Lehrangebot

Master-Theses in Financial Econometrics and Financial and Economic Data Science, SS 2023

Subareas and details

1. Subarea I: Basic time series econometrics

I.a) Parametric, semi-parametric models for economic, financial or environmental time and their applications. Forecasting economic, financial or environmental time using semiparametric ARMA models possibly with seasonal component (topics based on M.184.4451 and Chapter 2 of W5453, the main package for this subarea is "smoots", x12, DeSeaTS)

I.b) Forecasting economic, financial or environmental time using semiparametric long-memory time series models (see M.184.5453, Ch3, coming, R package is "esemifar")

2. Subarea II: Advanced Financial Econometrics

II.a) Modeling of high-frequency financial data (see Chapter 5 of M.184.5453)

II.b) Parametric and semiparametric long memory GARCH models and their application in quantitative risk management (see Chapter 6 of M.184.5453)

II.c) Parametric and semiparametric multivariate GARCH models and their application in quantitative risk management (see Chapter 7 of M.184.5453)

3. Subarea III: Deep Learning with application to Financial and Economic Data:

a. Combination of deep learning with shortmemory (SM) GARCH models

b. Combination of deep learning with semiparametric GARCH models

c. Combination of deep learning with longmemory (LM) GARCH models

d. Combination of machine learning with semiparametric (LM) GARCH models

e. Deep learning with application to economic, business or environmental data.

Remark 1. The prerequisite for writing a Master Thesis at our Chair is that you have visited M.184.5451. If you still not yet have visited it but are going to visit this module in SS 2023, please indicate that you have visited W5333. This will be considered as an alternative to W5451.

Remark 3. Topics Subarea II are suitable for those who are visiting the advanced time series module M.184.5453. If you are going to choose topics from Subarea III, the prerequisite is M.184.5452. You can also learn those topics yourselves.

Remark 3. Topics with BWL-focuses, e.g. studies on the behaviors of important German firms on the financial market, can be provided,

Master-Theses in Financial Econometrics and Financial and Economic Data Science, WS 2023/24

Subareas and details

1. Subarea I: Basic time series econometrics

I.a) Parametric, semi-parametric models for economic, financial or environmental time and their applications. Forecasting economic, financial or environmental time using semiparametric ARMA models possibly with seasonal component (topics based on M.184.4451 and Chapter 2 of W5453, the main package for this subarea is "smoots", x12, DeSeaTS)

I.b) Forecasting economic, financial or environmental time using semiparametric long-memory time series models (see M.184.5453, Ch3, coming, R package is "esemifar")

2. Subarea II: Advanced Financial Econometrics

II.a) Modeling of high-frequency financial data (see Chapter 5 of M.184.5453)

II.b) Parametric and semiparametric long memory GARCH models and their application in quantitative risk management (see Chapter 6 of M.184.5453)

II.c) Parametric and semiparametric multivariate GARCH models and their application in quantitative risk management (see Chapter 7 of M.184.5453)

II.d) Application of some most recently proposed long memory volatility models

II.e) Stationery and trend-stationary dual long memory processes in finance and economics

3. Subarea III: Deep Learning with application to Financial and Economic Data:

a. Combination of deep learning with short-memory (SM) GARCH models

b. Combination of deep learning with semiparametric (SM) GARCH models

c. Combination of deep learning with long-memory (LM) GARCH models

d. Combination of machine learning with semiparametric (LM) GARCH models

e. Deep learning with application to economic, business or environmental data.

Remark 1. The prerequisite for writing a Master Thesis at our Chair is that you have at least visited one of M.184.4451, M.184.5451 (or equivalently M.184.5333 by Prof. Dr. Oliver Müller), M.184.5452 or M.184.5453. If you still not yet have visited one of those modules, but are visiting M.184.4451 or M.184.5452 just now, please indicate this in your application for the allocation of your Master thesis on the central allocation system.

Remark 3. Topics Subarea II are suitable for those who are visiting the advanced time series module M.184.5453. If you are going to choose topics from Subarea III, the prerequisite is M.184.5452. You can also learn those topics yourselves.

Remark 3. Topics with BWL-focuses, e.g. studies on the behaviors of important German firms on the financial market, can be provided,

Remark 4. The choice of further advanced Econometric/Data Science topics, e.g. those in reinforcement learning or modeling of spatial data, is encouraged, provided that you have the previous knowledge on those topics. If this is your case, please discuss it with me in advance.