Lazy Trading Part 5: Read Forex news and Sentiment Analysis
Lazy Trading Part 5: Read Forex news and Sentiment Analysis
About this Course: Read news and Sentiment Analysis
The fifth part of this series will give you the ability to automatically read Forex Calendar for any specific event like US Non-Farm Payroll or when President Trump is going to have a speech. This will provide an ability to consider these events in your trading strategies in a simplest form of disabling the trading robots.
Additional research of this course will be about correlation of Asset's Text data Sentiment to the Asset's price in the future. This research will be conducted on two trading ideas*:
Sentiment difference of News Headers in the US, Canada, GB and it's their currency Pairs.
Sentiment of Twitter data relevant to Tesla Stock prices
As usual provided methods and ideas will help us to practice computer and data science skills:
Webscrap news and analyse their sentiment for trading
Setting up Version Control in our Projects
Know how to automate our R code
Text Sentiment analysis using basic Sentiment Analysis Polarity Scoring and NRC Sentiment Dictionary (8 emotions)
Performing descriptive analysis of the Sentiment Polarity Scoring of the News Headers
Getting Twitter data into R
Deep regression learning to correlate Sentiment scores to the objective variable [performed in h2o deep learning environment]
*There is absolutely no guarantee that proposed methods will work!!!
About the Lazy Trading Courses:
This series of courses is designed to to combine fascinating experience of Algorithmic Trading and at the same time to learn Computer and Data Science! Particular focus is made on building foundation of Decision Support System that can help to automate a lot of boring processes related to Trading.
This project is containing several short courses focused to help you managing your Automated Trading Systems:
Set up your Home Trading Environment
Set up your Trading Strategy Robot
Set up your automated Trading Journal
Statistical Automated Trading Control
Reading News and Sentiment Analysis
Using Artificial Intelligence to detect market status
Building an AI trading system
Update: dedicated R package 'lazytrade' was created to facilitate code sharing among different courses
IMPORTANT:
All courses will be short focusing to one specific topic with very short theoretical explanations. These courses will help to focus on developing strategies by automating boring but important processes for a trader.
Best possible way to take the courses as a series is to reproduce all methods by re-creating automated trading system on PC Windows
What will you learn apart of trading:
While completing these courses you will learn much more rather than just trading by using provided examples:
Learn and practice to use Decision Support System
Be organized and systematic using Version Control and Automated Statistical Analysis
Learn using R to read, manipulate data and perform Machine Learning including Deep Learning
Learn and practice Data Visualization
Learn sentiment analysis and web scrapping
Learn Shiny to deploy any data project in hours
Get productivity hacks
Learn to automate your tasks and scheduling them
Get expandable examples of MQL4 and R code
What these courses are not:
These courses will not teach and explain specific programming concepts in details
These courses are not meant to teach basics of Data Science or Trading
There is no guarantee on bug free programming
Disclaimer:
Trading is a risk. This course must not be intended as a financial advice or service. Past results are not guaranteed for the future.
Learn to stop your Algorithmic Trading System when specific Macroeconomic Events are expected
Url: View Details
What you will learn
- Web Text scrapping in R
- Learn how to read Macroeconomic news in R
- Do Text Sentiment analysis
Rating: 4.4
Level: Intermediate Level
Duration: 3 hours
Instructor: Vladimir Zhbanko
Courses By: 0-9 A B C D E F G H I J K L M N O P Q R S T U V W X Y Z
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