
This video provides an overview of the entire course.
What is a trading bot? Why as a programmer should you invest time in a building a trading bot? How to go about building a bot?
Introduction to trading bots
Understand the reason to build a trading bot
Learn to build a trading bot
Learn the basics of how to get and handle historical trade data, which forms the basis of analyzing any stock data. Use Python and some modules to do the same.
Discuss the required software
Handle stocks data from the internet
Learn to load stocks data from the local machine
Understand what time series data is and learn how to use Python and modules to explore and analyze stock time series data.
Discuss the basics of time series data
Read, explore, analyze, and visualize stock data for a single stock
Learn to handle data from multiple stocks
Learn about various order types and understand what short selling is.
Discuss various order types
Explain short selling
A code solution demonstrating analysis of stock market data.
Set up the demo
Write live code for the code demo
Explain the code as we go
How to design a trading algorithm.
Explain the top-level steps for writing a trading algorithm
Explain each step in detail
Describe how the steps integrate with each other
Explain how to structure your trading algorithm.
Introduce a trading strategy
Learn to write code for a trading strategy
Investigate the performance evaluation of a trading algorithm
Demonstrate how to back-test or trial trades in code.
Introduce back-testing or running trial trades
Write code for running trial trades
Evaluate the performance of trial trades with the trade strategy
Demonstrate writing a trading logic for futures trade.
Introduce the Quantopian platform
Write a trading logic in Quantopian
Run the algorithm and view the performance
Explain different types of orders that can be handled by Quantopian.
Talk about various data available for use in algorithms
Use various data in the algorithms
Understand what volatility means in trading.
Explore trade volatility
Handle volatility in markets
Demonstrate the running of a trading algorithm on Quantopian.
Walk through the code for the algorithm
Run the algorithm on Quantopian
Evaluate the results of the run
Introduce FXCM and how to use it to build forex trades in Python.
Introduce FXCM, the online forex trading platform
Set up FXCM in your development environment
Demonstrate forex trading in Python with FXCM
Use FXCM data to explain how forex plots and charts work and how to analyze them.
Various forex plots and charts
Use FXCM to plot and analyze forex data
Explain how supply and demand work in the forex market.
Explain what supply is in the forex market
Understand demand in the forex market
Interaction of supply and demand with each other
Demonstrate how to do trend analysis in FXCM for forex.
Use FXCM for trend analysis
Explain FXCM Candle Stick chart analysis
Configure the FXCM UI to customize the charts
This course is a great opportunity to get started with trading, reap the rewards, and take the markets by storm. Programmers who have a basic knowledge of trading in traditional assets and wish to develop their own trading bots will find that this course addresses their core concerns and shows how to go about designing and developing a trading bot.
The course will enable you to get started with creating a traditional asset trading bot. It will arm you with all the necessary programming tools and techniques to develop a full-fledged trading bot that numerous investors/traders can utilize. It covers general features such as using a financial calculator to do conversions, simply by interacting with a bot. Your customers, using your trading, bot can look up recent trends to make informed predictions and see what others have been trading, and how much.
About the Author
Harish Garg, founder of BignumWorks Software LLP, is a data scientist and a lead software developer with 17 years' software industry experience. BignumWorks is an India-based software consultancy that provides consultancy services in software development and technical training. Harish has worked for McAfee\Intel for 11+ years. He is an expert in creating data visualizations using R, Python, and web-based visualization libraries.
Mithun Lakshmanaswamy of BignumWorks Software LLP has been developing applications in Python for 9+ years. He has written enterprise-level distributed applications that are deployed on scores of servers and have the ability to support thousands of users simultaneously. Some of the applications he has developed are related to parsing millions of virus definitions, analyzing network packets from an enterprise setup, and so on. He is also quite proficient in teaching technical concepts and is quite involved with his current organization’s training programmes. He has worked on multiple projects working with Python, AWS and so on, implementing the concepts of concurrent and distributed computing.