Written by students who passed Immediately available after payment Read online or as PDF Wrong document? Swap it for free 4.6 TrustPilot
logo-home
Document preview thumbnail
Preview 2 out of 6 pages
Summary

Summary Logit Model

Document preview thumbnail
Preview 2 out of 6 pages

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. 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.

Content preview

, Logit model
Logistic regression, or logit regression, or logit model is a regression model where the dependent
variable (DV) is categorical. ... The binary logistic model is used to estimate the probability of a binary
response based on one or more predictor (or independent) variables (features).

The term refers to any problem where the values that the dependent variables may take are limited
to certain integers (e.g. 0, 1, 2, 3, 4) or even where it is a binary number (only 0 or 1). There are
numerous examples of instances where this may arise, for example where we want to model:

o Why firms choose to list their shares on the NASDAQ rather than the NYSE
o Why some stocks pay dividends while others do not
o What factors affect whether countries default on their sovereign deb
o Why some firms choose to issue new stock to finance an expansion while others
issue bonds
o Why some firms choose to engage in stock splits while others do not.

The logit model: empirical example




- The output looks like a linear regression output.
- The estimation is easy, the interpretation is different.
- The table above shows that just Inverse Leverage (MV) is significant, based on p-value. It is a
good default indicator.




- The graph above, shows the linear fit of the logit model.
o The linear fit is introduced to a function  this explains the s-type curve in the graph
between 0 and 1.

Connected book
 image
Publisher: mei 2014 ISBN: 9781107661455 Edition: 1

Document information

Study
Summarized whole book?
Unknown
Uploaded on
November 23, 2017
Number of pages
6
Written in
2017/2018
Type
Summary
$4.19

Wrong document? Swap it for free Within 14 days of purchase and before downloading, you can choose a different document. You can simply spend the amount again.
Written by students who passed
Immediately available after payment
Read online or as PDF

Seller avatar
Reputation scores are based on the amount of documents a seller has sold for a fee and the reviews they have received for those documents. There are three levels: Bronze, Silver and Gold. The better the reputation, the more your can rely on the quality of the sellers work.
claudiughiuzan
3.8
(52)
Sold
403
Followers
208
Items
38
Last sold
2 year ago



Why students choose Stuvia

Created by fellow students, verified by reviews

Quality you can trust: written by students who passed their tests and reviewed by others who've used these notes.

Didn't get what you expected? Choose another document

No worries! You can instantly pick a different document that better fits what you're looking for.

Pay as you like, start learning right away

No subscription, no commitments. Pay the way you're used to via credit card and download your PDF document instantly.

Student with book image

“Bought, downloaded, and aced it. It really can be that simple.”

Alisha Student

Working on your references?

Create accurate citations in APA, MLA and Harvard with our free citation generator.

Working on your references?

Frequently asked questions