00_epat_august_2017.md

Executive Program in Algorithmic Trading (QuantInsti)

Python Sessions by Dr. Yves J. Hilpisch | The Python Quants GmbH

Online, 26. & 27. August 2017

Resources

• http://tpq.io
• http://hilpisch.com
• http://twitter.com/dyjh

Slides

You find the introduction slides under http://hilpisch.com/epat.pdf

Python

We are using Python 3.6. Download and install Miniconda 3.6 from https://conda.io/miniconda.html

If you have either Miniconda or Anaconda already installed, there is no need to install anything new. You should then execute the following lines on the shell/command prompt:

conda create -n epat python=3.6
(source) activate epat
conda install numpy pandas=0.19 scikit-learn matplotlib
conda install pandas-datareader pytables
conda install ipython jupyter
jupyter notebook

Management of environments: https://conda.io/docs/using/envs.html

Cloud

Use this link to get a 10 USD bonus on DigitalOcean when signing up for a new account.

Books

Good book about everything import in Python data analysis: Python Data Science Handbook, O'Reilly

Good book covering object-oriented programming in Python: Fluent Python, O'Reilly

01_vecback_oop.ipynb

02_event_based_backtesting.ipynb

tick_client.py

#
# Simple Tick Client with ZeroMQ
#
import zmq
import datetime

context = zmq.Context()
socket = context.socket(zmq.SUB)
socket.connect('tcp://127.0.0.1:5555')

socket.setsockopt_string(zmq.SUBSCRIBE, 'AAPL')

while True:
    msg = socket.recv_string()
    t = datetime.datetime.now()
    print('%s | ' % str(t), msg)

tick_collector.py

#
# Simple Tick Collector with ZeroMQ
#
import zmq
import datetime
import pandas as pd

context = zmq.Context()
socket = context.socket(zmq.SUB)
socket.connect('tcp://127.0.0.1:5555')

socket.setsockopt_string(zmq.SUBSCRIBE, 'AAPL')

data = pd.DataFrame()

ticks = 0

while ticks < 100:
    ticks += 1
    msg = socket.recv_string()
    t = datetime.datetime.now()
    print('%s | ' % str(t), msg)
    sym, value = msg.split()
    data = data.append(pd.DataFrame({sym: float(value)}, index=[t]))
    if ticks % 10 == 0:
        h5 = pd.HDFStore('data.h5', 'w')
        h5['data'] = data
        h5.close()

tick_server.py

#
# Simple Tick Data Server with ZeroMQ
#
import zmq
import time
import random

context = zmq.Context()
socket = context.socket(zmq.PUB)
socket.bind('tcp://127.0.0.1:5555')

AAPL = 100.

while True:
    AAPL += random.gauss(0, 1) * 0.5
    msg = 'AAPL %.4f' % AAPL
    socket.send_string(msg)
    print(msg)
    time.sleep(random.random() * 2)

tick_trader.py

#
# Simple Tick Trader with ZeroMQ
#
import zmq
import datetime
import pandas as pd

context = zmq.Context()
socket = context.socket(zmq.SUB)
socket.connect('tcp://127.0.0.1:5555')

socket.setsockopt_string(zmq.SUBSCRIBE, 'AAPL')

data = pd.DataFrame()

ticks = 0
position = 0

while ticks < 200:
    ticks += 1
    msg = socket.recv_string()
    t = datetime.datetime.now()
    sym, value = msg.split()
    data = data.append(pd.DataFrame({sym: float(value)}, index=[t]))

    resam = data.resample('2s', label='right').last()
    resam['SMA1'] = resam['AAPL'].rolling(5).mean()
    resam['SMA2'] = resam['AAPL'].rolling(10).mean()
    resam.dropna(inplace=True)

    if len(resam) > 2:
        print('%3d | %s | ' % (ticks, str(t)), msg, '| %.3f | %.3f' %
                (resam['SMA1'].iloc[-2], resam['SMA2'].iloc[-2]))
        if position == 0 and resam['SMA1'].iloc[-2] > resam['SMA2'].iloc[-2]:
            print('going long the market')
            position = 1
            #
            # place trading code here (for buy order)
            #
        elif position == 1 and resam['SMA1'].iloc[-2] < resam['SMA2'].iloc[-2]:
            print('going market neutral')
            position = 0
            #
            # place trading code here (for sell order)
            #

    #if ticks % 10 == 0:
    #    h5 = pd.HDFStore('data.h5', 'w')
    #    h5['data'] = data
    #    h5.close()

tick_trader_ls.py

#
# Simple Tick Trader LS with ZeroMQ
#
import zmq
import datetime
import pandas as pd

context = zmq.Context()
socket = context.socket(zmq.SUB)
socket.connect('tcp://127.0.0.1:5555')

socket.setsockopt_string(zmq.SUBSCRIBE, 'AAPL')

data = pd.DataFrame()

ticks = 0
position = 0

while ticks < 200:
    ticks += 1
    msg = socket.recv_string()
    t = datetime.datetime.now()
    sym, value = msg.split()
    data = data.append(pd.DataFrame({sym: float(value)}, index=[t]))

    resam = data.resample('2s', label='right').last()
    resam['SMA1'] = resam['AAPL'].rolling(5).mean()
    resam['SMA2'] = resam['AAPL'].rolling(10).mean()
    resam.dropna(inplace=True)

    if len(resam) > 2:
        print('%3d | %s | ' % (ticks, str(t)), msg, '| %.3f | %.3f' %
                (resam['SMA1'].iloc[-2], resam['SMA2'].iloc[-2]))
        if position in [0, -1] and resam['SMA1'].iloc[-2] > resam['SMA2'].iloc[-2]:
            print('going long the market')
            position = 1
            #
            # place trading code here (for buy order)
            #
        elif position in [0, 1] and resam['SMA1'].iloc[-2] < resam['SMA2'].iloc[-2]:
            print('going short the market')
            position = -1
            #
            # place trading code here (for sell order)
            #