Complete algorithmic forex trading and back testing system

Complete algorithmic forex trading and back testing system, available at $94.99, has an average rating of 4.86, with 317 lectures, based on 772 reviews, and has 6357 subscribers.

You will learn about Build a robust live 24/7 trading bot with Python Learn to use Python and multi-threading to stream live prices Leverage multi-threading, events and work queues to make trading decisions Build a comprehensive strategy back testing system that tests thousands of trades a second Learn how to integrate spread and fine grain prices into your strategy testing for accurate results Archive historical data and back test multiple instruments over a six+ year period Learn data science techniques with Jupyter Notebooks and Pandas to analyse your results Automate spreadsheet creation with tables and charts for further analysis Have some fun evaluating popular YouTube strategies with promised 90% win rates Learn to identify single, dual and multi-candle patterns Learn to develop indicators such as MACD, RSI and Keltner Channels Use Python to scrape the web for information to help build your strategies Use web scraping to get live economic calendar data, headlines and sentiments Create and interact with MongoDB to store information Build a full featured React web application to display technicals, sentiments, headlines, prices and your bot status Create a Flask API backend with endpoints to access technicals, sentiments, headlines, prices.. etc. Deploy your bot to a cloud service Learn to implement comprehensive logging This course is ideal for individuals who are Someone who is interested in building and automating trading systems or Someone who want to learn common data science techniques It is particularly useful for Someone who is interested in building and automating trading systems or Someone who want to learn common data science techniques.

Enroll now: Complete algorithmic forex trading and back testing system

Summary

Title: Complete algorithmic forex trading and back testing system

Price: $94.99

Average Rating: 4.86

Number of Lectures: 317

Number of Published Lectures: 317

Number of Curriculum Items: 317

Number of Published Curriculum Objects: 317

Original Price: 99.99

Quality Status: approved

Status: Live

What You Will Learn

Build a robust live 24/7 trading bot with Python

Learn to use Python and multi-threading to stream live prices

Leverage multi-threading, events and work queues to make trading decisions

Build a comprehensive strategy back testing system that tests thousands of trades a second

Learn how to integrate spread and fine grain prices into your strategy testing for accurate results

Archive historical data and back test multiple instruments over a six+ year period

Learn data science techniques with Jupyter Notebooks and Pandas to analyse your results

Automate spreadsheet creation with tables and charts for further analysis

Have some fun evaluating popular YouTube strategies with promised 90% win rates

Learn to identify single, dual and multi-candle patterns

Learn to develop indicators such as MACD, RSI and Keltner Channels

Use Python to scrape the web for information to help build your strategies

Use web scraping to get live economic calendar data, headlines and sentiments

Create and interact with MongoDB to store information

Build a full featured React web application to display technicals, sentiments, headlines, prices and your bot status

Create a Flask API backend with endpoints to access technicals, sentiments, headlines, prices.. etc.

Deploy your bot to a cloud service

Learn to implement comprehensive logging

Who Should Attend

Someone who is interested in building and automating trading systems

Someone who want to learn common data science techniques

Target Audiences

Someone who is interested in building and automating trading systems

Someone who want to learn common data science techniques

Whilst fun, Forex trading is not easy! To be successful today, you must have the ability to test strategies, automate trading and access information.

IMPORTANT:

Note: For this course, we will use the Oanda API service. It is available in most countries worldwide, however please check before purchasing the course.  You can check in video #3 called “Oanda account setup and API access”

Whether it’s as a hobby or professional, this course will give you the foundation upon which you will be able to:

Build a live trading bot

Create a fast, accurate strategy testing system

Retrieve live headlines, sentiments, technicals and more from the web.

Use databases to store and correlate data with market moves

Build a web application showing the latest prices, sentiments and other market data

Learn full stack development, using MongoDB, Python and JavaScript (with React)

We will start by learning to use Python to access the Oanda REST API. Next, we’ll download a few thousand candles and develop a simple strategy back test, testing multiple parameters and currency pairs at once. We’ll use the results from this back test to learn how to automate the export of results into a spreadsheet format with tables and graphs.

Once the simple strategy has been tested, we’ll get hold of a lot more data – six years’ worth for multiple time frames. We’ll rerun our simple strategy, and then move on to implementing candle pattern detection and indicator calculation. We will also look at using multi-processing to speed up the testing even more.

Now we have some more knowledge, it’s time to create a more comprehensive back testing system – with spread and breaking candles down into finer time frames. For testing we will choose two strategies with over a million views on YouTube and assess whether they really give the claimed 90% win rate…

It’s now time to move on to the big moment – the live trading bot. We will develop a robust trading bot that trades multiple pairs with comprehensive logging. We will structure the code such that it is easy to swap in and out strategies.

Now it’s time to get more advancedand learn how stream prices live – using multi-threading with events and work queues to react to prices and make decisions

We will learn how to use Web Scraping with Python to access live sentiments, technicals, headlines and economic data. Alongside this, we’ll create a MongoDB database to store our data.

Next up: React!We will use the famous framework to develop ourselves a web application that can access live prices, our sentiment data and much more.

Finally, we will deploy our trading bot on a cloud service.

The course includes a quick-start appendix for Python and for HTML/CSS/JavaScript.

Course Curriculum

Chapter 1: Introduction

Lecture 1: What does intermediate mean?

Lecture 2: What is the aim of this course?

Chapter 2: Account Setup & Forex Trading Introduction

Lecture 1: Oanda account setup and API access

Lecture 2: How forex trading works part one

Lecture 3: How forex trading works part 2

Chapter 3: Environment Setup

Lecture 1: Overview

Lecture 2: Python installation

Lecture 3: What are Python virtual environments?

Lecture 4: Python virtual environments on Windows

Lecture 5: Python virtual environments on Linux / Mac OS

Lecture 6: The pip upgrade warning

Lecture 7: Visual Studio Code and extensions

Lecture 8: Postman

Chapter 4: The Oanda API

Lecture 1: Introduction

Lecture 2: Oanda API documentation and authorization

Lecture 3: Accounts endpoint

Lecture 4: Account summary endpoint

Lecture 5: Account instruments endpoint

Lecture 6: Instrument Candles Endpoint

Lecture 7: Pricing endpoint

Chapter 5: Initial exploration with Python

Lecture 1: Introduction

Lecture 2: Jupyter Notebook setup

Lecture 3: Our first request

Lecture 4: The instruments API

Lecture 5: Fetching candles #1

Lecture 6: Fetching candles #2

Lecture 7: Fetching candles #3

Lecture 8: Fetching candles #4 – saving data to file

Lecture 9: Fetching candles #5 – saving multiple instruments

Lecture 10: The OandaApi class

Lecture 11: Making a request from the OandaApi class

Lecture 12: Making a request from the OandaApi class #2

Lecture 13: Instrument class

Lecture 14: Instrument collection class

Lecture 15: Instrument collection class #2

Chapter 6: The Moving Average Cross Strategy

Lecture 1: Introduction

Lecture 2: Plotting a candlestick chart with Plotly

Lecture 3: Styling the candlestick chart

Lecture 4: Creating a plotting class

Lecture 5: Strategy introduction

Lecture 6: The moving average cross

Lecture 7: Calculating a moving average

Lecture 8: Plotting a moving average

Lecture 9: Plotting multiple moving averages

Lecture 10: Calculating the deltas

Lecture 11: Detecting Trades

Lecture 12: Pandas and groupby

Lecture 13: Evaluating gains (or losses)

Lecture 14: Plotting gains over time

Lecture 15: Moving into a script

Lecture 16: Loading price data

Lecture 17: Applying crosses

Lecture 18: Calculating results for multiple instruments

Lecture 19: The Result class

Lecture 20: Creating results

Lecture 21: Converting results to Dataframes

Lecture 22: Combining all results together

Lecture 23: Saving the results #1

Lecture 24: Saving the results #2

Lecture 25: Loading back test results

Lecture 26: Do we have a winner?

Lecture 27: Finding the best cross

Lecture 28: How good is our chosen cross?

Chapter 7: Automating Spreadsheets

Lecture 1: Introduction

Lecture 2: 2023 xlsxwriter changes

Lecture 3: Preparing the xlsxwriter code

Lecture 4: Saving results to xlsx

Lecture 5: Exporting the cumulative gains

Lecture 6: Charting the cumulative gains

Lecture 7: Summary

Chapter 8: Collecting (much) more data

Lecture 1: Introduction

Lecture 2: Fetching candles from the OandaApi class

Lecture 3: Loading candle DataFrames from the OandaApi class

Lecture 4: Collection function definitions

Lecture 5: Collection entry function

Lecture 6: Date ranges

Lecture 7: Running the data fetch from the API

Lecture 8: Collecting a lot of data

Lecture 9: Checking the collected data

Lecture 10: Re-run of the moving avg. cross with six years of data.

Chapter 9: Calculating trading indicators

Lecture 1: Introduction

Lecture 2: Bollinger bands introduction

Lecture 3: Bollinger bands calculation

Lecture 4: Average True Range

Lecture 5: Keltner Channels

Lecture 6: Relative Strength Index (RSI)

Lecture 7: Moving Average Convergence Divergence (MACD)

Chapter 10: Identifying candle patterns

Lecture 1: Introduction

Lecture 2: Candle characteristics

Lecture 3: Coding candle characteristics #1

Instructors

Richard Allbert
Digital Decode GmbH

Rating Distribution

1 stars: 5 votes

2 stars: 4 votes

3 stars: 12 votes

4 stars: 164 votes

5 stars: 587 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!