by Mustafa Qamar-ud-Din | Publisher: Packt Publishing | Release Date: February 2019 | ISBN: 9781789951165

Introducing the study of machine learning and algorithmic trading for financial practitioners About This VideoBuilding high-frequency trading robotsApplying feature engineering on stock market dataDiving deeper into the pros and cons of various financial data structuresBuilding & evaluating many machine learning modelsImplementing backtesting econometrics for trading strategies evaluationHacking Ensemble Learning Algorithms in Machine LearningFeaturing a premiere on Ensemble Learning with Bagging & BoostingExperience-based tutorials and hands-on financial challengesIn DetailHave 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.The code bundle for this video course is available at - https://github.com/PacktPublishing/Machine-Learning-for-Algorithmic-Trading-Bots-with-PythonDownloading the example code for this course: You can download the example code files for all Packt video courses you have purchased from your account at http://www.PacktPub.com. If you purchased this course elsewhere, you can visit http://www.PacktPub.com/support and register to have the files e-mailed directly to you.

1. Chapter 1 : Building Your First Trading Bot
   • The Course Overview 00:04:18
   • Introduction to Financial Machine Learning and Algorithmic Trading 00:18:39
   • Setting up the Environment 00:08:07
   • Project Skeleton Overview 00:05:33
   • Fetching and Understanding the Dataset 00:18:31
   • Build the Conventional Buy and Hold Strategy 00:06:18
   • Evaluate the Strategy’s Performance 00:09:50
2. Chapter 2 : Design a Machine Learning Model
   • Intuition behind Random Forests Algorithm 00:17:57
   • Build and Implement Random Forests Algorithm 00:23:51
   • Plug-in Random Forests Implementation into Your Bot 00:06:57
   • Evaluate Random Forest’s Performance 00:05:21
3. Chapter 3 : Build a Trading Algorithm
   • Introducing Online Algorithms 00:08:46
   • Getting Statistical Correlation 00:07:18
   • Implement Exploit Correlation Strategy 00:20:11
   • Evaluate the Strategy 00:07:13
4. Chapter 4 : Design Advanced Machine Learning Model
   • Ensemble Learning Theory 00:06:03
   • Implementing GBoosting Using Python 00:16:47
   • Evaluating the Model Performance 00:16:28
5. Chapter 5 : Build Advanced Trading Algorithm
   • Introduction to Scalpers Trading Strategy 00:06:37
   • Implement Scalpers Trading Strategy 00:34:15
   • Evaluate Scalpers Trading Strategy 00:08:23
6. Chapter 6 : Model and Strategy Evaluation
   • Introducing Value at Risk Backtest 00:04:57
   • Implement Value at Risk Backtest 00:09:51
   • Value at Risk with Machine Learning 00:04:16
   • Implement VaR Using SVR 00:10:14
   • Conclusion and Next steps. 00:03:34