Type of studies | Title |
---|---|
Master Academic Studies | Information and Analytics Engineering (Year: 1, Semester: Summer) |
Master Academic Studies | Information Engineering (Year: 1, Semester: Summer) |
Category | Professional-applicative |
Scientific or art field |
|
ECTS | 4 |
Algorithmic objectives of trade are to introduce students to the key factors that determine the algorithmic models of trade and understand the basic concepts of defining automated systems The financial trade market. The main objective of this course is to complement and integrate knowledge of systems engineers need algorithmic trade management.
Students who live audience of the course and pass the exam are qualified to understand the methods of analysis and decision-making when creating models of algorithmic trading and to make decisions about the use of algorithmic trade in business.
"Dow Theory," Moving averages and their significance, leading indicators in algorithmic trading, following indicators in algorithmic trading, the role of trade volume, formation algorithms, neural networks, genetic algorithms, transaction costs, the use of algorithms to arbitration, contemporary experience in the application of algorithmic models trade in the market.
Lectures, exercises and workshops. The exam is taken in two parts. The first part of the exam students take a team addressing or resolving the case study written test with multiple choice. Students who have passed the first part of the exam are allowed to take the oral part of the exam. The oral exam is taken orally and is eliminatory.
Authors | Title | Year | Publisher | Language |
---|---|---|---|---|
2005 | English | |||
2010 | English |
Course activity | Pre-examination | Obligations | Number of points |
---|---|---|---|
Exercise attendance | Yes | Yes | 5.00 |
Project | Yes | Yes | 40.00 |
Oral part of the exam | No | Yes | 50.00 |
Lecture attendance | Yes | Yes | 5.00 |
Full Professor
Assistant Professor
Assistant - Master
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