26 research outputs found

    Measuring portfolio performance using a modified measure of risk

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    This paper reports the results of an investigation into the properties of a theoretical modification of beta proposed by Leland (1999) and based on earlier work of Rubinstein (1976). It is shown that when returns are elliptically symmetric, beta is the appropriate measure of risk and that there are other situations in which the modified beta will be similar to the traditional measure based on the capital asset pricing model. For the case where returns have a normal distribution, it is shown that the criterion either does not exist or reduces exactly to the conventional beta. It is therefore conjectured that the modified measure will only be useful for portfolios that have nonstandard return distributions which incorporate skewness. For such situations, it is shown how to estimate the measure using regression and how to compare the resulting statistic with a traditional estimated beta using Hotelling's test. An empirical study based on stocks from the FTSE350 does not find evidence to support the use of the new measure even in the presence of skewness.Journal of Asset Management (2007) 7, 388-403. doi:10.1057/palgrave.jam.225005

    Embedding mRNA Stability in Correlation Analysis of Time-Series Gene Expression Data

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    Current methods for the identification of putatively co-regulated genes directly from gene expression time profiles are based on the similarity of the time profile. Such association metrics, despite their central role in gene network inference and machine learning, have largely ignored the impact of dynamics or variation in mRNA stability. Here we introduce a simple, but powerful, new similarity metric called lead-lag R2 that successfully accounts for the properties of gene dynamics, including varying mRNA degradation and delays. Using yeast cell-cycle time-series gene expression data, we demonstrate that the predictive power of lead-lag R2 for the identification of co-regulated genes is significantly higher than that of standard similarity measures, thus allowing the selection of a large number of entirely new putatively co-regulated genes. Furthermore, the lead-lag metric can also be used to uncover the relationship between gene expression time-series and the dynamics of formation of multiple protein complexes. Remarkably, we found a high lead-lag R2 value among genes coding for a transient complex

    R-Ras Regulates Migration through an Interaction with Filamin A in Melanoma Cells

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    Changes in cell adhesion and migration in the tumor microenvironment are key in the initiation and progression of metastasis. R-Ras is one of several small GTPases that regulate cell adhesion and migration on the extracellular matrix, however the mechanism has not been completely elucidated. Using a yeast two-hybrid approach we sought to identify novel R-Ras binding proteins that might mediate its effects on integrins.We identified Filamin A (FLNa) as a candidate interacting protein. FLNa is an actin-binding scaffold protein that also binds to integrin Ξ²1, Ξ²2 and Ξ²7 tails and is associated with diverse cell processes including cell migration. Indeed, M2 melanoma cells require FLNa for motility. We further show that R-Ras and FLNa interact in co-immunoprecipitations and pull-down assays. Deletion of FLNa repeat 3 (FLNaΞ”3) abrogated this interaction. In M2 melanoma cells active R-Ras co-localized with FLNa but did not co-localize with FLNa lacking repeat 3. Thus, activated R-Ras binds repeat 3 of FLNa. The functional consequence of this interaction was that active R-Ras and FLNa coordinately increased cell migration. In contrast, co-expression of R-Ras and FLNaΞ”3 had a significantly reduced effect on migration. While there was enhancement of integrin activation and fibronectin matrix assembly, cell adhesion was not altered. Finally, siRNA knockdown of endogenous R-Ras impaired FLNa-dependent fibronectin matrix assembly.These data support a model in which R-Ras functionally associates with FLNa and thereby regulates integrin-dependent migration. Thus in melanoma cells R-Ras and FLNa may cooperatively promote metastasis by enhancing cell migration

    Multiple Signals Converge on a Differentiation MAPK Pathway

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    An important emerging question in the area of signal transduction is how information from different pathways becomes integrated into a highly coordinated response. In budding yeast, multiple pathways regulate filamentous growth, a complex differentiation response that occurs under specific environmental conditions. To identify new aspects of filamentous growth regulation, we used a novel screening approach (called secretion profiling) that measures release of the extracellular domain of Msb2p, the signaling mucin which functions at the head of the filamentous growth (FG) MAPK pathway. Secretion profiling of complementary genomic collections showed that many of the pathways that regulate filamentous growth (RAS, RIM101, OPI1, and RTG) were also required for FG pathway activation. This regulation sensitized the FG pathway to multiple stimuli and synchronized it to the global signaling network. Several of the regulators were required for MSB2 expression, which identifies the MSB2 promoter as a target β€œhub” where multiple signals converge. Accessibility to the MSB2 promoter was further regulated by the histone deacetylase (HDAC) Rpd3p(L), which positively regulated FG pathway activity and filamentous growth. Our findings provide the first glimpse of a global regulatory hierarchy among the pathways that control filamentous growth. Systems-level integration of signaling circuitry is likely to coordinate other regulatory networks that control complex behaviors
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