Empirical Finance

Here are the exercises from Chapter 3 and 4 together with their solutions.

Summary of the 1st lecture, week 1. It includes explanations of the Dummy variables and interactions, visualisation of interaction effects, R-squared, Adjusted R-Square, Multicollinearity, interpretation of the entire Stata table, interpretation of the sign of the coefficients, p-values, t-values, and standard errors, Root MSE, and the F-test. This summary helps you go through material without watching again the lengthy web-lectures. I practically wrote down everything what he said. It helps al...

The codes written during the matlab tutorial with a step by step explanation of what we are programming.

This summary provides the basis for the ARMA models. It contains an explanation of the autocorrelation, White Noise, Partial Autocorrelation, Moving Average Model, Stationarity of the time series, weakly stationary, covariance stationary, model selection criteria, and how to interpret the graphs. This summary helps you go through material without watching again the lengthy web-lectures. I practically wrote down everything what he said. It helps also if you did not watch the weblecture, because ...

Summary of the 2nd lecture, week 1. It includes explanation of the logit model with an empirical example, estimation of the model, and how to build a ROC curve step by step as provided by the teacher in class. Also the interpretation of the coefficients is provided. The self-study questions and the multiple questions with the solutions are from the end of the book. The exam questions are from the exams provided by the lecturer.

Here are the exercises from Chapter 12 together with the solutions.

An extensive summary of all the material discussed during the lectures.

This summary provides a good explanation of the panel data. It goes into explaining the meaning of panel data, how to deal with panel data regressions, pooled regressions with examples from the class, fixed effects, time and firm fixed effects and random effects model. It explains the within and between estimator, the interpretation of the models, the Hausman test together with the interpretation of the stata table, some exam questions, and at the end it goes into the clustered standard errors....

Here is the summary from the models AR(1), MA(1), ARMA(2,1) step by step, explained with colours. If something is not understandable, please write it in the comments below. This summary helps you go through material without watching again the lengthy web-lectures. I practically wrote down everything what he said. It helps also if you did not watch the weblecture, because you can find here everything what he talked about.