Yves Hilpisch yhilpisch

## big_tstables.py
#
# TsTables -- High Frequency Times Series Data with PyTables
#
# to install -- pip install tstables
# Github repo -- https://github.com/afiedler/tstables
#
# Dr. Yves J. Hilpisch
#
# The Python Quants GmbH
# http://quant-platform.com

## client.py
import zmq

context = zmq.Context()
socket = context.socket(zmq.SUB)
socket.connect('tcp://0.0.0.0:8888')
socket.setsockopt_string(zmq.SUBSCRIBE, u'value')

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

## jupyter_notebook_config.py
c.NotebookApp.certfile='/cert.pem'
c.NotebookApp.keyfile='/cert.key'
c.NotebookApp.password='sha1:768ce7b87bf6:fa6013a02f7053bc014ef7c65be0ef34f77f21fd'

c.NotebookApp.ip='*'
c.NotebookApp.port=8888

c.NotebookApp.open_browser=False

## ScikitBacktest.py
#
# Backtesting Algo Strategies based on
# Logistic Regression with scikit-learn
#
# Yves Hilpisch
# ODSC London 2016
# The Python Quants GmbH
#

import numpy as np

## StrategyOptimizer.py
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns; sns.set()
from pandas_datareader import data as web

class StrategyOptimizer(object):
    def __init__(self, symbol, start, end, t1, t2):
        self.symbol = symbol
        self.start = start

## ScikitBacktester01.py
#
# Python for Algorithmic Trading
# Quant Insights Bootcamp
#
# The Python Quants
#
import numpy as np
import pandas as pd
import seaborn as sns; sns.set()
from pandas_datareader import data as web

## Titanic.csv

          
            
            Class
            Sex
            Age
            Survived
            Freq

            
              1
              1st
              Male
              Child
              No
              0

            
              2
              2nd
              Male
              Child
              No
              0

            
              3
              3rd
              Male
              Child
              No
              35

            
              4
              Crew
              Male
              Child
              No
              0

            
              5
              1st
              Female
              Child
              No
              0

            
              6
              2nd
              Female
              Child
              No
              0

            
              7
              3rd
              Female
              Child
              No
              17

            
              8
              Crew
              Female
              Child
              No
              0

            
              9
              1st
              Male
              Adult
              No
              118

## admin.txt

Welcome to the Algo Trading Bootcamp
====================================

WIFI
====
Ft1ch#2016#!

Quant Platform
==============

## RegPred.py
#
# Stock Market Prediction
# with Linear Regression
#
# The Python Quants GmbH
#
import numpy as np
import pandas as pd
from pandas_datareader import data as web
import seaborn as sns

## 00_overview.md

      
        
          
            
              
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                yhilpisch
                / 00_overview.md
            
            
              Last active
              September 19, 2018 18:51
            
              
                Code from Plotcon, 04. May 2017, Oakland
              
          
        
      
        
  
      
    Streaming Financial Data & Plots with Ploty

This Gist hosts the code from my talk and brief coding session at Plotcon.

tick data server with ZeroMQ
tick data client with ZeroMQ
tick data plotting with plotly
Flask app embedding the streaming plot
	#
	# TsTables -- High Frequency Times Series Data with PyTables
	#
	# to install -- pip install tstables
	# Github repo -- https://github.com/afiedler/tstables
	#
	# Dr. Yves J. Hilpisch
	#
	# The Python Quants GmbH
	# http://quant-platform.com
	import zmq

	context = zmq.Context()
	socket = context.socket(zmq.SUB)
	socket.connect('tcp://0.0.0.0:8888')
	socket.setsockopt_string(zmq.SUBSCRIBE, u'value')

	while True:
	data = socket.recv_string()
	print(data)
	c.NotebookApp.certfile='/cert.pem'
	c.NotebookApp.keyfile='/cert.key'
	c.NotebookApp.password='sha1:768ce7b87bf6:fa6013a02f7053bc014ef7c65be0ef34f77f21fd'

	c.NotebookApp.ip='*'
	c.NotebookApp.port=8888

	c.NotebookApp.open_browser=False
	#
	# Backtesting Algo Strategies based on
	# Logistic Regression with scikit-learn
	#
	# Yves Hilpisch
	# ODSC London 2016
	# The Python Quants GmbH
	#

	import numpy as np
	import numpy as np
	import pandas as pd
	import matplotlib.pyplot as plt
	import seaborn as sns; sns.set()
	from pandas_datareader import data as web

	class StrategyOptimizer(object):
	def __init__(self, symbol, start, end, t1, t2):
	self.symbol = symbol
	self.start = start
	#
	# Python for Algorithmic Trading
	# Quant Insights Bootcamp
	#
	# The Python Quants
	#
	import numpy as np
	import pandas as pd
	import seaborn as sns; sns.set()
	from pandas_datareader import data as web
	Class	Sex	Age	Survived	Freq
1	1st	Male	Child	No	0
2	2nd	Male	Child	No	0
3	3rd	Male	Child	No	35
4	Crew	Male	Child	No	0
5	1st	Female	Child	No	0
6	2nd	Female	Child	No	0
7	3rd	Female	Child	No	17
8	Crew	Female	Child	No	0
9	1st	Male	Adult	No	118

	Welcome to the Algo Trading Bootcamp
	====================================

	WIFI
	====
	Ft1ch#2016#!

	Quant Platform
	==============
	#
	# Stock Market Prediction
	# with Linear Regression
	#
	# The Python Quants GmbH
	#
	import numpy as np
	import pandas as pd
	from pandas_datareader import data as web
	import seaborn as sns