496 research outputs found

    Time-Varying Volatility and the Dynamic Behavior of the Term Structure

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    In this paper, we consider a framework with which the cross sectional and time series behavior of the yield curve can be studied simultaneously. We examine the relationship between the yield curve and the time-varying conditional volatility of the Treasury bill market. We demonstrate that differently shaped yield curves can result given different combinations of volatility and expectations about future spot rates. Moreover, adjusting the forward rate for the volatility related liquidity premium can improve its performance as a predictor of future spot rates at least for the period from August 1964 to August 1979.

    Measuring and Testing the Impact of News on Volatility

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    This paper introduces the News Impact Curve to measure how new information is incorporated into volatility estimates. A variety of new and existing ARCH models are compared and estimated with daily Japanese stock return data to determine the shape of the News Impact Curve. New diagnostic tests are presented which emphasize the asymmetry of the volatility response to news. A partially non-parametric ARCH model is introduced to allow the data to estimate this shape. A comparison of this model with the existing models suggests that the best models are one by Glosten Jaganathan and Runkle (GJR) and Nelson's EGARCE. Similar results hold on a pre-crash sample period but are less strong.

    A multi-dynamic-factor model for stock returns

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    In this paper, we define dynamic and static factors and distinguish between the dynamic and static structure of asset excess returns. We examine the value-weighted market portfolio as a dynamic factor and propose an intuitively appealing procedure to search for more dynamic factors. We find evidence that the market is a dynamic factor but a three-dynamic-factor model is superior in modelling the decile portfolios. The two additional factors are correlated with a January dummy and Bond risk premium and with production growth and a recession dummy, respectively. We found that small firms are more sensitive to the January/Bond risk factor, while large firms are more sensitive to the Production/Recession factor. We found that after accounting for the systematic risk corresponding to the three dynamic factors, there is not much of a static component of asset risk premium and there is no evidence for a higher `unexplained' return on small firm portfolios.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/30125/1/0000501.pd

    Asset pricing with a factor-arch covariance structure : Empirical estimates for treasury bills

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    In this paper we suggest using the FACTOR-ARCH model as a parsimonious structure for the conditional covariance matrix of asset excess returns. This structure allows us to study the dynamic relationship between asset risk premia and volatilities in a multivariate system. One and two FACTOR-ARCH models are successfully applied to pricing of Treasury bills. The results show stability over time, pass a variety of diagnostic tests, and compare favorably with previous empirical findings.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/28496/1/0000293.pd

    Comprehensive genetic diagnosis of tandem repeat expansion disorders with programmable targeted nanopore sequencing

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    More than 50 neurological and neuromuscular diseases are caused by short tandem repeat (STR) expansions, with 37 different genes implicated to date. We describe the use of programmable targeted long-read sequencing with Oxford Nanopore's ReadUntil function for parallel genotyping of all known neuropathogenic STRs in a single assay. Our approach enables accurate, haplotype-resolved assembly and DNA methylation profiling of STR sites, from a list of predetermined candidates. This correctly diagnoses all individuals in a small cohort (n = 37) including patients with various neurogenetic diseases (n = 25). Targeted long-read sequencing solves large and complex STR expansions that confound established molecular tests and short-read sequencing and identifies noncanonical STR motif conformations and internal sequence interruptions. We observe a diversity of STR alleles of known and unknown pathogenicity, suggesting that long-read sequencing will redefine the genetic landscape of repeat disorders. Last, we show how the inclusion of pharmacogenomic genes as secondary ReadUntil targets can further inform patient care

    Lobular Carcinomas In Situ Display Intralesion Genetic Heterogeneity and Clonal Evolution in the Progression to Invasive Lobular Carcinoma

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    Purpose:; Lobular carcinoma; in situ; (LCIS) is a preinvasive lesion of the breast. We sought to define its genomic landscape, whether intralesion genetic heterogeneity is present in LCIS, and the clonal relatedness between LCIS and invasive breast cancers.; Experimental Design:; We reanalyzed whole-exome sequencing (WES) data and performed a targeted amplicon sequencing validation of mutations identified in 43 LCIS and 27 synchronous more clinically advanced lesions from 24 patients [9 ductal carcinomas; in situ; (DCIS), 13 invasive lobular carcinomas (ILC), and 5 invasive ductal carcinomas (IDC)]. Somatic genetic alterations, mutational signatures, clonal composition, and phylogenetic trees were defined using validated computational methods.; Results:; WES of 43 LCIS lesions revealed a genomic profile similar to that previously reported for ILCs, with; CDH1; mutations present in 81% of the lesions. Forty-two percent (18/43) of LCIS were found to be clonally related to synchronous DCIS and/or ILCs, with clonal evolutionary patterns indicative of clonal selection and/or parallel/branched progression. Intralesion genetic heterogeneity was higher among LCIS clonally related to DCIS/ILC than in those nonclonally related to DCIS/ILC. A shift from aging to APOBEC-related mutational processes was observed in the progression from LCIS to DCIS and/or ILC in a subset of cases.; Conclusions:; Our findings support the contention that LCIS has a repertoire of somatic genetic alterations similar to that of ILCs, and likely constitutes a nonobligate precursor of breast cancer. Intralesion genetic heterogeneity is observed in LCIS and should be considered in studies aiming to develop biomarkers of progression from LCIS to more advanced lesions
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