| Course for : | Intermediate |
|---|---|
| Course Deuration : | 3 hours on-demand video |
| In Course Have : | Video, Articles |
| Course Fee : | $9.99 |
What you'll learn
Description
Learn to stop your Algorithmic Trading System when specific Macroeconomic Events are expected
Requirements
- It would be best if you had in Trading and pitfalls
- You’d like to master Data Science using Trading
- PC Windows (min 4CPU 8Gb RAM). The machine must be turned on continuously for some time.
- MQL4 and the R basic level
- The most effective with 1 3 courses or four-course from the Lazy Trading Series
- Twitter account
Description
Learn more about this course: Check out the latest news and analyze sentiment.
The fifth installment of this series gives you the capability to automatically look through the Forex Calendar for any specific date, like US Non-Farm Payroll or when President Trump will be giving an address. This will allow you to include these events in your trading strategies. It is a simple way of deactivating the trading robots.
The second part of the course will briefly focus on the relationship between an Asset’s Text sentiment and the asset’s price. The research will focus using two trading strategies*:
- Sentiment variance of news headlines in the US, Canada, GB and the currency pair they use.
- Twitter’s sentiment is a significant source of Twitter information relevant to Tesla’s Prices of Tesla stock.
Like always, the ways and concepts will help us practice the skills of data and computer science:
- Web scrap news and look at their trading sentiment
- Setting up Version Control in our Projects
- Learn how to automatize our R code
- Text Sentiment analysis using the basic Sentiment Analysis Polarity Scoring, and NRC Sentiment Dictionary (8 emotions)
- Conducting a descriptive analysis to determine the Sentiment Polarity Scoring of News Headers
- Transferring Twitter details into R
- Deep regression learning for correlating sentiment scores with the objective variable (performed in the H2O deep learning environment[performed in the h2o deep learning environment
It can be no assurance that the methods proposed are effective!!
About the Lazy Trading Courses:
This course series is designed to provide the thrilling experience of Algorithmic Trading and simultaneously master the basics of Computer and Data Science! The focus is on building the foundations of a Decision Support System that can assist in automating a variety of the tedious processes associated with Trading.
This project includes several short courses that are designed to help you manage all aspects of Automated Trading Systems:
- Create Your Home Trading Environment
- Configure Your Trading Strategy Robot
- Create your automated Trading Journal
- Statistical Automated Trading Control
- Reading News and Sentiment Analysis
- Utilizing Artificial Intelligence to detect the market state
- Designing the foundations of an AI trading system
Updating: specially designed R-based package called ‘lazy trade’ was developed to make it easier for code sharing between various classes
IMPORTANT:
- The courses will be all-in-one, focused on a specific subject with brief theoretical explanations. These courses will allow you to develop strategies that automatize routine but crucial procedures for traders.
- The best way to learn the classes in a series is to duplicate all, creating an automated trading system using PC Windows.
What can you expect to learn in addition to Trading:
When you complete these courses, you will gain more knowledge than just trading, using the examples provided.
- Practice and learn to use the Decision Support System
- Get organized and efficient by using Version Control and Automated Statistical Analysis
- Learn with R to manipulate, read and carry out Machine Learning including Deep Learning
- Study and practice Practice data Visualization
- Learn about sentiment analysis and scraping websites
- Get Shiny and deploy any project involving data within hours
- Find productivity tips
- Automate your tasks and schedule them
- See examples of MQL4 that can be expanded and R code.
These courses are not:
- They will not be able to provide instruction and explanations of certain programming ideas in detail
- These classes are not designed to introduce the basics or the fundamentals of Data Science or Trading
- There is no guarantee of bugs-free programming.
Disclaimer:
Trading involves risk. This course is not considered a financial service or advice. Past performance is not guaranteeable for the future.
Who should this course be intended for:
- Anyone who would like to become more productive
- Anyone who wants to know more about Data Science
- Anyone who would like to test Algorithmic Trading but have little time
- Anyone interested to learn more about Web Scrapping and Text Analytics
