** » Master Thesis Supervision (Financial Econometrics) ** (2017, 2018)

** » Computational Finance using Python ** (MIF – 2018)

__Reading material:__

○ Hilpisch (2014) *"Python for Finance"*

○ Hull (2012) *"Options, Futures and Other Derivatives"*

** » Mathematical and Empirical Finance ** (B.Sc. Econometrics – 2017)

__Reading material:__

○ Luenberger (2013) *"Investment Science"*

** » Financial Econometrics ** (M.Sc. Econometrics & M.Sc. Actuarial Science/Mathematical Finance – 2018)

__Reading material:__

○ Tsay (2010) *"Analysis of Financial Time Series"*

** » Bachelor Thesis Supervision (Finance) ** (2013, 2014, 2015)

** » Financial Analysis and Investor Behavior ** (M.Sc. Finance (CFA track) – 2014, 2015, 2016)

* Reading material:* Selection of research papers, e.g.,

○ Black and Litterman (1991) *"Asset Allocation: Combining Investor Views with Market Equilibrium"*

○ Brandt, Santa-Clara, and Valkanov (2009) *"Parametric Portfolio Policies: Exploiting Characteristics in the Cross Section of Equity Returns"*

** » Information Economics ** (Research Master Course – 2014, 2015, 2016, 2017)

Awarded as the ** Best Teaching Assistant** in the CentER Graduate Program (Business) in 2016-2017

__Reading material:__

○ Mas Colell, Whinston, and Green (1995) *"Microeconomic Theory"*

○ Bolton and Dewatripont (2005) *"Contract Theory"*

** » Empirical Methods in Finance ** (M.Sc. Finance – 2013, 2014, 2015, 2016, 2017, 2018)

* Reading material:* ;

○ Verbeek (2008) *"A Guide to Modern Econometrics"*

○ Brooks (2014) *"Introductory Econometrics for Finance"*

Please find all `.do`-files and data sets on the Tilburg University Blackboard.

Lecture 1.1 – Getting started with Stata (11:58)

* This video covers:* the Stata GUI, Stata's command syntax (explained using the command summarize), opening the

Lecture 1.2 – Getting started with Stata (13:30)

* This video covers:* working in the

Lecture 2.1 – Managing and editing data (18:25)

* This video covers:* Importing data into Stata (here: a .xls file), inspecting your dataset (e.g., describe, or simple line graphs), editing your dataset (e.g., labelling, generating variables), Stata's operators and functions in the context of generating variables, Stata's system variables (

Lecture 2.2 – Managing and editing data (14:11)

* This video covers:* the

Lecture 2.3 – Managing and editing data (17:28)

* This video covers:* generating variables using the

Lecture 3.1 – Regression analysis (19:31)

* This video covers:* loading a Stata dataset, time-setting your data (here: time-series data), understanding the CAPM as a regression model, using the regress command, interpreting a regression output

Lecture 3.2 – Regression analysis (18:38)

* This video covers:* installing user-written packages (here:

Lecture 3.3 – Regression analysis (23:08)

* This video covers:* visual inspection of the CAPM (using a

Lecture 3.4 – Regression analysis (07:11)

* This video covers:* running multiple regression analysis (here: the Carhart four-factor model), using local macros as a tool to store variable lists, interpreting a multiple regression output

Lecture 4.1 – Panel data techniques (07:11)

* This video covers:* Loading a panel data set (here: a .xls file) and xtsetting the data, using “xt” panel commands, editing your dataset (e.g., labelling, generating variables), generating variables using the

Lecture 4.2 – Panel data techniques (24:36)

* This video covers:* Executing pooled-OLS regression analysis, using cluster-robust standard errors, using robust regression analysis (using

Lecture 4.3 – Panel data techniques (22:30)

* This video covers:* Predicting the estimated fixed-effects, using the

Lecture 5.1 – Times-series analysis (24:57)

* This video covers:* Working with Stata's date function (transforming a string date variable to a numeric date variable), using

Lecture 5.2 – Times-series analysis (28:18)

* This video covers:* Working with Stata's time-series operators (

Lecture 5.3 – Times-series analysis (12:46)

* This video covers:* Static and dynamic point-forecasting with Stata using the

__Additional reading material (related to Stata):__

○ Cameron and Trivedi (2010) *"Microeconometrics using Stata"*

○ Baum (2006) *"An Introduction to Modern Econometrics Using Stata"*

○ Baum (2009) *"An Introduction to Stata Programming"*