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(