Shrinkage Anyone? concerning, efficiency, following, decrease, increase

sabre

Which of the following concerning Shrinkage Estimators is FALSE?

A) the term 'shrinkage' refers to the approach's ability to reduce the impact of extreme values in historical estimates

B) any choice for the target covariance matrix will lead to an increase (or at least not a decrease) in the efficiency of the covariance estimates versus the historical estimate

C) shrinkage estimator is an inferior approach for estimating the population covariance matrix for the medium- and smaller-size datasets that are typical in finance

cityboy

I was in the pool!

B or C......

due to the word "any" i will go with B.

ohai

i'll take C.

liangfeng

I said C. Though I have no idea.

IAmNeil

and just for giggles since i'm now looking at my notecards and it's my next one after shrinkage, remember with volatility clustering, high volatility periods are often followed by periods of more high vol or low with low. the higher the rate of decay b/t volatility b/t one period and the next, the greater the tendency for volatility clustering. i like these quizes- reminding me of the little stuff i completely forgot even existed in this cirriculum.

Valores

these eggs are delicious................



c cuz shrinkage is a superior way for esitmationg not inferior

liangfeng

C is the correct answer..............superior is the right word, not inferior as pimp stated

"it shrinks?"........................."like a frightened turtle!"

Analyze_This

c.... is the right answer...it is not an inferior way doing things

Chuckrox

C shrinkage fits medium and small data like financial market