FX Trading with FXCM

Install the Python wrapper package

pip install fxcmpy

Open a FAXM Demo Account

Create a unique API token

Connect to the API

import fxcmpy
api = fxcmpy.fxcmpy(access_token=YOUR_FXCM_API_TOKEN, log_level='error')

The configuration file

[FXCM]
log_level = error
log_file = PATH_TO_AND_NAME_OF_LOG_FILE
access_token = YOUR_FXCM_API_TOKEN

import fxcmpy
api = fxcmpy.fxcmpy(config_file='pyalgo.cfg')

api = fxcmpy.fxcmpy(config_file='pyalgo.cfg', server='demo')
api = fxcmpy.fxcmpy(config_file='pyalgo.cfg', server='real')

Retrieving data

Retrieving tick data

import time
import numpy as np
import pandas as pd
import datetime as dt
from pylab import mpl, plt

plt.style.use('seaborn')
mpl.rcParams['savefig.dpi'] = 300
mpl.rcParams['font.family'] = 'serif'

The available symbols

from fxcmpy import fxcmpy_tick_data_reader as tdr

print(tdr.get_available_symbols())

Retrieves one week’s worth of tick data for a single symbol

start = dt.datetime(2020, 3, 25)
stop = dt.datetime(2020, 3, 30)

td = tdr('EURUSD', start, stop)

td.get_raw_data().info()

td.get_data().info()

td.get_data().head()

Pick a subset of the data and implement typical financial analytics tasks

sub = td.get_data(start='2020-03-25 12:00:00', end='2020-03-25 12:15:00')

sub.head()

sub['Mid'] = sub.mean(axis=1)

sub['SMA'] = sub['Mid'].rolling(1000).mean()

sub[['Mid', 'SMA']].plot(figsize=(10, 6), lw=1.5)

Retrieving candles data

Candles data is data for certain homogeneous time intervals (“bar”) with open, high, low, and close values for both bid and ask prices.

from fxcmpy import fxcmpy_condles_data_reader as cdr

print(cdr.get_available_symbols())

start = dt.datetime(2020, 4, 1)
stop = dt.datetime(2020, 5, 1)

period = 'H1'

candles = cdr('EURUSD', start, stop, period)

data = candles.get_data()

data.info()

data[data.columns[:4]].tail()

data[data.columns[4:]].tail()

data['MidClose'] = data[['BidClose', 'AskClose']].mean(axis=1)

data['SMA1'] = data['Midclose'].rolling(30).mean()
data['SMA2'] = data['Midclose'].rolling(100).mean()

data[['MidClose', 'SMA1', 'SMA2']].plot(figsize=(10, 6))

Working with the API

import fxcmpy

fxcmpy.__version__

api = fxcmpy.fxcmpy(config_file='../pyalgo.cfg')

instruments = api.get_instruments()

Retrieving historical data

candles = api.get_candles('USD/JPY', period='D1', number=10)

candles[candles.columns[:4]]

candles[candles.column[4:]]

start = dt.datetime(2019, 1, 1)
end = dt.datetime(2020, 6, 1)

candles = api.get_candles('EUR/GBP', period='D1', start=start, stop=end)

candles.info()

candles = api.get_candles('EUR/USD', period='m1', number=250)

candles['askclose'].plot(figsize=(10, 6)

Retrieving streaming data

def output(data, dataframe):
    print('%3d | %s | %s | %6.5f, %6m5f' %(len(dataframe), data['Symbol'], pd.to_datetime(int(date['Updated']), unit='ms'), data['Rates'][0], data['Rates'][1]))

api.subscribe_market_data('EUR/USD', (output,))

api.get_last_price('EUR/USD')

api.unsubscribe_market_data('EUR/USD')

Placing orders

Verifies that there are no open positions and then opens different positions via the .create_makret_buy_order() method:

api.get_open_positions()

order = api.create_market_buy_order('EUR/USD', 100)

sel = ['tradeId', 'amountK', 'currency', 'grossPL', 'isBuy']

api.get_open_positions()[sel]

order = api.create_market_buy_order('EUR/GBP', 50)

api.get_open_positions()[sel]

order = api.create_market_sell_order('EUR/USD', 25)

order = api.create_market_buy_order('EUR/GBP', 50)

api.get_open_positions()[sel]

api.close_all_for_symbol('EUR/GBP')

api.get_open_positions()[sel]

api.close_all()

api.get_open_positions()

Account information

api.get_default_account()

api.get_accounts().T