can we have some tricks to remember these two models
Dummy variables are used to represent a qualitative independent variable. Probit models are used to estimate the probability of occurrence for a qualitative dependent variable. Schweser doesnt do a great job on detailing these two ne inputs??
neither does cfa… i think all you need to know is what you just said
the way I remember it is Probit = based on NORMAL distribution Logit = Based on a LOGISTICal distribution
PROBIT = BINARY probablity of bankruptcy/merger/spinoff/ bla… Here the dependendant variable is the binary 1 (will occur?) or 0(will not occur?) LOGIT = log distributions… DUMMY = Factor portfolio
kkk some toughts on Discriminant models ??
Discriminant - Used for classification into n baskets. Like classifying the stock as Small/Mid/Large Cap.