MySchool

Department of Engineering
Dean:	Dr. Ármann Gylfason
Email:	ru@ru.is
Website:	http://www.ru.is/tvd
Teachers	View

MSc in Financial Engineering
Semesters:	4
Years:	2
ETCS:	120
About major	Fjármálaverkfræði er þverfagleg grein sem samþættir fjármálafræði við verkfræðilegar aðferðir, stærðfræðileg líkön, tölfræði, aðgerðagreiningu og hagnýta tölvunarfræði. Nám í fjármálaverkfræði hentar þeim sem hafa áhuga á t.d. áhættustýringu, afleiðuviðskiptum eða fjárstýringu. MSc námið er mótað að kröfum Verkfræðingafélags Íslands um fullnaðarmenntun í verkfræði.
Learning Outcomes	View
Education cycle	2

Legend
	Mandatory course on major		Teaching language
	Optional course on major		Prerequisites for course

Vorönn/Spring 2024

Energy Financial Assessment

SE-833-FA2

ECTS 6

Engineering Optimization

T-423-ENOP

ECTS 6

Sleep

T-424-SLEE

ECTS 6

Decision Analysis for Management

T-603-AKVA

ECTS 6

Internship in Engineering I

T-706-INT1

ECTS 6

Internship in Engineering II

T-706-INT2

ECTS 6

Systems Biology

T-765-SYBI

ECTS 8

Project Management and Strategic Planning

T-803-VERK

ECTS 8

Derivatives and risk management

T-814-DERI

ECTS 8

Creating a Complete Business Plan for a Technical Idea - Entrepreneurship and the Innovation Process

T-814-INNO

ECTS 8

Modern Trends in Financial Engineering

T-816-MTFE

ECTS 8

Tissue Engineering and Biomaterials

T-828-TISS

ECTS 8

Graduate Research Opportunities I

T-829-GRO1

ECTS 6

Finite Element Analysis in Engineering

T-844-FEMM

ECTS 8

Neural Engineering

T-863-NEUR

ECTS 8

Wind Power

T-863-WIND

ECTS 8

Power System Operation

T-867-POSY

ECTS 8

Stability and Control in Electric Power Systems

T-867-STAB

ECTS 8

Protection Philosophy for Smart-Grids

T-868-PROT

ECTS 8

MSc Thesis

T-899-MEIS

ECTS 30

MSc Thesis

T-900-MEIS

ECTS 30

MSc thesis II

T-901-MEI2

ECTS 30

Business Process Management

V-716-BPMA

ECTS 7,5

Entrepreneurial Finance

V-733-ENTR

ECTS 7,5

Business Intelligence and Analytics

V-784-REK5

ECTS 7,5

Entrepreneurship and Starting New Ventures

X-204-STOF

ECTS 6

Exchange Studies

X-699-EXCH

ECTS 30

Sumar/Summer 2024

Graduate Research Opportunities I

T-829-GRO1

ECTS 6

Exchange Studies

X-699-EXCH

ECTS 30

Haustönn/Fall 2024

Special Topics in Energy I

SE-801-STE

ECTS 1

Energy Economics

SE-805-EC1

ECTS 6

Special Topics in Energy III

SE-806-STE

ECTS 6

Embedded System Programming

T-738-EMBE

ECTS 8

Simulation II

T-806-SIMU

ECTS 6

Quality Management

T-807-QUAL

ECTS 6

Applying Models in Management

T-808-NOLI

ECTS 8

Data Mining and Machine Learning

T-809-DATA

ECTS 8

Optimization Methods

T-810-OPTI

ECTS 8

Applied Probability

T-811-PROB

ECTS 8

Year

1. year

Semester

Fall 2024

Level of course

4. Second cycle, introductory

Type of course

Elective

Prerequisites

T-606-PROB, Probability and Stochastic Processes

Schedule

No schedule found.

Lecturer

No lecturer found.

Content

This course will start by recalling some basic concepts in probability theory. Important discrete and continuous probability distributions will be introduced and applied to concrete problems. The concepts of expectations, variances and covariances will be introduced and applied to selected problems. The importance of the theorem of large numbers, central limit theorem and the consequences of these will be introduced. Markov chains will be discussed as well as Poisson and death – birth processes with several applications, including queueing theory. Basic stochastic processes such as Brownian motion and Wiener processes and their important role in the modelling and management of uncertainty will be discussed. Throughout the course examples and applications to various practical problems will be considered.

Learning outcome - Objectives

This course will cover some important topics in probability theory with particular emphasis on their application to practical problems. At the end of the course the student will have an appreciation of the important role probability plays in various areas of engineering and be able to apply it to a range of concrete realworld problems. This learning outcome can be broken down into the following sub outcomes:
• Understand the basic concepts of probability distributions and their role in the modelling of uncertain outcomes – both in the discrete and the continuous case • Use expectation, variance and covariance to model various probabilistic phenomena
• Apply conditional probabilities and Bayes’s formula to events in the presence of partial information
• Understand jointly distributed random variables and functions of random variables
• Understand the theoretical basis of moment generating functions and their application to the construction of probability distribution functions
• Understand the theoretical basis of the limit theorems, the law of large numbers and important inequalities
• Understand the role of probability in Reliability applications
• Understand Poisson processes, birth and death processes and Markov processes and their roles in the modelling of queues
• Understand different types of queues and their classification
• Be able to estimate the performance of different queueing systems in terms of quantities such as, queue length, expected waiting time or the probability of system blockage
• Understand the role of stochastic processes in financial applications

Course assessment

Student led recitations and assignments; Class exams; Final exam.

Reading material

No reading material found.

Teaching and learning activities

Interactive lectures, projects and class exams.

Language of instruction

English

Financial Engineering of the Firm

T-814-FINA

ECTS 8

Managing Research and Development - Methods and Models