312.170 (18W) Financial Data Analysis
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
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
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 schemePosition 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)
-
Modeling-Analysis - Optimization of discrete, continuous and stochastic systems (
0.0h XX / 0.0 ECTS)
-
Subject: Modeling-Analysis-Optimization of discrete, continuous and stochastic systems
(Compulsory subject)
- 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)
-
5.3 Financial Data Analysis (
2.0h VO / 4.0 ECTS)
-
Subject: Applied Statistics
(Compulsory elective)
- 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)
-
Lehrveranstaltungen aus den Vertiefungsfächern (
0.0h XX / 12.0 ECTS)
-
Subject: Applied Mathematics
(Compulsory elective)
- 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)
-
Finanzstatistik (
3.0h VU / 5.0 ECTS)
-
Subject: Statistik
(Compulsory subject)
- 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)
-
Studienleistungen gem. § 3 Abs. 2a des Curriculums (
16.0h XX / 32.0 ECTS)
-
Subject: Studienleistungen gem. § 3 Abs. 2a des Curriculums
(Compulsory subject)