Detecting Regimes of Predictability in the U.S. Equity Premium

We investigate the stability of predictive regression models for the U.S. equity premium. A new approach for detecting regimes of temporary predictability is proposed using se- quential implementations of standard (heteroskedasticity-robust) regression t-statistics for predictability applied over relatively short time periods. Critical values for each test in the sequence are provided using subsampling methods. Our primary focus is to develop a real-time monitoring procedure for the emergence of predictive regimes using tests based on end-of-sample data in the sequential procedure, although the procedure could be used for an historical analysis of predictability. Our proposed method is robust to both the degree of persistence and endogeneity of the regressors in the predictive regression and to certain forms of heteroskedasticity in the shocks. We discuss how the detection procedure can be designed such that the false positive rate is pre-set by the practitioner at the start of the monitoring period. We use our approach to investigate for the presence of regime changes in the predictability of the U.S. equity premium at the one-month horizon by traditional macroeconomic and financial variables, and by binary technical analysis indicators. Our results suggest that the one-month ahead equity premium has temporarily been predictable (displaying so-called ‘pockets of predictability’), and that these episodes of predictability could have been detected in real-time by practitioners using our proposed methodology

Tests for explosive financial bubbles in the presence of non-stationary volatility

This paper studies the impact of permanent volatility shifts in the innovation process on the performance of the test for explosive financial bubbles based on recursive right-tailed Dickey–Fuller-type unit root tests proposed by Phillips, Wu and Yu (2011). We show that, in this situation, their supremum-based test has a non-pivotal limit distribution under the unit root null, and can be quite severely over-sized, thereby giving rise to spurious indications of explosive behaviour. We investigate the performance of a wild bootstrap implementation of their test procedure for this problem, and show it is effective in controlling size, both asymptotically and in finite samples, yet does not sacrifice power relative to an (infeasible) size-adjusted version of their test, even when the shocks are homoskedastic. We also discuss an empirical application involving commodity price time series and find considerably less emphatic evidence for the presence of explosive bubbles in these data when using our proposed wild bootstrap implementation of the Phillips, Wu and Yu (2011) test

Testing for Unit Roots Under Multiple Possible Trend Breaks and Non‐Stationary Volatility Using Bootstrap Minimum Dickey–Fuller Statistics

In a recent paper, Harvey et al. (2013) (HLT) propose a new unit root test that allows for the possibility of multiple breaks in trend. Their proposed test is based on the infimum of the sequence (across all candidate break points) of local GLS detrended augmented Dickey–Fuller‐type statistics. HLT show that the power of their unit root test is robust to the magnitude of any trend breaks. In contrast, HLT show that the power of the only alternative available procedure of Carrion‐i‐Silvestre et al. (2009), which employs a pretest‐based approach, can be very low indeed (even zero) for the magnitudes of trend breaks typically observed in practice. Both HLT and Carrion‐i‐Silvestre et al. (2009) base their approaches on the assumption of homoskedastic shocks. In this article, we analyse the impact of non‐stationary volatility (for example, single and multiple abrupt variance breaks, smooth transition variance breaks and trending variances) on the tests proposed in HLT. We show that the limiting null distribution of the HLT unit root test statistic is not pivotal under non‐stationary volatility. A solution to the problem, which does not require the practitioner to specify a parametric model for volatility, is provided using the wild bootstrap and is shown to perform well in practice. A number of different possible implementations of the bootstrap algorithm are discussed.</jats:p

Real-Time Detection of Regimes of Predictability in the U.S. Equity Premium

We propose new real-time monitoring procedures for the emergence of end-of-sample predictive regimes using sequential implementations of standard (heteroskedasticity-robust) regression t-statistics for predictability applied over relatively short time periods. The procedures we develop can also be used for detecting historical regimes of temporary predictability. Our proposed methods are robust to both the degree of persistence and endogeneity of the regressors in the predictive regression and to certain forms of heteroskedasticity in the shocks. We discuss how the monitoring procedures can be designed such that their false positive rate can be set by the practitioner at the start of the monitoring period using detection rules based on information obtained from the data in a training period. We use these new monitoring procedures to investigate the presence of regime changes in the predictability of the U.S. equity premium at the one-month horizon by traditional macroeconomic and financial variables, and by binary technical analysis indicators. Our results suggest that the one-month ahead equity premium has temporarily been predictable, displaying so-called 'pockets of predictability', and that these episodes of predictability could have been detected in real-time by practitioners using our proposed methodology

Treatment of Porphyromonas gulae infection and downstream pathology in the aged dog by lysine-gingipain inhibitor COR388.

COR388, a small-molecule lysine-gingipain inhibitor, is currently being investigated in a Phase 2/3 clinical trial for Alzheimer's disease (AD) with exploratory endpoints in periodontal disease. Gingipains are produced by two species of bacteria, Porphyromonas gingivalis and Porphyromonas gulae, typically associated with periodontal disease and systemic infections in humans and dogs, respectively. P. gulae infection in dogs is associated with periodontal disease, which provides a physiologically relevant model to investigate the pharmacology of COR388. In the current study, aged dogs with a natural oral infection of P. gulae and periodontal disease were treated with COR388 by oral administration for up to 90 days to assess lysine-gingipain target engagement and reduction of bacterial load and downstream pathology. In a 28-day dose-response study, COR388 inhibited the lysine-gingipain target and reduced P. gulae load in saliva, buccal cells, and gingival crevicular fluid. The lowest effective dose was continued for 90 days and was efficacious in continuous reduction of bacterial load and downstream periodontal disease pathology. In a separate histology study, dog brain tissue showed evidence of P. gulae DNA and neuronal lysine-gingipain, demonstrating that P. gulae infection is systemic and spreads beyond its oral reservoir, similar to recent observations of P. gingivalis in humans. Together, the pharmacokinetics and pharmacodynamics of COR388 lysine-gingipain inhibition, along with reduction of bacterial load and periodontal disease in naturally occurring P. gulae infection in the dog, support the use of COR388 in targeting lysine-gingipain and eliminating P. gingivalis infection in humans

Staphylococcus pseudintermedius Sbi paralogs inhibit complement and bind IgM, IgG Fc and Fab

The success of staphylococci as pathogens has been attributed, in part, to their ability to evade their hosts’ immune systems. Although the proteins involved in evasion have been extensively studied in staphylococci affecting humans little characterization has been done with Staphylococcus pseudintermedius, an important cause of pyoderma in dogs. Staphylococcus aureus binder of immunoglobulin (Sbi) interferes with innate immune recognition by interacting with multiple host proteins. In this study, a S. pseudintermedius gene that shares 38% similarity to S. aureus Sbi was cloned from S. pseudintermedius strains representative of major clonal lineages bearing two paralogs of the protein. Binding of immunoglobulins and Fab and Fc fragments as well as interaction with complement was measured. S. pseudintermedius Sbi protein bound IgG from multiple species and canine complement C3, neutralized complement activity and bound to canine IgM and B cells. Evidence from this work suggests Sbi may play an important role in S. pseudintermedius immune evasion

Assessing the relative validity of the Scottish Collaborative Group FFQ for measuring dietary intake in adults

Acknowledgements: The authors would like to thank Jacqueline Burr and Lindsey Shaw for collecting the data for this study. Data coding and entry for the food diaries was completed by Dr Lindsey Masson. The authors would also like to acknowledge the Scottish Health Survey Team, the Scottish Government and the National Centre for Social Research for their support in conducting this research. Financial support: This work was supported by funding from the Rural and Environment Science and Analytical Services Division (RESAS) programme of the Scottish Government (J.L.H., L.C.A.C., S.W. and G.Mc.N.). The RESAS programme had no role in the design, analysis or writing of this article. Conflict of interest: None. Authorship: J.L.H., L.C.A.C., S.W. and G.Mc.N. were responsible for the design of the study and formulated the research question. L.C.A.C. and S.W. carried out the study. J.L.H. completed the literature review, conducted the statistical analysis and drafted the initial paper. All authors were responsible for drafting and revising the manuscript and have approved the final version. Ethics of human subject participation: This study was conducted according to the guidelines laid down in the Declaration of Helsinki and all procedures involving human subjects were approved by the Rowett Human Studies Ethical Review Panel. Written informed consent was obtained from all participants.Peer reviewedPostprintPostprintPostprintPostprintPostprintPostprintPostprintPostprin

Acute Ethanol Administration Rapidly Increases Phosphorylation of Conventional Protein Kinase C in Specific Mammalian Brain Regions in Vivo

Background Protein kinase C (PKC) is a family of isoenzymes that regulate a variety of functions in the central nervous system including neurotransmitter release, ion channel activity, and cell differentiation. Growing evidence suggests that specific isoforms of PKC influence a variety of behavioral, biochemical, and physiological effects of ethanol in mammals. The purpose of this study was to determine whether acute ethanol exposure alters phosphorylation of conventional PKC isoforms at a threonine 674 (p-cPKC) site in the hydrophobic domain of the kinase, which is required for its catalytic activity. Methods Male rats were administered a dose range of ethanol (0, 0.5, 1, or 2 g/kg, intragastric) and brain tissue was removed 10 minutes later for evaluation of changes in p-cPKC expression using immunohistochemistry and Western blot methods. Results Immunohistochemical data show that the highest dose of ethanol (2 g/kg) rapidly increases p-cPKC immunoreactivity specifically in the nucleus accumbens (core and shell), lateral septum, and hippocampus (CA3 and dentate gyrus). Western blot analysis further showed that ethanol (2 g/kg) increased p-cPKC expression in the P2 membrane fraction of tissue from the nucleus accumbens and hippocampus. Although p-cPKC was expressed in numerous other brain regions, including the caudate nucleus, amygdala, and cortex, no changes were observed in response to acute ethanol. Total PKC? immunoreactivity was surveyed throughout the brain and showed no change following acute ethanol injection

A refined, rapid and reproducible high resolution melt (HRM)-based method suitable for quantification of global LINE-1 repetitive element methylation

<p>Abstract</p> <p>Background</p> <p>The methylation of DNA is recognized as a key mechanism in the regulation of genomic stability and evidence for its role in the development of cancer is accumulating. LINE-1 methylation status represents a surrogate measure of genome-wide methylation.</p> <p>Findings</p> <p>Using high resolution melt (HRM) curve analysis technology, we have established an in-tube assay that is linear (r > 0.9986) with a high amplification efficiency (90-105%), capable of discriminating between partcipant samples with small differences in methylation, and suitable for quantifying a wide range of LINE-1 methylation levels (0-100%)--including the biologically relevant range of 50-90% expected in human DNA. We have optimized this procedure to perform using 2 μg of starting DNA and 2 ng of bisulfite-converted DNA for each PCR reaction. Intra- and inter-assay coefficients of variation were 1.44% and 0.49%, respectively, supporting the high reproducibility and precision of this approach.</p> <p>Conclusions</p> <p>In summary, this is a completely linear, quantitative HRM PCR method developed for the measurement of LINE-1 methylation. This cost-efficient, refined and reproducible assay can be performed using minimal amounts of starting DNA. These features make our assay suitable for high throughput analysis of multiple samples from large population-based studies.</p

Decision problems with quantum black boxes

We examine how to distinguish between unitary operators, when the exact form of the possible operators is not known. Instead we are supplied with "programs" in the form of unitary transforms, which can be used as references for identifying the unknown unitary transform. All unitary transforms should be used as few times as possible. This situation is analoguous to programmable state discrimination. One difference, however, is that the quantum state to which we apply the unitary transforms may be entangled, leading to a richer variety of possible strategies. By suitable selection of an input state and generalized measurement of the output state, both unambiguous and minimum-error discrimination can be achieved. Pairwise comparison of operators, comparing each transform to be identified with a program transform, is often a useful strategy. There are, however, situations in which more complicated strategies perform better. This is the case especially when the number of allowed applications of program operations is different from the number of the transforms to be identified