MySchool

Verkfræðideild
Deildarforseti:	Dr. Ármann Gylfason
Vefpóstur:	ru@ru.is
Vefsíða:	http://www.ru.is/tvd
Kennarar	Skoða

MSc í fjármálaverkfræði
Annir:	4
Ár:	2
Einingar:	120
Um námsleiðina	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.
Hæfniviðmið	Skoða
Námsstig	2

Táknmyndir
	Skyldufag á braut		Kennslutungumál
	Valfag á braut		Undanfarar fyrir námskeið

Vorönn/Spring 2024

Energy Financial Assessment

SE-833-FA2

6 Einingar

Verkfræðilegar bestunaraðferðir

T-423-ENOP

6 Einingar

Svefn

T-424-SLEE

6 Einingar

Ákvarðanatökuaðferðir

T-603-AKVA

6 Einingar

Starfsnám í verkfræði I

T-706-INT1

6 Einingar

Starfsnám í verkfræði II

T-706-INT2

6 Einingar

Systems Biology

T-765-SYBI

8 Einingar

Verkefnastjórnun og stefnumarkandi áætlunargerð

T-803-VERK

8 Einingar

Afleiður og áhættustýring

T-814-DERI

8 Einingar

Ár

1. ár

Önn

Vorönn/Spring 2024

Stig námsgreinar

5. Framhaldsnám, framhaldsnámskeið

Tegund námskeiðs

Skylda

Undanfarar

Engir undanfarar.

Skipulag

Kennt í 12 vikur.

Kennari

Ralph Rudd

Lýsing

Year of study: 4th year (1st year MSc).Semester: Spring.
Level of course: 6. Second cycle, advanced.Type of course: Core for MSc Financial Engineering, elective for other programs.Prerequisites: Appropriate undergraduate degree.Probability and Stochastic Processes (T-606-PROB)Derivatives (T-503-AFLE)Applied Probability (T-811-PROB)Other recommended prerequisites: Risk Management (T-602-RISK)Data Mining and Machine Learning (T-809-DATA)Financial Engineering of the Firm (T-814-FINA)Schedule: 12 weeks of 2 x 2.5-hour (3-period) lectures per week.Supervisor: Ralph Rudd.Lecturer: Ralph Rudd.The core focus of this course is study and use of quantitative techniques in risk management.The approach is centered around the study of portfolio value change, where we consider general portfolios that can consist of a mixture of equity, fixed income, credit, and derivative instruments.
The risk of a portfolio is represented by its loss distribution, which is a function of its risk factors. In this course we examine how to model and manipulate this loss distribution. The modelling proceeds via modelling the risk factors themselves, and we investigate the properties of common risk factors in the real world. The manipulation of the loss distribution is done by modifying the portfolio constituents, usually through hedging.
To assess the risk of a portfolio, we look at summary measures of its loss distribution, primarily value-at-risk and expected shortfall. We examine the properties of these risk measures and investigate their shortcomings.

Námsmarkmið

Learning Outcomes: After completing this course, students will have a good knowledge of how to identify, quantify and manage derivative and market risk. The learning outcome can be broken down into the following sub-outcomes:

Be able to define and explain the fundamental concepts used in the measurement and management of financial risk.
Be able to analyse and model changes in portfolio value and derive loss distributions.
Apply the loss distribution framework to different kinds of asset and liability portfolios.
Apply different quantitative approaches to measuring risk, with particular focus on risk measures that are calculated from loss distributions, like value-at-risk and expected shortfall.
Be able to build realistic models for risk management purposes by considering the empirical properties of fundamental risk factors and developing models that share these properties.
To model multivariate loss distributions with complex cross-dependencies.
Be able to aggregate and disaggregate risk across multi-instrument portfolios.

Námsmat

Lesefni

Ekkert skráð lesefni.

Kennsluaðferðir

Tungumál

Enska

Gerð viðskiptaáætlunar fyrir tæknilega hugmynd - Frumkvöðlafræði og nýsköpun

T-814-INNO

8 Einingar

Nýjar stefnur í fjármálaverkfræði

T-816-MTFE

8 Einingar