Quantitative Methods in Finance: Univariate Models Quiz

A spurious regression occurs when two independent variables are actually related, but the regression suggests a relationship between one of the variables and the dependent variable.

A white noise process is an example of a stationary stochastic process.

The Box-Jenkins methodology primarily focuses on univariate time series forecasting models.

The Autocovariance Function measures the linear dependency between observations at different time points in a time series.

Stationary processes exhibit time-varying mean and variance over time.

A nonstationary stochastic process is a type of stochastic process that has a constant mean and variance over time.

The Autoregressive model is based on the assumption that the current value of a time series is related to the past values of the same series.

The Autocovariance function measures the linear dependency between observations at the same time point in a time series.

The Box-Jenkins forecasting methodology is primarily used for multivariate time series forecasting models.

Forecasting with ARMA (1,1) models involves using both autoregressive and moving average components to predict future values of a time series.