A normal distribution has coefficients of skewness and excess kurtosis which are respectively:

Transforming two explanatory variables into a ratio

Removing large positive residuals

Using a procedure for estimation and inference which did not assume normality

Removing large negative residuals

Consistent and unbiased but inefficient

Consistent and asymptotically efficient but biased

Inconsistent

Consistent, unbiased and efficient

A slowly decaying acf, and a pacf with 3 significant spikes

A slowly decaying pacf and an acf with 3 significant spikes

A slowly decaying acf and pacf

 An acf and a pacf with 3 significant spikes

The current value of y

Zero

The historical unweighted average of y

An exponentially weighted average of previous values of y

An AR(1)

An AR(2)

An ARMA(1,1)

An MA(3)

There are 2 linearly independent cointegrating vectors

There are at most 2 linearly independent cointegrating vectors

There are 3 variables in the system

There are at least 2 linearly independent cointegrating vectors

It is the volatility of the underlying asset’s returns implied from the price of a traded option and an option pricing model

It is the volatility of the underlying asset’s returns implied from a statistical model such as GARCH

It is the volatility of an option price implied from a statistical model such as GARCH

It is the volatility of an option price implied from the underlying asset volatility

The price range (high minus low) on that day

The squared return on that day

The sum of the squares of hourly returns on that day

The squared return on the previous day

Product

Production

Pricing

Distribution

Order

Distance

Origin

All of the above