00_pff_bootcamp.md

Python for Finance Online Bootcamp

3-Day Bootcamp about Python, NumPy & pandas for Finance

Dr. Yves J. Hilpisch

CEO The Python Quants | The AI Machine

Online, May 2023

Short Link

http://bit.ly/pffbc_may_2023

GotoWebinar

https://attendee.gotowebinar.com/register/1260449774563154009

Quant Platform

https://bootcamp.pqp.io (registration)
https://base.pqp.io (login)

Slides

https://certificate.tpq.io/pffbc.pdf

Discord Server

https://discord.gg/eanaY3vfKp

Miniconda Installer

https://conda.io/en/main/miniconda.html

Docker

To install Docker see https://docs.docker.com/install/.

To run a Ubuntu-based Docker container, execute on the shell (Linux/Mac) the following:

docker run -ti -p 9999:9999 -h pffbc -v $(pwd):/root/live ubuntu:latest /bin/bash

Make sure to adjust the folder to be mounted accordingly.

Once, JupyterLab is installed, run it with the following command:

jupyter lab --allow-root --port 9999 --ip 0.0.0.0

Cloud

Use this link to get a 200 USD bonus on DigitalOcean when signing up for a new account.

Further Resources

• https://tpq.io
• https://hilpisch.com
• https://books.tpq.io
• https://youtube.com/@dyjh
• https://twitter.com/dyjh

01_pff_bootcamp.ipynb

02_pff_bootcamp.ipynb

03_pff_bootcamp.ipynb

04_pff_bootcamp.ipynb

05_pff_bootcamp.ipynb

06_pff_bootcamp.ipynb

tick_client.py

#
# Simple Tick Data Client
#
import zmq

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

while True:
    msg = socket.recv_string()
    print(msg)

tick_collector.py

#
# Simple Tick Data Collector
#
import zmq

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

raw = list()
while True:
    msg = socket.recv_string()
    print(msg)
    symbol, price = msg.split()
    raw.append((symbol, float(price)))

tick_dataframe.py

#
# Simple Tick Data Collector
# (using pandas DataFrame objects)
#
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, '')

data = pd.DataFrame()
while True:
    msg = socket.recv_string()
    t = datetime.datetime.now()
    print(msg)
    symbol, price = msg.split()
    df = pd.DataFrame({'symbol': symbol, 'price': float(price)}, index=[t])
    data = pd.concat((data, df))

tick_server.py

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

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

AAPL = 100.
MSFT = 100.

while True:
    if random.random() > 0.45:
        AAPL += random.gauss(0, 1) / 2
        msg = f'AAPL {AAPL:.3f}'
    else:
        MSFT += random.gauss(0, 1) / 2
        msg = f'MSFT {MSFT:.3f}'
    socket.send_string(msg)
    print(msg)
    time.sleep(random.random() * 2)