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Get historical expiry dates for futures

using the eikon api with python, i'd like to retrieve the expiry date of expired future contracts. Let me explain: ek.get_data(instruments='Wc1',fields='EXPIR_DATE') successfully gives me the current expiry date of Wc1. This is already great, but I also want to know the expiry date of Wc1 on any given date in the past. Example: the expiry date of Wc1 at 1-aug-2020 was 14-sep-2020. How/where can I input a date or date range in order to get expiry dates?

NB: the related posts on this topic did not help me.

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They told me it's not possible. In the end I looked up all the rules for each seperate future (which months and which day in the month it rolls over), then wrote a python script to calculate all the expiry dates from 1980 until 2030 for each given future.

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hey @valstar - are you willing to share your script? that would be plain awesome. thanks!


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You may need to contact the content support team via MyRefinitiv to get a chain RIC (prefixed with 0#) which can provide future RICs for Wc1. Then, you can use that chain RIC to get expiration dates. You can refer to this thread for the code.

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@Andreas Sure. but I dont have time to explain it so you'll have to dig through it yourself ;)
Please note that the mappings.future_map table contains the future_codes (eikon RICS) and contracts_available (an int which tells python how much deliveries a future has ahead. If you dont know it, just set it to 12; this gives you 12 periods ahead).

Python script:

# purpose: we want daily currency rates

import logging as logger

from datetime import datetime, timedelta

import time

import eikon as ek

from sqlalchemy import create_engine

import os

import sys

sys.path.insert(1, os.path.join(sys.path[0], '..'))

from sales_report_library import *

import warnings

warnings.simplefilter(action='ignore', category=FutureWarning) #https://stackoverflow.com/questions/40659212/futurewarning-elementwise-comparison-failed-returning-scalar-but-in-the-futur


query = "select distinct future_code,contracts_available from mappings.future_map where retrieve = 'dev';"

given_start_date_str = '1988-01-01' #ran from 1988-01-01

given_end_date_str = '2020-09-20' #max yesterday.

steps = 40 #steps*futures*contracts (40*5*13). must be smaller than 3000, because max records = 3000.



scrape_date = datetime.today()

initialize_logger(logging_directory='log', console_level='INFO')


data_source = 'futures'

params = config(filename='../specific.ini', section='postgresql') # some settings

engine = create_engine(f"postgresql+psycopg2://{params['user']}:{params['password']}@{params['host']}:{params['port']}/{params['database']}") # engine to write to DB

given_start_date = datetime.strptime(given_start_date_str, '%Y-%m-%d')

given_end_date = datetime.strptime(given_end_date_str, '%Y-%m-%d')

all_contracts = list()

#connect to eikon with the app key

params = config(filename='..\generic.ini', section='eikon_api')




logger.error('Could not connect to eikon. probably logged out.')


#get meta data

logger.info('Get meta data from DB')

df_meta = sql_to_df(query)

future_codes = list(set(df_meta['future_code']))

#step 1) create a list with ALL the contracts we want. so all contracts of all futures.

logger.info('Loop over future codes')

for future_code in future_codes:

logger.info(f'Iteration future_code={future_code}')

df_meta_temp = df_meta.loc[df_meta['future_code'] == future_code]

df_meta_temp.reset_index(drop=True, inplace=True) # reset row index

contracts_available = df_meta_temp.loc[0, 'contracts_available']

contracts = [f'{future_code}c{i}' for i in range(1, contracts_available + 1)] #Wc1, Wc2 etc.

all_contracts = all_contracts + contracts

#end for loop

logger.info(f'Now going to retrieve all {len(all_contracts)} contracts for the {len(future_codes)} futures.')

start_date = given_start_date

end_date = given_end_date

while start_date <= given_end_date:

end_date = start_date + timedelta(days=steps)

if end_date > given_end_date: #if we are too far already

end_date = given_end_date

start_date_str = start_date.strftime('%Y-%m-%d')

end_date_str = end_date.strftime('%Y-%m-%d')

# make the api call for these dates. get timeseries from eikon. this returns the dates in the rows (from start to end date) and all the contracts in the columns. The values are the CLOSE values.

logger.info(f'############################ Retrieving rates from {start_date_str} to {end_date_str}...')


df = ek.get_timeseries(all_contracts, start_date=start_date_str, end_date=end_date_str, interval="daily", fields="CLOSE")


print('crasht. sleep 60 sec and try this iteration again')



continue #goes back to the while loop. start_date hasnt changed so we are doing exactly the same iteration

#clean the data

logger.info('Made the api call. Now clean it.')

df.insert(loc=0, column='future_date', value=df.index) #take the dates from the rownames and put them in a new column

df_cleaned = pd.melt(df, id_vars='future_date', var_name='contract') #unpivot the data

df_cleaned = df_cleaned.loc[(df_cleaned['value'] != '') & (pd.notnull(df_cleaned['value'])) & (~pd.isna(df_cleaned['value']))] #remove rows where field 'value' is empty

#insert to database

logger.info(f'Start inserting into postgres. {len(df_cleaned.index)} rows...')

df_cleaned.to_sql(schema='stage', name='futures', con=engine, if_exists='append', index=False, chunksize=10000) # appends the dataframe to the specified sql table.

logger.info(f'Finished inserting into postgres')

start_date = end_date + timedelta(days=1) #in the next iteration the start the day after we just finished.


time.sleep(30) # as not to overload eikon.

#end while loop

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