CS7646 Summer 2017 ATL

Overview

This summer, the course will follow this broad outline:

1. Brief introduction to Manipulating Financial Data in Python
2. Introduction to Machine Learning
3. Computational Investing
4. Machine Learning Algorithms for Trading

Instructor information

David Byrd
Research Scientist, Interactive Media Technology Center at Georgia Tech

2017 Summer Schedule

Class meets MW 12:30 - 2:20 in Klaus 1456

2017 Summer Schedule

This schedule is tentative and subject to change due to the compressed summer timeline. I am not certain exactly how quickly we will progress through the material.

The first exam will be given in week 6 or 7 depending on our progress. I will nail it down early in the class.

The second exam will be given on the final day of regular class in week 10.

Week	Topic	Due
1	Course Overview, Intro to Markets, Intro to Machine Learning, Pandas Tutorial
2	Visualizing Market Data, Pricing Stocks, Numpy Tutorial, Working with Time Series
3	Incomplete Data, Plots, ML Lexicon/Taxonomy, Evaluating Learners
4	Supervised Learning (KNN, LinReg, Decision Trees, Boosting, Bagging)
5	Market History, Actors, Order Book, Order Types
6	Markets, Valuation, Capitalization, Time Value of Money
7	Options, Leverage
8	Technical Analysis, Candlestick Chart Patterns, CAPM, Efficient Market Hypothesis
9	Fund. Law of APM, Efficient Frontier, Finite Automata, Markov Decision Processes
10	Value Iteration, Q-Learning

Assignments

This is a project-heavy class. There will be 5 projects this semester, due roughly every two weeks. Note that there are two non-cumulative exams during the semester. The final project in the class (and the most complex) will be due during the final exam period, in lieu of a final exam.

Assignment details will be added here.

Office hours

David Byrd (Instructor), TBD

TAs TBD