Loonycorn – Machine Learning – Quant Trading

Table of Contents

1. INTRODUCTION
   1. You, This Course, and Us! 00:02:01
2. DEVELOPING TRADING STRATEGIES IN EXCEL
   1. Are markets efficient or inefficient? 00:10:27
   2. Momentum Investing 00:11:31
   3. Mean Reversion 00:06:30
   4. Evaluating Trading Strategies – Risk and Return 00:16:22
   5. Evaluating Trading Strategies – The Sharpe Ratio 00:10:16
   6. The 2 Step process – Modeling and Backtesting 00:03:49
   7. Developing a Trading Strategy in Excel 00:11:42
3. SETTING UP YOUR DEVELOPMENT ENVIRONMENT
   1. Installing Anaconda for Python 00:09:00
   2. Installing Pycharm – a Python IDE 00:03:55
   3. MySQL Introduced and Installed – Mac OS X 00:07:04
   4. MySQL Server Configuration and MySQL Workbench – Mac OS X 00:17:32
   5. MySQL Installation – Windows 00:06:32
   6. For Linux-Mac OS Shell Newbies – Path and Other Environment Variables 00:08:26
4. SETTING UP A PRICE DATABASE
   1. Programmatically Downloading Historical Price Data 00:06:24
   2. Code Along – Downloading Price Data from Yahoo Finance 00:14:40
   3. Code Along – Downloading a URL in Python 00:07:39
   4. Code Along – Downloading Price Data from the NSE 00:13:55
   5. Code Along – Unzip and Process the Downloaded Files 00:05:22
   6. Manually download data for 10 years 00:01:00
   7. Code Along – Download Historical Data for 10 years 00:06:26
   8. Inserting the Downloaded Files into a Database 00:10:11
   9. Code Along – Bulk Loading Downloaded Files into MySQL Tables 00:15:13
   10. Data Preparation 00:04:16
   11. Code Along – Data Preparation 00:12:43
   12. Adjusting for Corporate Actions 00:08:41
   13. Code Along – Adjusting for Corporate Actions 1 00:15:29
   14. Code Along – Adjusting for Corporate Actions 2 00:08:47
   15. Code Along – Inserting Index Prices into MySQL 00:05:41
   16. Code Along – Constructing a Calendar Features Table in MySQL 00:06:54
5. DECISION TREES, ENSEMBLE LEARNING AND RANDOM FORESTS
   1. Planting the seed – What are Decision Trees 00:17:02
   2. Growing the Tree – Decision Tree Learning 00:18:04
   3. Branching out – Information Gain 00:18:51
   4. Decision Tree Algorithms 00:07:51
   5. Overfitting – The Bane of Machine Learning 00:19:04
   6. Overfitting Continued 00:11:20
   7. Cross-Validation 00:18:55
   8. Regularization 00:07:18
   9. The Wisdom of Crowds – Ensemble Learning 00:16:39
   10. Ensemble Learning continued – Bagging, Boosting and Stacking 00:18:03
   11. Random Forests – Much More Than Trees 00:12:28
6. A TRADING STRATEGY AS MACHINE LEARNING CLASSIFICATION
   1. Defining the Problem – Machine Learning Classification 00:15:51
7. FEATURE ENGINEERING
   1. Know the basics – A Pandas tutorial 00:11:42
   2. Code Along – Fetching Data from MySQL 00:18:35
   3. Code Along – Constructing Some Simple Features 00:07:28
   4. Code Along – Constructing a Momentum Feature 00:08:42
   5. Code Along – Constructing a Jump Feature 00:05:52
   6. Code Along – Assigning Labels 00:03:13
   7. Code Along – Putting It All Together 00:18:08
   8. Code Along – Include Support Features from Other Tickers 00:06:34
8. ENGINEERING A COMPLEX FEATURE – A CATEGORICAL VARIABLE WITH PAST TRENDS
   1. Engineering a Categorical Variable 00:03:49
   2. Code Along – Engineering a Categorical Variable 00:06:47
9. BUILDING A MACHINE LEARNING CLASSIFIER IN PYTHON
   1. Introducing Scikit-Learn 00:03:33
   2. Introducing RandomForestClassifier 00:09:26
   3. Training and Testing a Machine Learning Classifier 00:15:01
   4. Compare Results from Different Strategies 00:05:45
   5. Using Class Probabilities for Predictions 00:03:11
10. NEAREST NEIGHBORS CLASSIFIER
    1. A Nearest Neighbors Classifier 00:06:50
    2. Code Along – A Nearest Neighbors Classifier 00:04:16
11. GRADIENT BOOSTED TREES
    1. What are Gradient Boosted Trees 00:12:38
    2. Introducing XGBoost – A Python Library for GBT 00:11:51
    3. Code Along – Parameter Tuning for Gradient Boosted Classifiers 00:09:21
12. INTRODUCTION TO QUANT TRADING
    1. Financial Markets – Who Are the Players 00:16:38
    2. What is a Stock Market Index 00:03:14
    3. The Mechanics of Trading – Long Vs Short Positions 00:11:56
    4. Futures Contracts 00:14:26

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