I'm trying to download Price close of MSCI europe index and MSCI quality index

damiano.amendola

I cannot post the screenshot. There are missing data from 2002 in MSCI Europe Index(.dMIEU00000PUS) but I checked and there are prices from 2001. Moreover, I downloaded and I saw that the price is fixed at 1317 in 2002,why?

jason.ramchandani01

@damiano.amendola the reason you are seeing this is that there is an API call limit of 3000 interday rows for the Timeseries API. When the API hits this limit it silently fails and returns a max of 3000 most recent rows. So you can get around this limitation using iteration with the following code i wrote:

from dateutil import parser
from datetime import timedelta
from datetime import datetime
import math
import time

def date_range(start, end, intv):
    start = datetime.strptime(start,"%Y-%m-%d")
    end = datetime.strptime(end,"%Y-%m-%d")
    diff = (end  - start ) / intv
    for i in range(intv):
        yield (start + diff * i).strftime("%Y-%m-%d")
    yield end.strftime("%Y-%m-%d")

def get_daily(rics,fields,start,end):
    for ric in rics:        
        interval = math.ceil((parser.parse(end) - parser.parse(start)).days / 3000)
        l = list(date_range(start,end,interval))
        df1 = pd.DataFrame()
        df = pd.DataFrame()
        for i in range(interval):
            ts = ek.get_timeseries(rics=ric,fields=fields, start_date=l[0+i],end_date=l[1+i], interval='daily')
            df = df.append(ts)
            time.sleep(0.4)


    return df

So now we have our function defined we can simply call it with your RIC:

rics = ['.dMIEU00000PUS'] # Just for one ric at the moment I will extend this for multi-ric
fields = ['OPEN', 'HIGH', 'LOW', 'CLOSE']
start = '1999-01-02'
end = '2018-06-04'
df = get_daily(rics,fields,start,end)
df

I hope this can help.