ARCH(1) model

[elenayhg]

why the regression equation is about squared residual while we can use it to forecast variance of residual? not intuitive to me.

Thanks for your help.

[lockheed10023]

same thing.

[S2000magician]

@elenayhg

why the regression equation is about squared residual while we can use it to forecast variance of residual? not intuitive to me.

Thanks for your help.

σ² = E(X – µ)² = E(X²) – µ².

[elenayhg]

@S2000magician

@elenayhg

why the regression equation is about squared residual while we can use it to forecast variance of residual? not intuitive to me.

Thanks for your help.

σ² = E(X – µ)² = E(X²) – µ².

so basically we assume u=0 for rediduals, so that var(residual)=residual^2.

[S2000magician]

@elenayhg

@S2000magician

@elenayhg

why the regression equation is about squared residual while we can use it to forecast variance of residual? not intuitive to me.

Thanks for your help.

σ² = E(X – µ)² = E(X²) – µ².

so basically we assume u=0 for rediduals, so that var(residual)=residual^2.

Yup.

[elenayhg]

@S2000magician

@elenayhg

@S2000magician

@elenayhg

why the regression equation is about squared residual while we can use it to forecast variance of residual? not intuitive to me.

Thanks for your help.

σ² = E(X – µ)² = E(X²) – µ².

so basically we assume u=0 for rediduals, so that var(residual)=residual^2.

Yup.

appreciate.