Phase Distribution and Phase Correlation of Financial Time Series

Scaling, phase distribution and phase correlation of financial time series are investigated based on the Dow Jones Industry Average (DJIA) and NASDAQ 10-minute intraday data for a period from Aug. 1 1997 to Dec. 31 2003. The returns of the two indices are shown to have nice scaling behaviors and belong to stable distributions according to the criterion of Levy's alpha stable distribution condition. A novel approach catching characteristic features of financial time series based on the concept of instantaneous phase is further proposed to study phase distribution and correlation. The analysis of phase distribution concludes return time series fall into a class which is different from other non-stationary time series. The correlation between returns of the two indices probed by the distribution of phase difference indicates there was a remarkable change of trading activities after the event of 911 attack, and this change persisted in later trading activities.Phase Distribution, High Frequency Data, Scaling Analysis, Levy Distribution, Stock Market, Frequency Variant

SPT5 affects the rate of mRNA degradation and physically interacts with CCR4 but does not control mRNA deadenylation

The CCR4-NOT complex has been shown to have multiple roles in mRNA metabolism, including that of transcriptional elongation, mRNA transport, and nuclear exosome function, but the primary function of CCR4 and CAF1 is in the deadenylation and degradation of cytoplasmic mRNA. As previous genetic analysis supported an interaction between SPT5, known to be involved in transcriptional elongation, and that of CCR4, the physical association of SPT5 with CCR4 was examined. A two-hybrid screen utilizing the deadenylase domain of CCR4 as a bait identified SPT5 as a potential interacting protein. SPT5 at its physiological concentration was shown to immunoprecipitate CCR4 and CAF1, and in vitro purified SPT5 specifically could bind to CAF1 and the deadenylase domain of CCR4. We additionally demonstrated that mutations in SPT5 or an spt4 deletion slowed the rate of mRNA degradation, a phenotype associated with defects in the CCR4 mRNA deadenylase complex. Yet, unlike ccr4 and caf1 deletions, spt5 and spt4 defects displayed little effect on the rate of deadenylation. They also did not affect decapping or 5\u27 - 3\u27 degradation of mRNA. These results suggest that the interactions between SPT5/SPT4 and the CCR4-NOT complex are probably the consequences of effects involving nuclear events and do not involve the primary role of CCR4 in mRNA deadenylation and turnover

Kernel Estimation of Rate Function for Recurrent Event Data

Recurrent event data are largely characterized by the rate function but smoothing techniques for estimating the rate function have never been rigorously developed or studied in statistical literature. This paper considers the moment and least squares methods for estimating the rate function from recurrent event data. With an independent censoring assumption on the recurrent event process, we study statistical properties of the proposed estimators and propose bootstrap procedures for the bandwidth selection and for the approximation of confidence intervals in the estimation of the occurrence rate function. It is identified that the moment method without resmoothing via a smaller bandwidth will produce curve with nicks occurring at the censoring times, whereas there is no such problem with the least squares method. Furthermore, the asymptotic variance of the least squares estimator is shown to be smaller under regularity conditions. However, in the implementation of the bootstrap procedures, the moment method is computationally more efficient than the least squares method because the former approach uses condensed bootstrap data. The performance of the proposed procedures is studied through Monte Carlo simulations and an epidemiological example on intravenous drug users

Stoichiometry and Change of the mRNA Closed-Loop Factors as Translating Ribosomes Transit from Initiation to Elongation

Protein synthesis is a highly efficient process and is under exacting control. Yet, the actual abundance of translation factors present in translating complexes and how these abundances change during the transit of a ribosome across an mRNA remains unknown. Using analytical ultracentrifugation with fluorescent detection we have determined the stoichiometry of the closed-loop translation factors for translating ribosomes. A variety of pools of translating polysomes and monosomes were identified, each containing different abundances of the closed-loop factors eIF4E, eIF4G, and PAB1 and that of the translational repressor, SBP1. We establish that closed-loop factors eIF4E/eIF4G dissociated both as ribosomes transited polyadenylated mRNA from initiation to elongation and as translation changed from the polysomal to monosomal state prior to cessation of translation. eIF4G was found to particularly dissociate from polyadenylated mRNA as polysomes moved to the monosomal state, suggesting an active role for translational repressors in this process. Consistent with this suggestion, translating complexes generally did not simultaneously contain eIF4E/eIF4G and SBP1, implying mutual exclusivity in such complexes. For substantially deadenylated mRNA, however, a second type of closed-loop structure was identified that contained just eIF4E and eIF4G. More than one eIF4G molecule per polysome appeared to be present in these complexes, supporting the importance of eIF4G interactions with the mRNA independent of PAB1. These latter closed-loop structures, which were particularly stable in polysomes, may be playing specific roles in both normal and disease states for specific mRNA that are deadenylated and/or lacking PAB1. These analyses establish a dynamic snapshot of molecular abundance changes during ribosomal transit across an mRNA in what are likely to be critical targets of regulation