Flashcards in Quant Shit Deck (24):

1

## Conditional heteroskedasticity is

### residual variance related to level of X's

2

## Serial correlation is

### correlated residuals

3

## Multicollinearity is

### two or more X's are correlated

4

## Effect of conditional heteroskedasticity

###
Type I errors

high t stat, caused by low std errors

5

## Effect of serial correlation

###
Type I errors

positive correlation

6

## Effect of multicollinearity

### type II errors

7

## Detection of conditional heteroskedasticity

###
Breusch-Pagan Test

Chi-Square Test

8

## Detection of serial correlation

###
Durbin-Watson test

9

## Detection of multicollinearity

###
Conflicting t and F stats

Correlations among ind variables if k=2

10

## Correcting conditional skedasticity

### white-correct std errors

11

## Correction serial correlation

### Hansen method

12

## Correcting multicollinearity

### Drop a correlated variable

13

## Functional Form Misspecifications

###
-important variables omitted

-variables not transformed properly

-data pooled improperly

14

## Time-Series Misspecification

###
-X is lagged Y with serial correlation present

-Forecasting the past

-Measurement error

15

## Probit model

### estimates probability of default given values of X based on normal dist

16

## Logit Models

###
estimates probability of default given values of X based on logistic dist (computationally easier than normal dist).

Logistic dist NOT logarthimic

17

## Discriminant models

###
produces a score or rank used to classify into categories

ex- bankrupt, not bankrupt

18

## Economic Significance

###
not significant just because of statistical significance

-commissions, taxes, risk, etc.

19

## If a time series is mean reverting

### the value of the dependent variable tends to fall when above its mean; and rise when below its mean

20

## Mean Reverting Level Formula

### b0/ (1 - b1)

21

## Forecasting Accuracy of ARCH measured by

###
root of mean squared error.

Use model with lowest RMSE based on out-of-sample forecasting

22

## Without a mean reverting level, the time series is

### non-stationary

23

## Dickey-Fuller Tests for

### unit root

24