Honey, I shrunk the sample covariance matrix

The central message of this paper is that nobody should be using the samplecovariance matrix for the purpose of portfolio optimization. It containsestimation error of the kind most likely to perturb a mean-varianceoptimizer. In its place, we suggest using the matrix obtained from thesample covariance matrix through a transformation called shrinkage. Thistends to pull the most extreme coefficients towards more central values,thereby systematically reducing estimation error where it matters most.Statistically, the challenge is to know the optimal shrinkage intensity,and we give the formula for that. Without changing any other step in theportfolio optimization process, we show on actual stock market data thatshrinkage reduces tracking error relative to a benchmark index, andsubstantially increases the realized information ratio of the activeportfolio manager.

Estudi palinologic dels sediments de les mels de Xixona (Alacant)

Anàlisi pol.línica dels sediments de dotze mostres de mei recollides al terme municipal de Xixona (Alacant). Utilitzant els resultats fern una classificació qualitativa de les mels segons el seu origen floral i una de quantitativa aplicant els críteris de MAURIZIO, 1939.