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Quant Trading – Machine Learning
Description of Machine Learning
Play the Markets Like a Pro by Integrating Machine Learning into Your Investment Strategies! This online training course takes a completely practical approach to applying Machine Learning techniques to Quant Trading. The focus is on practically applying Machine Learning techniques to develop sophisticated Quant Trading models. From setting up your own historical price database in MySQL, to writing hundreds of lines of Python code, the focus is on doing from the get-go.
Financial markets are fickle beasts that can be extremely difficult to navigate for the average investor. This Quant Trading Using Machine Learning course will introduce you to machine learning, a field of study that gives computers the ability to learn without being explicitly programmed, while teaching you how to apply these techniques to quantitative trading. Using Python libraries, you will discover how to build sophisticated financial models that will better inform your investing decisions. Supplemental Material included!
What will you learn in Machine Learning?
INTRODUCTION

You, This Course, and Us!

DEVELOPING TRADING STRATEGIES IN EXCEL

Are markets efficient or inefficient?
Momentum Investing
Mean Reversion
Evaluating Trading Strategies – Risk and Return
Evaluating Trading Strategies – The Sharpe Ratio
The 2 Step process – Modeling and Backtesting
Developing a Trading Strategy in Excel

SETTING UP YOUR DEVELOPMENT ENVIRONMENT

Installing Anaconda for Python
Installing Pycharm – a Python IDE
MySQL Introduced and Installed – Mac OS X
MySQL Server Configuration and MySQL Workbench – Mac OS X
MySQL Installation – Windows
For Linux-Mac OS Shell Newbies – Path and Other Environment Variables

SETTING UP A PRICE DATABASE

Programmatically Downloading Historical Price Data
Code Along – Downloading Price Data from Yahoo Finance
Code Along – Downloading a URL in Python
Code Along – Downloading Price Data from the NSE
Code Along – Unzip and Process the Downloaded Files
Manually download data for 10 years
Code Along – Download Historical Data for 10 years
Inserting the Downloaded Files into a Database
Code Along – Bulk Loading Downloaded Files into MySQL Tables
Data Preparation
Code Along – Data Preparation
Adjusting for Corporate Actions
Code Along – Adjusting for Corporate Actions 1
Code Along – Adjusting for Corporate Actions 2
Code Along – Inserting Index Prices into MySQL
Code Along – Constructing a Calendar Features Table in MySQL

DECISION TREES, ENSEMBLE LEARNING AND RANDOM FORESTS

Planting the seed – What are Decision Trees
Growing the Tree – Decision Tree Learning
Branching out – Information Gain
Decision Tree Algorithms
Overfitting – The Bane of Machine Learning
Overfitting Continued
Cross-Validation
Regularization
The Wisdom of Crowds – Ensemble Learning
Ensemble Learning continued – Bagging, Boosting and Stacking
Random Forests – Much More Than Trees

A TRADING STRATEGY AS MACHINE LEARNING CLASSIFICATION

Defining the Problem – Machine Learning Classification

FEATURE ENGINEERING

Know the basics – A Pandas tutorial
Code Along – Fetching Data from MySQL
Code Along – Constructing Some Simple Features
Code Along – Constructing a Momentum Feature
Code Along – Constructing a Jump Feature
Code Along – Assigning Labels
Code Along – Putting It All Together
Code Along – Include Support Features from Other Tickers

ENGINEERING A COMPLEX FEATURE – A CATEGORICAL VARIABLE WITH PAST TRENDS

Engineering a Categorical Variable
Code Along – Engineering a Categorical Variable

BUILDING A MACHINE LEARNING CLASSIFIER IN PYTHON

Introducing Scikit-Learn
Introducing RandomForestClassifier
Training and Testing a Machine Learning Classifier
Compare Results from Different Strategies
Using Class Probabilities for Predictions

NEAREST NEIGHBORS CLASSIFIER

A Nearest Neighbors Classifier
Code Along – A Nearest Neighbors Classifier

GRADIENT BOOSTED TREES

What are Gradient Boosted Trees
Introducing XGBoost – A Python Library for GBT
Code Along – Parameter Tuning for Gradient Boosted Classifiers

INTRODUCTION TO QUANT TRADING

Financial Markets – Who Are the Players
What is a Stock Market Index
The Mechanics of Trading – Long Vs Short Positions
Futures Contracts