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:
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Build a live trading bot
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Create a fast, accurate strategy testing system
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Retrieve live headlines, sentiments, technicals and more from the web.
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Use databases to store and correlate data with market moves
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Build a web application showing the latest prices, sentiments and other market data
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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
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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
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You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
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