Algo Trading with Python: Build Indicators and Manage Risks
The Complete Course of Programming, Indicator Building and Risk Management for Forex and Crypto
Finance and Accounting,Investing and Trading,Algorithmic Trading
Lectures -61
Resources -14
Duration -4 hours
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Course Description
Are you a trader who is interested in learning how to build their own trading algorithm?
If so, this course will teach you the basics of Python - you will learn about all the native data types in Python, and know how to work with control flow structure so that you can have decision logic built into your code.
Trading is hard, but it is also highly rewarding. With Python, you can put in a methodical system to build your own rule-based algorithm in order to get to your goal efficiently.
Python is also the perfect language for AI-based algorithms using a variety of machine learning techniques. The AI-based courses are coming soon.
This complete course of algo trading with Python will teach all the Python syntax you need to know, and get you ready for working with Pandas, taking care of the DateTime objects, and handling errors. You will then immediately learn about how to use Python to connect to the MetaTrader5 terminal and get market data as well as account information programmatically from your broker directly. You will also learn about constructing indicators that work for your style of trading, by using Pandas, Ta-Lib, or writing your own user-defined functions. You will learn how to programmatically compute position size but first decide where you would like to place your stop loss level, and then query some account information to complete the computation. You will learn about the specific ways that you will communicate, using Python, with your brokers to enter and/or exit trades with the computed size for your risk tolerance. Further, you will also learn about how to set the stop loss and take profit, how to move stop loss to breakeven, and how to update (trail) your stop-loss level after that point. Once you have learned all about these topics, you are able to build as many elaborate risk management strategies as you want in a way that you like to trade.
At the end of this course, you will have a firm understanding of what goes into building an algorithmic trading strategy from scratch. You will have not only all the tools necessary to create your own algorithmic strategies, but you will also know how to manage your positions, as well as take what you already know and set up a backtesting environment for yourself so that you are able to systematically build and test strategies on an on-going basis.
The goal of the series is to give you an understanding of what goes into building an algorithmic trading strategy from scratch. By the end of the three-part series, you should have not only all the tools necessary to create your own algorithmic strategies, but you will also know how to manage your positions.
Goals
Build a complete algorithm, from scanning the market, and placing trades, to managing trades.
Learn how to build indicators that work for you.
Learn how to interact with your brokers programmatically and directly.
Use code to be systematic in trading and get your time back.
Learn how to enter a trade, exit a trade, and get other account data programmatically.
Learn Python skills to protect your accounts and profits.
Learn all the skills so that you are able to build a backtesting system for your algorithm from this course.
Prerequisites
No programming experience is required. I will teach you everything you need to know.

Curriculum
Check out the detailed breakdown of what’s inside the course
Optional (For Mac Users)
1 Lectures
-
Optional (For Mac Users) 05:06 05:06
Installing Anaconda
1 Lectures

Install Ta-Lib
1 Lectures

Python Primer
9 Lectures

Learning Pandas
16 Lectures

Writing User-Defined Functions
6 Lectures

Handling Datetime
5 Lectures

Getting Broker Data
3 Lectures

Building Indicators
3 Lectures

Getting Account Info
1 Lectures

Position Sizing
3 Lectures

Putting It Together
6 Lectures

Trailing
6 Lectures

Instructor Details

Jenny Hung
Jenny had always loved math, but she decided to pursue accounting in the first place. She has 10 years of experience in tax compliance and tax planning, her passion for math was reignited, and she went back to school to study mathematics and statistics.
Jenny believes that numbers help us understand the world, and a math-based approach helps us understand numbers because mathematics is essentially a way of thinking through any problem. We are surrounded by numbers, equations and algorithms – especially in this age of the digital world, data is the ammunition for the digital world.
She loves coding, data analysis, quantitative finance, and everything mathematical. Her specialty is finance / econometrics-related deep reinforcement learning and uses data analysis and machine learning to support the decision-making process.
More importantly than her love of code and math, she loves to make a difference and inspire. This is because citizens of the globe don’t always get to vote to either get in or stay out of this digital world — even when people are not actively participating in the digital world, they are passively being involved in it. Data about this world, and the algorithms that feed upon the data, are shaping our world in ways that are not always desirable to the passive participants.
Her goal with this signature course is to teach as many people as possible the vital skills of critical data thinking, data analysis and applied machine learning so that students can leverage these life-long skills to improve their lives.
Jenny has a law degree, studied Mathematics and Statistics, and is a CPA from Canada.
Course Certificate
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