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Minimize SC
This is the : .Schwarz Criterion. In this model, the utility function is given by: SC = m * log( Var(e) / m ) + n * log(m) where Var(e) = variance of excess return of manager over benchmark, using current subset n = number of indices in current subset m = number of returns In this model, StyleADVISOR chooses the subset of indices where SC assumes its minimal value. Related Statistics: Model Selection Maximize Adjusted R2 Minimize Cp Minimize AIC
SC = m * log( Var(e) / m ) + n * log(m) where Var(e) = variance of excess return of manager over benchmark, using current subset n = number of indices in current subset m = number of returns
SC = m * log( Var(e) / m ) + n * log(m)
where
Var(e) = variance of excess return of manager over benchmark, using current subset n = number of indices in current subset m = number of returns
Related Statistics: Model Selection Maximize Adjusted R2 Minimize Cp Minimize AIC