Proxying for Expected Returns with Price Earnings Ratios

Long-run regression models using the trailing earnings over price ratio to predict future returns suggested by Campbell and Shiller (1988, 2001) work quite well. However, in this note we show that this variable might result in a downward biased proxy for expected future returns. Instead we suggest using a moving average of the log of 1 plus the earnings price ratio when forecasting long-run returns. The empirical results for the S&P 500 show the superiority of our approach to existing ones.Earnings yield, Stock Return, Forecasting

Long-Run Regressions: Theory and Application to US Asset Markets

The question of long-run predictability in the aggregate US stock market is still unsettled. This is due to the lack of a robust method to judge the statistical significance of long-run regressions under the maintained hypothesis. By developing a spectral theory of long-run regressions with both long-run dependent and independent variables, we demonstrate a version of Engle's (1974) conjecture that asymptotically correct standard errors can be computed by multiplying the ordinary least squares standard errors by the square root of 2/3 times the length of the forecast horizon. We generalize Stambaugh's (1999) bias formula to the long-run regression model proposed in this paper. In addition, we find, that for persistent predictive variables, the OLS estimator in our regression model is more efficient than the estimator in the predictive regressions suggested by Campbell and Shiller (1988) and Hodrick (1992). Application of our method shows thatthe long-run earnings yield significantly predicts up to 69% of the variation in the 10-year S&P 500 real return, and up to 49% of long-run bond returns.Forecasting, stock returns, spectral analysis, Hansen-Hodrick standard errors

A Computational Study of the Distribution of Particles in a Lab-Scale CFB Boiler

When two-fluid modeling is used to predict riser flows there have been difficulties in predicting the solids hold up in risers represented by the correct pressure drop profile. A way of encountering this inherent problem in current Eulerian-Eulerian CFD modeling is to approximate the actual particle size distribution by using more particle phases instead of the current practice of using one mean diameter. For the lab-scale CFB investigated, CFD simulations show that a mal-distribution occurs in the CFB; the larger particles are retained in the riser, whereas the intermediate and small particles are distributed both in the return leg and the riser. Simulations using an altered particle size distribution, i.e. a larger amount of large particles, show significant improvements in the pressure profile in the bottom part of the riser

A Survey and Taxonomy of Core Concepts and Research Challenges in Cross-Platform Mobile Development

Developing applications targeting mobile devices is a complex task involving numerous options, technologies and trade-o s, much so due to the proliferation and fragmentation of devices and platforms. As a result of this, cross-platform app development has enjoyed the attention of practitioners and academia for the previous decade. Throughout this review, we assess the academic body of knowledge and report on the state of research on the eld. We do so with a particular emphasis on core concepts, including those of user experience, device features, performance, and security. Our ndings illustrate that the state of research demand for empirical veri cation of an array of unbacked claims, and that a particular focus on qualitative user-oriented research is essential. Through our outlined taxonomy and state of research overview, we identify research gaps and challenges, and provide numerous suggestions for further researc

Global gene expression profiling of brown to white adipose tissue transformation in sheep reveals novel transcriptional components linked to adipose remodeling

BACKGROUND: Large mammals are capable of thermoregulation shortly after birth due to the presence of brown adipose tissue (BAT). The majority of BAT disappears after birth and is replaced by white adipose tissue (WAT). RESULTS: We analyzed the postnatal transformation of adipose in sheep with a time course study of the perirenal adipose depot. We observed changes in tissue morphology, gene expression and metabolism within the first two weeks of postnatal life consistent with the expected transition from BAT to WAT. The transformation was characterized by massively decreased mitochondrial abundance and down-regulation of gene expression related to mitochondrial function and oxidative phosphorylation. Global gene expression profiling demonstrated that the time points grouped into three phases: a brown adipose phase, a transition phase and a white adipose phase. Between the brown adipose and the transition phase 170 genes were differentially expressed, and 717 genes were differentially expressed between the transition and the white adipose phase. Thirty-eight genes were shared among the two sets of differentially expressed genes. We identified a number of regulated transcription factors, including NR1H3, MYC, KLF4, ESR1, RELA and BCL6, which were linked to the overall changes in gene expression during the adipose tissue remodeling. Finally, the perirenal adipose tissue expressed both brown and brite/beige adipocyte marker genes at birth, the expression of which changed substantially over time. CONCLUSIONS: Using global gene expression profiling of the postnatal BAT to WAT transformation in sheep, we provide novel insight into adipose tissue plasticity in a large mammal, including identification of novel transcriptional components linked to adipose tissue remodeling. Moreover, our data set provides a useful resource for further studies in adipose tissue plasticity. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-015-1405-8) contains supplementary material, which is available to authorized users

Cystic fibrosis–adapted Pseudomonas aeruginosa quorum sensing lasR mutants cause hyperinflammatory responses

Cystic fibrosis lung disease is characterized by chronic airway infections with the opportunistic pathogen Pseudomonas aeruginosa and severe neutrophilic pulmonary inflammation. P. aeruginosa undergoes extensive genetic adaptation to the cystic fibrosis (CF) lung environment, and adaptive mutations in the quorum sensing regulator gene lasR commonly arise. We sought to define how mutations in lasR alter host-pathogen relationships. We demonstrate that lasR mutants induce exaggerated host inflammatory responses in respiratory epithelial cells, with increased accumulation of proinflammatory cytokines and neutrophil recruitment due to the loss of bacterial protease–dependent cytokine degradation. In subacute pulmonary infections, lasR mutant–infected mice show greater neutrophilic inflammation and immunopathology compared with wild-type infections. Finally, we observed that CF patients infected with lasR mutants have increased plasma interleukin-8 (IL-8), a marker of inflammation. These findings suggest that bacterial adaptive changes may worsen pulmonary inflammation and directly contribute to the pathogenesis and progression of chronic lung disease in CF patients