Improved estimation of the covariance matrix of stock returns with an application to portofolio selection

This paper proposes to estimate the covariance matrix of stock returnsby an optimally weighted average of two existing estimators: the samplecovariance matrix and single-index covariance matrix. This method isgenerally known as shrinkage, and it is standard in decision theory andin empirical Bayesian statistics. Our shrinkage estimator can be seenas a way to account for extra-market covariance without having to specifyan arbitrary multi-factor structure. For NYSE and AMEX stock returns from1972 to 1995, it can be used to select portfolios with significantly lowerout-of-sample variance than a set of existing estimators, includingmulti-factor models.

Using composite estimators to improve both domain and total area estimation

In this article we propose using small area estimators to improve the estimatesof both the small and large area parameters. When the objective is to estimateparameters at both levels accurately, optimality is achieved by a mixed sampledesign of fixed and proportional allocations. In the mixed sample design, oncea sample size has been determined, one fraction of it is distributedproportionally among the different small areas while the rest is evenlydistributed among them. We use Monte Carlo simulations to assess theperformance of the direct estimator and two composite covariant-freesmall area estimators, for different sample sizes and different sampledistributions. Performance is measured in terms of Mean Squared Errors(MSE) of both small and large area parameters. It is found that the adoptionof small area composite estimators open the possibility of 1) reducingsample size when precision is given, or 2) improving precision for a givensample size.

Genome-wide association study of major recurrent depression in the U.K. population.

OBJECTIVE: Studies of major depression in twins and families have shown moderate to high heritability, but extensive molecular studies have failed to identify susceptibility genes convincingly. To detect genetic variants contributing to major depression, the authors performed a genome-wide association study using 1,636 cases of depression ascertained in the U.K. and 1,594 comparison subjects screened negative for psychiatric disorders. METHOD: Cases were collected from 1) a case-control study of recurrent depression (the Depression Case Control [DeCC] study; N=1346), 2) an affected sibling pair linkage study of recurrent depression (probands from the Depression Network [DeNT] study; N=332), and 3) a pharmacogenetic study (the Genome-Based Therapeutic Drugs for Depression [GENDEP] study; N=88). Depression cases and comparison subjects were genotyped at Centre National de Génotypage on the Illumina Human610-Quad BeadChip. After applying stringent quality control criteria for missing genotypes, departure from Hardy-Weinberg equilibrium, and low minor allele frequency, the authors tested for association to depression using logistic regression, correcting for population ancestry. RESULTS: Single nucleotide polymorphisms (SNPs) in BICC1 achieved suggestive evidence for association, which strengthened after imputation of ungenotyped markers, and in analysis of female depression cases. A meta-analysis of U.K. data with previously published results from studies in Munich and Lausanne showed some evidence for association near neuroligin 1 (NLGN1) on chromosome 3, but did not support findings at BICC1. CONCLUSIONS: This study identifies several signals for association worthy of further investigation but, as in previous genome-wide studies, suggests that individual gene contributions to depression are likely to have only minor effects, and very large pooled analyses will be required to identify them.

Kenraali K. O. Leinonen 5/10 1973

Kirje 5.10.1973

Presidentti J.K. Paasikivi 27/11 1956

Kirje 27.11.1956

Effects of mineralocorticoid and K+ concentration on K+ secretion and ROMK channel expression in a mouse cortical collecting duct cell line.

The cortical collecting duct (CCD) plays a key role in regulated K(+) secretion, which is mediated mainly through renal outer medullary K(+) (ROMK) channels located in the apical membrane. However, the mechanisms of the regulation of urinary K(+) excretion with regard to K(+) balance are not well known. We took advantage of a recently established mouse CCD cell line (mCCD(cl1)) to investigate the regulation of K(+) secretion by mineralocorticoid and K(+) concentration. We show that this cell line expresses ROMK mRNA and a barium-sensitive K(+) conductance in its apical membrane. As this conductance is sensitive to tertiapin-Q, with an apparent affinity of 6 nM, and to intracellular acidification, it is probably mediated by ROMK. Overnight exposure to 100 nM aldosterone did not significantly change the K(+) conductance, while it increased the amiloride-sensitive Na(+) transport. Overnight exposure to a high K(+) (7 mM) concentration produced a small but significant increase in the apical membrane barium-sensitive K(+) conductance. The mRNA levels of all ROMK isoforms measured by qRT-PCR were not changed by altering the basolateral K(+) concentration but were decreased by 15-45% upon treatment with aldosterone (0.3 or 300 nM for 1 and 3 h). The paradoxical response of ROMK expression to aldosterone could possibly work as a preventative mechanism to avoid excessive K(+) loss which would otherwise result from the increased electrogenic Na(+) transport and associated depolarization of the apical membrane in the CCD. In conclusion, mCCD(cl1) cells demonstrate a significant K(+) secretion, probably mediated by ROMK, which is not stimulated by aldosterone but increased by overnight exposure to a high K(+) concentration.

Kenraaliluutnantti evp. K.L. Oesch 12/12 1974

Kirje 12.12.1974