df = market.fetch_market(md_request)
print(df)
# We can also download G10 FX from Eikon using shortcuts, without
# specifying RIC
# we just need to specify category at 'fx'
# You can add your own customized tickers by editing the various conf
# CSV files
md_request = MarketDataRequest(
start_date=datetime.datetime.utcnow() - timedelta(days=5),
# Start date (download data over past decade)
freq='intraday',
category='fx',
cut='NYC',
data_source='eikon', # use Eikon as data source
tickers=['EURUSD', 'GBPUSD'], # ticker
fields=['close', 'open', 'high', 'low'], # which fields to download
eikon_api_key=eikon_api_key)
print(df)
df = market.fetch_market(md_request)
# Also let's do this for daily data
md_request.freq = 'daily'
df = market.fetch_market(md_request)
print(df)
tickers=['GBPUSD'],
cache_algo='cache_algo_return',
abstract_curve=FXSpotCurve(
construct_via_currency='USD',
depo_tenor='ON'))
df_tot = market.fetch_market(md_request=md_request)
df_tot.columns = [x + '-tot-cuemacro' for x in df_tot.columns]
df_tot = df_tot.tz_localize(pytz.utc)
df_tot.index = df_tot.index + pd.Timedelta(
hours=22) # Roughly NY close 2200 GMT
md_request.abstract_curve = None
# Get intraday spot data
md_request.freq = 'tick'
md_request.data_source = 'dukascopy'
df_intraday_spot = market.fetch_market(md_request=md_request)
df_intraday_spot = pd.DataFrame(
df_intraday_spot.resample('1min').last().dropna())
# Get Bloomberg calculated total return indices (for spot)
md_request.category = 'fx-tot'
md_request.freq = 'daily'
md_request.data_source = 'bloomberg'
df_bbg_tot = market.fetch_market(md_request)
df_bbg_tot.columns = [x + '-bbg' for x in df_bbg_tot.columns]
df_bbg_tot = df_bbg_tot.tz_localize(pytz.utc)
df_bbg_tot.index = df_bbg_tot.index + pd.Timedelta(
