Syllabus

Titel
5195 Y2E Financial Engineering
LV-Leiter/innen
Assoz.Prof. PD Dr. Zehra Eksi-Altay, BSc.MSc.
Kontakt
  • LV-Typ
    PI
  • Semesterstunden
    2
  • Unterrichtssprache
    Englisch
Anmeldung
07.02.2019 bis 24.02.2019
Anmeldung über LPIS
Hinweise zur LV
Planpunkt(e) Master
Termine
Wochentag Datum Uhrzeit Raum
Dienstag 05.03.2019 09:00 - 13:00 D4.0.127
Dienstag 12.03.2019 09:00 - 13:00 D4.0.127
Dienstag 19.03.2019 09:00 - 13:00 D4.0.127
Dienstag 26.03.2019 09:00 - 13:00 TC.4.01
Dienstag 02.04.2019 09:00 - 13:00 D4.0.127
Dienstag 09.04.2019 09:00 - 13:00 D4.0.127
Dienstag 30.04.2019 09:00 - 11:00 TC.5.15

Inhalte der LV

During this course students will become acquainted with the essential techniques and tools for financial engineering.  In particular, at the end of this course, students are expected to gain knowledge in:

  • principles of Monte Carlo simulation;
  • simulation of  stochastic processes;
  • variance reduction techniques;
  • applications in derivative pricing and term-structure modelling;
  • applications in risk management.

Lernergebnisse (Learning Outcomes)

After completing this course the student will have the ability to:

  • price derivatives using Monte Carlo techniques;
  • apply variance reduction techniques ;
  • simulate Brownian paths and SDEs;
  • price exotic options by means of Monte Carlo simulation;
  • construct a yield curve;
  • perform basic risk analysis (V@R, ES, etc ).

Regelung zur Anwesenheit

Full attendance is mandatory. This means that students should attend at least 80% of all lectures ( at most one out of seven sessions  can be missed).

Lehr-/Lerndesign

This course is mainly taught using a combination of (i) lectures elaborating relevant topics and (ii) examples (exercises) illustrating and deepening various aspects of a certain topic. The lectures are aimed at providing the core information about the principles of financial engineering. The examples should give students the opportunity to apply theoretical knowledge to practical problems and help to comprehend the key ideas of the lecture.  Regular homework assignments will help students to consolidate and expand their knowledge and understanding by developing solutions to applied problems.

Leistung(en) für eine Beurteilung

  • 60% Two written exams
  • 30% Homework assignment:

Homework assignments consist of  practical problems to be solved on the computer.  Students will be asked to  present their results shortly. Assignments can be worked out in teams. The assessment of  homework assignments will be based on the correctness of the results, the clarity of the work and the recognizable effort made. The late homework assignments will be penalized severely. 

  • 10% Class participation

50% must be achieved in total to successfully pass the course.

Teilnahmevoraussetzung(en) und Vergabe von Wartelistenplätzen

Fulfillment of the specific requirements for admission to courses and examinations defined in the curriculum.

    Literatur

    1 Autor/in: Paul Glasserman
    Titel: Monte Carlo Methods in Financial Engineering

    Verlag: Springer
    Auflage: 1st
    Jahr: 2004
    Empfehlung: Stark empfohlen (aber nicht absolute Kaufnotwendigkeit)
    Art: Buch
    2 Autor/in: R. Seydel
    Titel: Tools for Computational Finance

    Verlag: Springer
    Empfehlung: Stark empfohlen (aber nicht absolute Kaufnotwendigkeit)
    Art: Buch
    3 Autor/in: Paolo Brandimarte
    Titel:

    Handbook in Monte Carlo Simulation: Applications in Financial Engineering, Risk
    Management, and Economics.


    Verlag: Wiley
    Jahr: 2014
    Empfehlung: Stark empfohlen (aber nicht absolute Kaufnotwendigkeit)
    Art: Buch
    4 Autor/in: Damiano Brigo and Fabio Mercurio
    Titel:

    Interest rate models-theory and practice: with smile, inflation and credit.


    Verlag: Springer Science & Business Media
    Jahr: 2007
    Empfehlung: Stark empfohlen (aber nicht absolute Kaufnotwendigkeit)
    Art: Buch
    5 Autor/in: Damir Filipovic
    Titel:

    Term Structure Models


    Verlag: Springer
    Auflage: first
    Jahr: 2009
    Art: Buch

    Empfohlene inhaltliche Vorkenntnisse

    • Basic knowledge in linear algebra
    • Basic knowledge in analysis
    • Knowledge in stochastics
    • Basic knowledge in finance
    • Knowledge of a programming language

    Erreichbarkeit des/der Vortragenden

    zehra.eksi@wu.ac.at

    Sonstiges

    • Slides will be made available online.
    Zuletzt bearbeitet: 19.02.2019



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