R5 - Quant - Multiple Regression Flashcards
Multiple Regression
Linear regression involving two or more independent variables.
Y = b0 + b1X1 + b2X2 + E
Where:
Yi = The ith Observation of the dependent variable Y
Xji = The ith observation of the independent variable Xj, j=1,2,…,k
b0 = The intercept of the equation
b1,..,bk = The slope coefficients for each independent var
Adjusted R2
A measure of goodness-of-fit of a regression that is adjusted for degrees of freedom and hence does not automatically increase when another independent variable is added to a regression.
Analysis of variance (ANOVA)
The analysis of the total variability of a dataset (such as observations on the dependent variable in a regression) into components representing different sources of variation; with reference to regression, ANOVA provides the inputs for an F-test of the significance of the regression as a whole.
Breusch−Pagan test
A test for conditional heteroskedasticity in the error term of a regression.
Categorical dependent variables
An alternative term for qualitative dependent variables.
Common size statements
Financial statements in which all elements (accounts) are stated as a percentage of a key figure such as revenue for an income statement or total assets for a balance sheet.
Conditional heteroskedasticity
Heteroskedasticity in the error variance that is correlated with the values of the independent variable(s) in the regression.
Data mining
The practice of determining a model by extensive searching through a dataset for statistically significant patterns.
Discriminant analysis
A multivariate classification technique used to discriminate between groups, such as companies that either will or will not become bankrupt during some time frame.
Dummy variable
A type of qualitative variable that takes on a value of 1 if a particular condition is true and 0 if that condition is false.
First-order serial correlation
Correlation between adjacent observations in a time series.
Generalized least squares
A regression estimation technique that addresses heteroskedasticity of the error term.
Heteroskedastic
With reference to the error term of regression, having a variance that differs across observations.
Heteroskedasticity-consistent standard errors
Standard errors of the estimated parameters of a regression that correct for the presence of heteroskedasticity in the regression’s error term.
Log-log regression model
A regression that expresses the dependent and independent variables as natural logarithms.
Logistic regression (logit model)
A qualitative-dependent-variable multiple regression model based on the logistic probability distribution.
Market timing
Asset allocation in which the investment in the market is increased if one forecasts that the market will outperform T-bills.
Model specification
With reference to regression, the set of variables included in the regression and the regression equation’s functional form.
Multicollinearity
A regression assumption violation that occurs when two or more independent variables (or combinations of independent variables) are highly but not perfectly correlated with each other.
Multiple linear regression model
A linear regression model with two or more independent variables.
Negative serial correlation
Serial correlation in which a positive error for one observation increases the chance of a negative error for another observation, and vice versa.
Nonstationarity
With reference to a random variable, the property of having characteristics such as mean and variance that are not constant through time.
Partial regression coefficients
The slope coefficients in a multiple regression.
Partial slope coefficients
The slope coefficients in a multiple regression.
Positive serial correlation
Serial correlation in which a positive error for one observation increases the chance of a positive error for another observation, and a negative error for one observation increases the chance of a negative error for another observation.
Probit regression (probit model)
A qualitative-dependent-variable multiple regression model based on the normal distribution.
Qualitative dependent variables
Dummy variables used as dependent variables rather than as independent variables.
Random walk
A time series in which the value of the series in one period is the value of the series in the previous period plus an unpredictable random error.
Regression coefficients
The intercept and slope coefficient(s) of a regression.
Robust standard errors
Standard errors of the estimated parameters of a regression that correct for the presence of heteroskedasticity in the regression’s error term.
Serially correlated
With reference to regression errors, errors that are correlated across observations.
Unconditional heteroskedasticity
Heteroskedasticity of the error term that is not correlated with the values of the independent variable(s) in the regression.
White-corrected standard errors
A synonym for robust standard errors.
