312.170 (18W) Financial Data Analysis

Wintersemester 2018/19

No registration period specified.

First course session
04.10.2018 12:15 - 13:45 HS 10 On Campus
... no further dates known

Overview

Lecturer
Course title german Financial Data Analysis
Type Lecture
Hours per Week 2.0
ECTS credits 4.0
Registrations 3
Organisational unit
Language of instruction English
Course begins on 04.10.2018

Time and place

List of events is loading...

Course Information

Intended learning outcomes

􏰀 The students should be able to analyse, whether a dataset of financial returns comes from Gaussian random variables.

The students should have a basic knowledge on risk measures.

The students should know the most common model used for financial time series.

􏰀 The students should understand several applications of extreme value theory in finance and insurance.

􏰀 The students should be able to work with multivariate models and how to deal with dependence.􏰀

The students should be able to fit a price process model to data.

The students should be able to simulate price processes and understand the basic concepts of Monte Carlo simulation.

Teaching methodology including the use of eLearning tools

Lecture with practical examples
Combination of slides and blackboard

Course content

􏰀 Return distribution
􏰀 Risk measures
 Financial time series
􏰀 Extreme value theory
􏰀 Multivariante models and dependence􏰀
Model calibration
Stochastic simulation methods

Prior knowledge expected

Knowledge on stochastics and stochastic processes.

Literature

A. J. McNeil, R. Frey, P. Embrechts.
Quantitative Risk Management.
Publisher: Princeton Series in Finance.

R. Carmona
Statistical Analysis of Financial Data in R.
Publisher: Springer.

P. Glassermann.
Monte Carlo Methods in Financial Engineering.
Publisher: Springer.

Examination information

Im Fall von online durchgeführten Prüfungen sind die Standards zu beachten, die die technischen Geräte der Studierenden erfüllen müssen, um an diesen Prüfungen teilnehmen zu können.

Examination methodology

There will be a final exam, presumably at the end of January.
The point scheme is as follows:
100-87 p. -> 1
86-75 p. -> 2
74-62 p. -> 3
61-50 p. -> 4
49-0 p. -> 5

Examination topic(s)

Everything that is covered in the lecture.
If additional reading is required for the lecture, this will be clearly announced in the lecture.

Assessment criteria / Standards of assessment for examinations

The mark depends only on the number of points the student achieves at the final exam.

Grading scheme

Grade / Grade grading scheme

Position in the curriculum

  • Thematic Doctoral Programme Modeling-Analysis-Optimization of discrete, continuous and stochastic systems (SKZ: ---, Version: 16W.1)
    • Subject: Modeling-Analysis-Optimization of discrete, continuous and stochastic systems (Compulsory subject)
      • Modeling-Analysis - Optimization of discrete, continuous and stochastic systems ( 0.0h XX / 0.0 ECTS)
        • 312.170 Financial Data Analysis (2.0h VO / 4.0 ECTS)
  • Masterstudium Mathematics (SKZ: 401, Version: 18W.1)
    • Subject: Applied Statistics (Compulsory elective)
      • 5.3 Financial Data Analysis ( 2.0h VO / 4.0 ECTS)
        • 312.170 Financial Data Analysis (2.0h VO / 4.0 ECTS)
  • Masterstudium Mathematics (SKZ: 401, Version: 18W.1)
    • Subject: Applied Mathematics (Compulsory elective)
      • Lehrveranstaltungen aus den Vertiefungsfächern ( 0.0h XX / 12.0 ECTS)
        • 312.170 Financial Data Analysis (2.0h VO / 4.0 ECTS)
  • Master's degree programme Technical Mathematics (SKZ: 401, Version: 13W.1)
    • Subject: Statistik (Compulsory subject)
      • Finanzstatistik ( 3.0h VU / 5.0 ECTS)
        • 312.170 Financial Data Analysis (2.0h VO / 4.0 ECTS)
  • Doctoral programme Doctoral programme in Technical Sciences (SKZ: 786, Version: 12W.4)
    • Subject: Studienleistungen gem. § 3 Abs. 2a des Curriculums (Compulsory subject)
      • Studienleistungen gem. § 3 Abs. 2a des Curriculums ( 16.0h XX / 32.0 ECTS)
        • 312.170 Financial Data Analysis (2.0h VO / 4.0 ECTS)

Equivalent courses for counting the examination attempts

This course is not assigned to a sequence of equivalent courses