on next page

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Table 1.3 – continued from previous pageevent_group eventFinancial Securities BondsFinancial Securities BondspaymentCriminal Actions BreachCompany Financials BudgetLaws And Regulations BureauLaws And Regulations Cabinet DepartmentFinancial Securities CallCorporate Action Corporate Action - Capital ExpenditureFinancing Activities Financing Activities - Capital ExpenditureInsurance Car InsuranceFinancing Actions ChargingCorporate Governance ChronologyLaws And Regulations ClaimLaws And Regulations ClauseCollaborations Collaborations EntityBankruptcy CollateralLaws And Regulations CommiteeBankruptcy Bankruptcy - CompanyEconomy Economy - CompanyFinancing Actions Financing Actions - CompanyCorporate Governance Company ChangeCompany Financials Company EarningsCompany Financials Company Earnings DelayCompany Financials Company ExpensesInsurance Insurance - Company SecurityLaws And Regulations Laws And Regulations - Company SecurityLaws And Regulations Concurrent ResolutionLaws And Regulations CongressCriminal Actions ConspiracyEconomy Economy - ConsumerReal Estate Real Estate - ConsumerProduct Development Product Development - Consumer GoodsLaws And Regulations Contract LawLaws And Regulations Contractual ProvisionLaws And Regulations Corporate BankruptcyFinancial Securities CouponLegal Actions CourtLaws And Regulations Court OrderInsurance CoverageInsurance Coverage GapFinancing Activities CreditCriminal Actions Criminal Actions - CrimeCriminal Actions CrimesEconomy CurrencySecurity Cyber SecurityCriminal Actions CybercrimeCollaborations DealsInsurance Death RateBankruptcy Bankruptcy - Debt

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Table 1.3 – continued from previous pageevent_group eventEconomy Economy - DebtFinancial Securities Financial Securities - DebtFinancing Actions Financing Actions - DebtFinancing Activities Financing Activities - DebtFinancial Securities Debt SecutiyReal Estate DeedLaws And Regulations Default RuleBankruptcy Bankruptcy - DefaultsLaws And Regulations DegreeBusiness Concerns DelaysLaws And Regulations Department Of JusticeBusiness Concerns DepartureInsurance Deposit InsuranceLegal Actions DetentionProduct Development DevelopmentBusiness Concerns DisagreementsLaws And Regulations DisclaimerLaws And Regulations DisclosureLaws And Regulations Laws And Regulations - DisputeReal Estate Real Estate - DisputeEconomy DistributionBusiness Concerns DisturbanceMergers And Acquisitions DivestitureCollaborations Collaborations - DocumentLaws And Regulations Laws And Regulations - DocumentLegal Actions Legal Actions - DocumentReal Estate Real Estate - DocumentSecurity Domestic SecurityCompany Financials DonationAnalyst Ratings DowngradeCompany Financials Earnings ForecastEconomy EconomicEconomy Economic AnalysisEconomy Economic CycleEconomy Economic SituationEconomy Economic TheoryEconomy EconomistEconomy EducationLaws And Regulations Education FoundationEconomy ElasticityProduct Development ElectronicCorporate Governance EmployeeEconomy EmploymentEconomy Economy - EnergyProduct Development Product Development - EnergyProduct Development EntertainmentLegal Actions EntityCorporate Action Corporate Action - Environmental IssueDisaster Disaster - Environmental Issue

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Table 1.3 – continued from previous pageevent_group eventFinancial Securities Financial Securities - EquityLaws And Regulations Laws And Regulations - EquityStock Valuation Equity ValueCompany Financials ErrorsCorporate Governance EventLaws And Regulations ExamCorporate Governance ExpansionReal Estate ExpensesInsurance ExpireInsurance Extra Liability InsuranceLaws And Regulations FederalLaws And Regulations Federal AgencyLaws And Regulations Federal Communications CommissionLaws And Regulations Federal Reserve BankLaws And Regulations FiduciaryCorporate Action Corporate Action - FinanceInsurance Insurance - FinanceStock Valuation Stock Valuation - FinanceLaws And Regulations Laws And Regulations - FinancialProduct Development Product Development - FinancialCorporate Governance Financial ChangeFinancing Activities Financial InvestmentsFinancing Activities Financial RecoveryCorporate Action Financial ReportsFinancing Activities Financial RiskLegal Actions FinesGovernment Food And Drug AdministrationEconomy Economy - ForecastMergers And Acquisitions Mergers And Acquisitions - ForecastLaws And Regulations FormCriminal Actions Criminal Actions - FraudLaws And Regulations Laws And Regulations - FraudLegal Actions Legal Actions - FraudReal Estate Real Estate - FraudFinancial Securities FundCorporate Governance FundingEconomy Game TheoryEconomy Gdp MovementAnalyst Ratings Analyst Ratings - GeneralCollaborations Collaborations - GeneralCompany Financials Company Financials - GeneralCriminal Actions Criminal Actions - GeneralDisaster Disaster - GeneralEconomy Economy - GeneralEmployment Actions Employment Actions - GeneralFinancing Activities Financing Activities - GeneralLaws And Regulations Laws And Regulations - GeneralLegal Actions Legal Actions - GeneralMarket Performance Market Performance - General

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Table 1.3 – continued from previous pageevent_group eventMergers And Acquisitions Mergers And Acquisitions - GeneralProduct Development Product Development - GeneralReal Estate Real Estate - GeneralRetirement Planning Retirement Planning - GeneralRumors Rumors - GeneralStock Valuation Stock Valuation - GeneralGeneral Business Actions GoalEconomy Economy - GovernmentInsurance Insurance - GovernmentBankruptcy Bankruptcy - Government AgencyEconomy Economy - Government AgencyFinancing Actions Financing Actions - Government AgencyGovernment Government - Government AgencyEconomy Government PolicyLaws And Regulations Government SpendingEconomy GraphLaws And Regulations GuaranteeCorporate Action Headquarters-ChangeInsurance Health InsuranceLaws And Regulations Health Insurance SecurityInsurance Insurance - HealthcareLaws And Regulations Laws And Regulations - HealthcareFinancial Securities High YieldInsurance Homeowners InsuranceLaws And Regulations IdentityLaws And Regulations IllegalEconomy Illegal TradeGeneral Business Actions ImprovementEconomy IndicatiorsEconomy IndicatorsLaws And Regulations IndividualSecurity Infrastructure SecurityCorporate Governance InitiativeCorporate Action Corporate Action - Insider ActivitiesStock Activities Stock Activities - Insider ActivitiesLegal Actions Insider TradingEconomy Economy - InstitutionLegal Actions Legal Actions - InstitutionReal Estate Real Estate - InstitutionEconomy InstitutionsReal Estate InsuranceLaws And Regulations Insurance ClauseLaws And Regulations Insurance CoverageInsurance Insurance IndustryInsurance Insurance PlanProduct Development Intellectual PropertyEconomy Economy - InterestLaws And Regulations Laws And Regulations - InterestBankruptcy Bankruptcy - Interest Rate

Continued on next page

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Table 1.3 – continued from previous pageevent_group eventEconomy Economy - Interest RateFinancing Actions Financing Actions - Interest RateCorporate Governance Corporate Governance - InvestmentFinancing Activities Financing Activities - InvestmentLaws And Regulations Laws And Regulations - InvestmentReal Estate Real Estate - InvestmentRetirement Planning Retirement Planning - InvestmentEconomy InvestmentLaws And Regulations InvestorContracts IPOStock Activities IpoCompany Financials IssuesLaws And Regulations Joint ResolutionsCompany Financials Joint ReturnLaws And Regulations Judicial OrderFinancial Securities JumboEconomy Economy - LaborLaws And Regulations Laws And Regulations - LaborEconomy Economy - Labor UnionEmployment Actions Employment Actions - Labor UnionFinancial Securities LadderLaws And Regulations Laws And Regulations - LawReal Estate Real Estate - LawCorporate Governance Corporate Governance - LawsuitLegal Actions Legal Actions - LawsuitEmployment Actions Employment Actions - LayoffRumors Rumors - LayoffFinancing Actions Financing Actions - LeaseReal Estate Real Estate - LeaseReal Estate LegalLaws And Regulations Legal ActionLaws And Regulations Legal AuthorityLaws And Regulations Legal BondLaws And Regulations Legal DistinctionLaws And Regulations Legal DocumentLegal Actions Legal EthicsMergers And Acquisitions Legal ProvisionLaws And Regulations Legislative BodyLaws And Regulations LetterBankruptcy LeverageLaws And Regulations LiabilityInsurance Life InsuranceLaws And Regulations Limited Liability CompanyGeneral Business Actions LimitingCompany Financials LiquidationLegal Actions LitigationBankruptcy Bankruptcy - LoanFinancing Actions Financing Actions - LoanLaws And Regulations Laws And Regulations - Loan

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Table 1.3 – continued from previous pageevent_group eventEconomy Economy - LoansReal Estate Real Estate - LoansDisaster Man-Made DisasterEmployment Actions ManagementCorporate Governance Management DecisionsCorporate Governance Management RegulationLaws And Regulations ManagerInsurance Managing RiskReal Estate Real Estate - MarketStock Valuation Stock Valuation - MarketEconomy Market ConcetrationEconomy Market EconomicsEconomy Market IndustryCorporate Action Market-ShareProduct Development MarketingEconomy MarketsCompany Financials Marriage TaxFinancial Securities Financial Securities - MeasureReal Estate Real Estate - MeasureInsurance MedicareMergers And Acquisitions Mergers And Acquisitions - MergerBusiness Concerns MistakesEconomy ModelEconomy MonetaryEconomy Monetary PolicyEconomy Monetary SystemLaws And Regulations Monitoring SystemBankruptcy Bankruptcy - MortgageFinancing Actions Financing Actions - MortgageReal Estate Real Estate - MortgageCorporate Action Name ChangeDisaster Natural DisasterFinancial Securities NegativeFinancial Securities NetCollaborations Collaborations - Non-ProfitLaws And Regulations Laws And Regulations - Non-ProfitBankruptcy Bankruptcy - ObligationFinancial Securities Financial Securities - ObligationLaws And Regulations Laws And Regulations - ObligationLaws And Regulations OffenseFinancial Securities OptionLaws And Regulations OrderGeneral Business Actions OverloadCorporate Action Corporate Action - OwnershipLaws And Regulations Laws And Regulations - OwnershipReal Estate Real Estate - OwnershipFinancial Securities Par ValueContracts Contracts - PartnershipCorporate Action Corporate Action - Partnership

Continued on next page

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Table 1.3 – continued from previous pageevent_group eventBankruptcy Bankruptcy - PaymentCorporate Governance Corporate Governance - PaymentFinancing Actions Financing Actions - PaymentReal Estate Real Estate - PaymentRumors Rumors - PaymentFinancing Activities PaymentsLegal Actions PenaltyProduct Development PharmaceuticalsCriminal Actions PlagiarismLaws And Regulations PledgeBankruptcy Bankruptcy - PolicyEconomy Economy - PolicyFinancing Actions Financing Actions - PolicyLaws And Regulations Laws And Regulations - PolicyCorporate Governance Portfolio ManagementCorporate Governance PositionContracts Pre-ContractInsurance PremiumCorporate Action Corporate Action - PriceEconomy Economy - PriceStock Valuation PricingInsurance Printed DocumentReal Estate ProcessesCorporate Action ProductRumors Product DevelopmentProduct Development Product DiscontinuationProduct Development Product ImprovementProduct Development Product Development - Product LaunchRumors Rumors - Product LaunchProduct Development Product RecallReal Estate ProgramLaws And Regulations Laws And Regulations - PropertyReal Estate Real Estate - PropertyInsurance Property InsuranceLaws And Regulations Proposed LegislationLaws And Regulations ProspectusLaws And Regulations Public HolidayCorporate Governance Public IssuesGeneral Business Actions Public RelationsCompany Financials Qualified IndividualsFinancial Securities RatingEconomy RatioEconomy Real EstateEconomy RecessionLaws And Regulations Laws And Regulations - RecordReal Estate Real Estate - RecordEmployment Actions RecruitmentCompany Financials Company Financials - RegulationLaws And Regulations Laws And Regulations - Regulation

Continued on next page

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Table 1.3 – continued from previous pageevent_group eventLaws And Regulations Regulation ProcedureLegal Actions RegulationsProduct Development RegulatoryInsurance Reimbursement PlanLaws And Regulations RelationshipReal Estate RentCorporate Governance ReorganizationEconomy ReportReal Estate ReposessionLaws And Regulations RepresentativeProduct Development Research And DevelopmentEmployment Actions ResignationCorporate Governance ResolutionEconomy Retail EstablishmentEconomy Economy - RetirementInsurance Insurance - RetirementRetirement Planning Retirement SecurityLaws And Regulations Laws And Regulations - RightReal Estate Real Estate - RightInsurance Insurance - RiskStock Valuation Stock Valuation - RiskInsurance Risk ManagementLaws And Regulations RuleCorporate Governance RulesReal Estate SaleLaws And Regulations Sale Of SecuritiesEconomy Sales AmountBankruptcy Bankruptcy - SecuritiesCorporate Governance Corporate Governance - SecuritiesLaws And Regulations SecurityRumors Sell OffLegal Actions SettlementLaws And Regulations ShareCorporate Governance ShareholdersStock Valuation SharesReal Estate ShortContracts SigningLaws And Regulations Simple ResolutionReal Estate SituationFinancing Activities Spin OffLaws And Regulations StandardLaws And Regulations State LawLaws And Regulations StatuteMarket Performance Stock ActivitiesMarket Performance Stock ActivityStock Activities Stock DelistingEconomy Stock IndexCorporate Action Corporate Action - Stock MarketEconomy Economy - Stock Market

Continued on next page

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Table 1.3 – continued from previous pageevent_group eventStock Activities Stock SplitCorporate Governance StocksCorporate Governance StoreLaws And Regulations StrategyProduct Development SuppliesCorporate Action SupplyEconomy SurveyLaws And Regulations Laws And Regulations - TakeoverMergers And Acquisitions Mergers And Acquisitions - TakeoverCompany Financials Company Financials - TaxEconomy Economy - TaxFinancial Securities Financial Securities - TaxLaws And Regulations Laws And Regulations - TaxCompany Financials Tax AccountingCompany Financials Tax AllowanceCompany Financials Tax Business Income/RevenueCompany Financials Tax Collection MethodCompany Financials Tax Company/BusinessCompany Financials Tax Consumption TaxCompany Financials Tax Credit TypeCompany Financials Tax DeductionCompany Financials Tax DefinitionCompany Financials Tax ExpenseCompany Financials Tax FormsCompany Financials Tax Government/BusinessCompany Financials Tax Government/PersonalCompany Financials Tax GrossCompany Financials Tax IdentifierCompany Financials Tax IncomeCompany Financials Tax Income TypeCompany Financials Company Financials - Tax IndividualCompany Financials Tax InvestmentCompany Financials Tax LawCompany Financials Tax Law/CountryCompany Financials Tax Law/DefinitionCompany Financials Tax Law/IrsCompany Financials Tax LossCompany Financials Tax MethodCompany Financials Tax Method/DefinitionCompany Financials Tax MortgageCompany Financials Tax NetCompany Financials Tax PersonalCompany Financials Tax PolicyCompany Financials Tax ProcessCompany Financials Tax PropertyCompany Financials Tax Property LawCompany Financials Tax Refund/ReturnsCompany Financials Tax RequirementCompany Financials Tax Returns

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Table 1.3 – continued from previous pageevent_group eventCompany Financials Tax SaleCompany Financials Tax SeasonCompany Financials Tax TypeCompany Financials Tax ValueCorporate Action TaxesCompany Financials TaxpayerProduct Development TechBusiness Concerns TerminationLaws And Regulations Terms And ConditionsEconomy TheoryLaws And Regulations TimeLaws And Regulations ToolEconomy TradeLaws And Regulations TradingBusiness Concerns TragedyReal Estate TransactionFinancial Securities TreasuryEconomy TrendReal Estate TypeInsurance Type Of InsuranceBusiness Concerns UncertaintyAnalyst Ratings UpgradeCompany Financials Company Financials - ValueReal Estate Real Estate - ValueCollaborations ValuesCriminal Actions ViolationEmployment Actions Employment Actions - WageFinancial Securities Financial Securities - Yield

1.5.3.5 story_type

blogfeednewssec_filing

1.5. Appendix 33