School of Engineering \ Artificial Intelligence Engineering
Course Credit
ECTS Credit
Course Type
Instructional Language
Programs that can take the course
Artificial Intelligence Engineering Undergraduate Program
Introduction to Financial Markets & Financial Instruments. Fundamentals of Financial Derivatives including Options, Forward Contracts, etc. Time Series Analysis, regression models, ARIMA, GARCH models. Technical Analysis of Financial Data. Financial Engineering. Trading/Investment Strategies. Portfolio allocation. Pairs Trading and other strategies. Introduction to Algorithmic Trading. Overview of Computational Intelligence techniques. Development and execution of algorithms and computational intelligence in financial decision making.
Textbook and / or References
SUNY Computational Finance Lecture Notes, http://www.cs.sunysb.edu/~skiena/691/
The aim of this course is to learn about how computational intelligence techniques are used in financial applications
1. Learn about financial markets and financial instruments
2. Learn about how to use computational intelligence models in finance
3. Learn about financial trading models and trading strategies
Week 1: Introduction, definitions, examples
Week 2: Fundamentals of Financial Derivatives
Week 3: Option strategies
Week 4: Option pricing with Binomial and Black Scholes models
Week 5: Time series analysis
Week 6: Regression, GARCH, ARIMA models
Week 7: Introduction to Technical Analysis
Week 8: Computational Intelligence Basics (ANN, GA, etc.)
Week 9: Introduction to Algorithmic Trading
Week 10: Portfolio allocation, Pairs Trading and other strategies
Week 11: Development and execution of algorithms and computational intelligence in financial decision making
Week 12: Student presentations
Tentative Assesment Methods
• Midterm Exams 25 %
• Final 30 %
• Homework 15 %
• Project 30 %
|
Program Outcome
*
|
| 1 |
2 |
3 |
4 |
5 |
6 |
7 |
8 |
9 |
10 |
11 |
|
Course Outcome
|
|---|
| 1 |
|
|
|
|
|
|
|
|
|
|
|
| 2 |
|
|
|
|
|
|
|
|
|
|
|
| 3 |
|
|
|
|
|
|
|
|
|
|
|