New course!! Building Python algo trading system with Bitcoin an crypto currency focus

(Last Updated On: August 1, 2018)

See below for video detail presentation

Python 3 Infrastructure Blocks with Crypto
As Bitcoin ruled the financial news cycle in recent times, many have had a peak interest in crypto currency along with systematic trading. There are many advanced trading research techniques including machine learning, AI, or quant. This course was created for the ‘newbie’ who has a basic understanding in popular programming languages but easy to learn such as Python. A focus of technical analysis was chosen since it is popular among retail traders. It is also seems to offer more predictable results as opposed to harder to learn concepts such as quant or machine learning. In essence, a simpler with more effective techniques were purposely chosen to get someone with basic programming knowledge (eg. Python) to get ramped up faster!
Price: $497.00

Here is the older and more affordable Python 2.7 version with the Crypto features

Python Trading Infrastructure Building Blocks Single
Python C++ Trading Infrastructure Building Blocks Topic units include: Unit 1 Popular Programming Language Overview for Algos and Automated Trading Unit 2 Why Python for my algos and automated trading Unit 3 Setting up your Python environment Unit 4 Why Python Introductory Programming Resources and Environment video and material Unit 5 Intro overview of MongoDB open source NOSQL database Unit 6 OPTIONAL Intro to Redis for highest performance in your algo trading Unit 7 Interfacing with Interactive Brokers TWS with Python and other demos Unit 8 Market Data Source with Yahoo Finance Unit 9 Pretty trading charts with Matplotlib and PyQtChart Unit 10 GUI Front End Customization with Qt Designer
Price: $247.00

COURSE NAME – Cryptography with Python: a practical tutorial for Python developers

Sub-title – Discover the secrets behind infrastructure components, cryptocurrency and use techniques in your Python code.

 

Short Sub-Title – Use Python v3 Infrastructure Algo Trading course with Crypto Currency such as Bitcoin

Python 3 Infrastructure Blocks with Crypto
As Bitcoin ruled the financial news cycle in recent times, many have had a peak interest in crypto currency along with systematic trading. There are many advanced trading research techniques including machine learning, AI, or quant. This course was created for the ‘newbie’ who has a basic understanding in popular programming languages but easy to learn such as Python. A focus of technical analysis was chosen since it is popular among retail traders. It is also seems to offer more predictable results as opposed to harder to learn concepts such as quant or machine learning. In essence, a simpler with more effective techniques were purposely chosen to get someone with basic programming knowledge (eg. Python) to get ramped up faster!
Price: $497.00

AUTHOR NAME – Bryan Downing

DURATION -3+ hours

OVERVIEW – As Bitcoin ruled the financial news cycle in recent times, many have had a peak interest in crypto currency along with systematic trading. There are many advanced trading research techniques including machine learning, AI, or quant.

This course was created for the ‘newbie’ who has a basic understanding in popular programming languages but easy to learn such as Python. A focus of technical analysis was chosen since it is popular among retail traders. It is also seems to offer more predictable results as opposed to harder to learn concepts such as quant or machine learning. In essence, a simpler with more effective techniques were purposely chosen to get someone with basic programming knowledge (eg. Python) to get ramped up faster!

It is very hopeful any student will become more confident in their capabilities to complete this without the unnecessary complexities that usually hold back their success.

 

TARGET AUDIENCE – Python programmers,data scientists who want to understand algo techniques and implement into a primitive automated trading system. This course is also geared for Pro or Retail traders who have an interest in learning the basics of Python and systematic trading.

 

KEY FEATURES

  • Infrastructure modern component implementation of an algo/automated/system trading system
  • Basic coverage of crypto currency Python packages and crypto currency exchanges
  • Technical analysis library package use for strategy idea development

 

APPROACH –

Videos and sample Python source code scripts are made available at time of presentation. Note that scripts are meant to to be small and simple for easiest consumption. Advanced techniques are stripped out to ensure completion of this course. This can be used as a launching to pad to understand the components of a primitive algo trading system In short, it is devised in a way to get you up and running as quickly as possible.

WHAT WILL YOU LEARN

 

  • Introduce you to programming  journey of various languages you will come across
  • Understand major  components in a primitive trading system to remove dependence on third party trading platforms
  • How crypto currency can off offer one of the most  profit asset classes to trade
  • Strategize coding basics to help  you in analyzing popular technical analysis techniques like Bollinger Bands, Relative Strength Indicators.
  • Learn about software mentioned is open and source which benefits you in controlling all elements of your trading process and strategies
  • Take advantage of the faster NOSQL database that is 100% compared against HFT projects.

ABOUT THE AUTHOR –I’m Bryan Downing and I’m the founder and owner of Quantlabs.net. ‘QLN’ (as I often call it) is unique – it’s the only quant-related website and membership service expressly designed to help you gain practical experience with the quantitative world

And I love the capital markets. It made logical sense to marry my software and investment passions together, so (how many years ago?) I launched QLN for quant analysts, quant researchers, and quant developers.In fact, what really spurred me on was the obvious fact that computer-based algorithmic trading is the way of the future. Every serious institutional investor is now relying on quantitative methods to improve their analysis, risk management, and trading activities. This trend isn’t likely to reverse anytime soon. In fact, it’s going to get more and more competitive (and more and more secretive) as everyone strives for a trading edge and a secret weapon or two to ensure steady profits.

I’m sure you’re thinking the same and I hope you enjoy blending technology, trading, and investments as much as I do!As it stands, my long experience and cutting-edge tutorials can help you to get a job or launch your own business in the quant field. Between my own knowledge and that of our members (yes, we have real live institutional quant members active ‘on the inside’) the QLN practical knowledge base is just going to get bigger, better and more useful.

SUMMARY OF CONTENT

    • Programming Language Overview
    • Python tools and methodology
    • Options to Capture Market Data
    • How to create Pandas dataframe to manipulate data
    • Demo technical analysis indicator functions
    • Redis NOSQL Overview and Sample
    • Funding Crypto Currency account

 

  • Cryptocurrency Outlook and CCXT Python Package overview
  • Crypto Currency trading idea
  • Intro to ChartDirector for Python

 

COURSE ROADMAP

 

SECTION 1 – Programming Language Overview

SECTION DURATION – 28 minutes

SECTION DESCRIPTION – Covers pros and cons of each language you may come across on your journey with algo/automated trading. I also list items you will need to consider when you want do live trading as well using correct concepts of High Frequency Trading (HFT) I cover a series of languages including:

 

  • Course Overview –
  • Offer the pros and cons of typical languages you will use
  • Show how Python is most sensible and popular open source languages

 

SECTION 2 – Python tools and methodology

SECTION DURATION – 43 minutes

SECTION DESCRIPTION – Covers all elements of Python 2 vs 3 including a high level of ‘Hello World’ example. Also covers from a newbie’s POV on non essential Jupyter and Machine Learning packages.

 

  • Python 2 vs 3
  • PIP the package manager
  • Python install options on operating systems
  • Tools like popular editors/IDEs e.g. Sublime
  • Simple Debugging techniques
  • Very high level concepts of popular machine learning frameworks and Jupyter use cases

SECTION 3 – Options to Capture Market Data

SECTION DURATION – 28 minute

SECTION DESCRIPTION –Different options for market data including free vs paid

 

  • IEX and IQFeed
  • LMAX and Interactive Brokers broker overview options
  • Dukascopy Forex.CFD broker Duka Python Package
  • Intro to JForex platform to create CSV using Java example

 

SECTION 4 – How to create Pandas dataframe to manipulate data

SECTION DURATION – 10 minutes

SECTION DESCRIPTION – Simple Python script that does the following

 

  • Read a comma separated value file (CSV)
  • Apply statistical calculation and manipulate rows
  • Export data to CSV or Excel format

 

SECTION 5 – Demo technical analysis indicator functions

SECTION DURATION – 7 minutes

SECTION DESCRIPTION – As the original TA-LIB can be complicated to build yet along with the buggy TA-Lib. Python package, there was another alternative that came up. A much simpler approach with the popular TA-LIB shows a simpler demo of running various indicators. These examples include:

 

  • Bollinger Band
  • Exponential Moving Average
  • Standard Deviation
  • Relative Strength Indicator

 

SECTION 6 – Redis NOSQL Overview and Sample

SECTION DURATION – 30 minutes

SECTION DESCRIPTION -NOSQL Database of choice

 

  • Why this is used
  • Open source and benchmarks
  • Compared against popular open source HFT project
  • Server and client edition
  • Python code demos

 

SECTION 7 – Funding Crypto Currency account

SECTION DURATION – 6 minute

SECTION DESCRIPTION –Options to cover to fund via bank credit card or use an anonymous credit card. Note that these option can be removed, invalid, or change without notification.

 

  • Different credit card option sources
  • Why banks block funding cryptocurrency via credit card
  • Round about way to fund anonymously via credit

 

SECTION 9 – Cryptocurrency Outlook and CCXT Python Package overview

SECTION DURATION – 20 minute

SECTION DESCRIPTION –Over of Python package working examples with no registration needed for popular exchanges

 

  •   Intro to CoinMarket.com to depend on volume
  •   Reliable exchanges at time of recording
  • Advantages of Python option vs web programming languages
  • Examples of CCXT Python Package

 

SECTION 10 – Crypto Currency trading idea with forward looking data tips for your strategy idea Crypto Currency trading idea with forward looking data for your strategy

SECTION DURATION – 11 minutes

SECTION DESCRIPTION –This is a set of ideas where you can use forward looking data to see how institutions gauge Bitcoin. These include:

 

  •    NVT Ratio
  • Futures and Options market
  • COT reports
  • Use of CoinMarketCap.com

 

SECTION 11– Intro to ChartDirector for Python

SECTION DURATION – 19 minutes

SECTION DESCRIPTION –This is an overall demo of features and how to install commercial ChartDirector for Python.

 

  •    How to install on Mac or Linux/Unix like systems
  •    Advantages over other open source Python packages like Matplotlib or Seaborn
  •    Benefits of ChartDirector
  •     Hints of Developing Interactive Self Standalone chart with potential live charting
  • Note that charts are generated via operating platform console terminal

 

This will vary on a product or Python package basis.

 

Minimum Hardware Requirements

For successful completion of this course, students will require computer systems with at least the following:

  • OS: Any
  • Processor: Minimal
  • Memory: 2 GB but may need 4GB if you to choose to install VirtualBox with Ubuntu Linux
  • Storage: Minimal

 

Recommended Hardware Requirements – For an optimal experience with hands-on labs and other practical activities, we recommend the following

configuration:

  • OS: In order of preference of MacOS, Linux (e.g. Ubuntu), and Windows
  • Processor: Any
  • Memory: 2 GB but may need more 4GB if you to choose install VirtualBox with Ubuntu Linux
  • Storage: 12 GB

 

Software Requirements

  • Operating system: See above
  • Browser: Any
  • Python 2.7 but prefer 3.x.
  • Sublime

 

Links and installation are provided in video module as required.