English | MP4 | AVC 1920×1080 | AAC 48KHz 2ch | 4h 50m | 890 MB
Introducing the study of machine learning and algorithmic trading for financial practitioners
Have you ever wondered how the Stock Market, Forex, Cryptocurrency and Online Trading works? Have you ever wanted to become a rich trader having your computers work and make money for you while you’re away for a trip in the Maldives? Ever wanted to land a decent job in a brokerage, bank, or any other prestigious financial institution?We have compiled this course for you in order to seize your moment and land your dream job in financial sector. This course covers the advances in the techniques developed for algorithmic trading and financial analysis based on the recent breakthroughs in machine learning. We leverage the classic techniques widely used and applied by financial data scientists to equip you with the necessary concepts and modern tools to reach a common ground with financial professionals and conquer your next interview.By the end of the course, you will gain a solid understanding of financial terminology and methodology and a hands-on experience in designing and building financial machine learning models. You will be able to evaluate and validate different algorithmic trading strategies. We have a dedicated section to backtesting which is the holy grail of algorithmic trading and is an essential key to successful deployment of reliable algorithms.
Algorithmic trading in practise is a very complex process and it requires data engineering, strategies design, and models evaluation. This course covers every single step in the process from a practical point of view with vivid explanation of the theory behind. The concepts and theories are explained with the aid of illustrations, diagrams and charts whenever possible to make it easier to grasp. The coding parts are explained line by line with clear reasoning why everything is done the way it is.
What You Will Learn
- You will learn about financial terminology and methodology and how to apply them
- Get hands-on financial data structures and financial machine learning
- Understand complex financial terminology and methodology in simple ways
- Ensemble models and cross-validation for financial applications
- Backtesting for models and strategies evaluation and validation
- Apply your skills to real world cryptocurrency trading such as BitCoin and Ethereum
- Putting machine learning into real world problems and derive solutions
Table of Contents
Building Your First Trading Bot
1 The Course Overview
2 Introduction to Financial Machine Learning and Algorithmic Trading
3 Setting up the Environment
4 Project Skeleton Overview
5 Fetching and Understanding the Dataset
6 Build the Conventional Buy and Hold Strategy
7 Evaluate the Strategy’s Performance
Design a Machine Learning Model
8 Intuition behind Random Forests Algorithm
9 Build and Implement Random Forests Algorithm
10 Plug-in Random Forests Implementation into Your Bot
11 Evaluate Random Forest’s Performance
Build a Trading Algorithm
12 Introducing Online Algorithms
13 Getting Statistical Correlation
14 Implement Exploit Correlation Strategy
15 Evaluate the Strategy
Design Advanced Machine Learning Model
16 Ensemble Learning Theory
17 Implementing GBoosting Using Python
18 Evaluating the Model Performance
Build Advanced Trading Algorithm
19 Introduction to Scalpers Trading Strategy
20 Implement Scalpers Trading Strategy
21 Evaluate Scalpers Trading Strategy
Model and Strategy Evaluation
22 Introducing Value at Risk Backtest
23 Implement Value at Risk Backtest
24 Value at Risk with Machine Learning
25 Implement VaR Using SVR
26 Conclusion and Next steps
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