Algo Trading with Python- Build Indicators and Manage Risks

Algo Trading with Python: Build Indicators and Manage Risks, available at $34.99, has an average rating of 3.55, with 61 lectures, based on 11 reviews, and has 91 subscribers.

You will learn about Build a complete algorithm, from scanning market, 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 the Python skills to protect your accounts and profits Learn all the skills so that you are able to build a backtesitng system for your algorithm from this course This course is ideal for individuals who are Forex and crypto traders who are interested in algorithimic trading or Forex and crypto traders who are interested in using machine learning in your algorithms in the future It is particularly useful for Forex and crypto traders who are interested in algorithimic trading or Forex and crypto traders who are interested in using machine learning in your algorithms in the future.

Enroll now: Algo Trading with Python: Build Indicators and Manage Risks

Summary

Title: Algo Trading with Python: Build Indicators and Manage Risks

Price: $34.99

Average Rating: 3.55

Number of Lectures: 61

Number of Published Lectures: 61

Number of Curriculum Items: 61

Number of Published Curriculum Objects: 61

Original Price: $79.99

Quality Status: approved

Status: Live

What You Will Learn

Build a complete algorithm, from scanning market, 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 the Python skills to protect your accounts and profits

Learn all the skills so that you are able to build a backtesitng system for your algorithm from this course

Who Should Attend

Forex and crypto traders who are interested in algorithimic trading

Forex and crypto traders who are interested in using machine learning in your algorithms in the future

Target Audiences

Forex and crypto traders who are interested in algorithimic trading

Forex and crypto traders who are interested in using machine learning in your algorithms in the future

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.

Course Curriculum

Chapter 1: Do This If You Are On a Mac

Lecture 1: Optional (For Mac Users)

Chapter 2: Installing Anaconda

Lecture 1: Installing Anaconda

Chapter 3: Install Ta-Lib

Lecture 1: Installing Ta-Lib

Chapter 4: Python Primer

Lecture 1: Python Expressions

Lecture 2: Overview of Data Types

Lecture 3: Numerical Data Type

Lecture 4: String Data Type

Lecture 5: List Data Type

Lecture 6: Tuple Data Type

Lecture 7: Set Data Type

Lecture 8: Dictionary Data Type

Lecture 9: Control Flow Structure

Chapter 5: Learning Pandas

Lecture 1: Course Introductions and Overview

Lecture 2: Working with Pandas DataFrame

Lecture 3: DataFrame at a Glance

Lecture 4: Working with DataFrame – Part 2

Lecture 5: DataFrame at a Glance – Part 2

Lecture 6: Accessing Columns

Lecture 7: Accessing Columns – Part 2

Lecture 8: Subsetting, Indexing and Slicing

Lecture 9: Unique Values

Lecture 10: Selecting Rows

Lecture 11: Selecting Rows – Part 2

Lecture 12: Subsetting

Lecture 13: Adding New Columns

Lecture 14: Sorting

Lecture 15: Using Groupby

Lecture 16: Pandas Summary

Chapter 6: Writing User-Defined Functions

Lecture 1: Python Function Overview

Lecture 2: Functions

Lecture 3: Error Handling – Try / Except

Lecture 4: Why Using Error-Handling

Lecture 5: Functions – Part 2

Lecture 6: Best Practices

Chapter 7: Handling Datetime

Lecture 1: Datetime Objects in Python

Lecture 2: Timezones

Lecture 3: Timedelta

Lecture 4: Converting Datetime to String

Lecture 5: Conveting String to Datetime

Chapter 8: Getting Broker Data

Lecture 1: Installing MetaTrader5 Module

Lecture 2: Connecting to MT5 Terminal

Lecture 3: Setting Timezones to Match Market Watch Time

Chapter 9: Building Indicators

Lecture 1: Overview

Lecture 2: Building Indicators via Pandas

Lecture 3: Building Indicators via Ta-Lib

Chapter 10: Getting Account Info

Lecture 1: Getting Account Info

Chapter 11: Position Sizing

Lecture 1: Recap

Lecture 2: Stoploss

Lecture 3: Calculate Size

Chapter 12: Putting It Together

Lecture 1: Putting It Together

Lecture 2: Putting It Together for Long Positions

Lecture 3: Putting It Together for Short

Lecture 4: One More Thing

Lecture 5: Summary

Lecture 6: Documentation and Summary

Chapter 13: Trailing

Lecture 1: Recap of What We Have So Far

Lecture 2: Updating Stoploss

Lecture 3: Updating Stoploss – Part 2

Lecture 4: Move Stops to Breakeven and Trail Afterwards for Long Positions

Lecture 5: Move Stops to Breakeven and Trail Afterwards for Short Positions

Lecture 6: Overall Summary

Instructors

Jenny Hung
Data Scientist, Mentor, and Trader

Rating Distribution

1 stars: 1 votes

2 stars: 2 votes

3 stars: 1 votes

4 stars: 5 votes

5 stars: 2 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!