Forecasting economic indicators using a consumer sentiment index: Survey‐based versus text‐based data

Given the confirmed effectiveness of the survey‐based consumer sentiment index (CSI) as a leading indicator of real economic conditions, the CSI is actively used in making policy judgments and decisions in many countries. However, although the CSI offers qualitative information for presenting current conditions and predicting a household's future economic activity, the survey‐based method has several limitations. In this context, we extracted sentiment information from online economic news articles and demonstrated that the Korean cases are a good illustration of applying a text mining technique when generating a CSI using sentiment analysis. By applying a simple sentiment analysis based on the lexicon approach, this paper confirmed that news articles can be an effective source for generating an economic indicator in Korea. Even though cross‐national comparative research results are suited better than national‐level data to generalize and verify the method used in this study, international comparisons are quite challenging to draw due to the necessary linguistic preprocessing. We hope to encourage further cross‐national comparative research to apply the approach proposed in this study.     

Robustness of alternative non‐linearity tests for SETAR models

In recent years there has been a growing interest in exploiting potential forecast gains from the non‐linear structure of self‐exciting threshold autoregressive (SETAR) models. Statistical tests have been proposed in the literature to help analysts check for the presence of SETAR‐type non‐linearities in an observed time series. It is important to study the power and robustness properties of these tests since erroneous test results might lead to misspecified prediction problems. In this paper we investigate the robustness properties of several commonly used non‐linearity tests. Both the robustness with respect to outlying observations and the robustness with respect to model specification are considered. The power comparison of these testing procedures is carried out using Monte Carlo simulation. The results indicate that all of the existing tests are not robust to outliers and model misspecification. Finally, an empirical application applies the statistical tests to stock market returns of the four little dragons (Hong Kong, South Korea, Singapore and Taiwan) in East Asia. The non‐linearity tests fail to provide consistent conclusions most of the time. The results in this article stress the need for a more robust test for SETAR‐type non‐linearity in time series analysis and forecasting. Copyright © 2004 John Wiley & Sons, Ltd.     

Observation of conformation-specific pathways in the photodissociation of 1-iodopropane ions.

Many molecules can rotate freely around single bonds and thereby interconvert between different conformations, such as gauche and anti 1,2-disubstituted ethane, a classic example of conformational isomerism. Even though rotation occurs rapidly at room temperature, the product selectivity seen in some reactions has been explained by conformation-dependent reaction mechanisms: if reactant molecules differing only in their conformation are located at different positions on the reaction path, they may undergo different reactions. But a direct verification of this effect is difficult, because the energy barrier separating conformational isomers is so low that under ambient conditions reactants with more than one conformation will be present. But by using temperatures low enough to suppress the interconversion between different conformations, gauche-1-iodopropane ions and anti-1-iodopropane ions have been selectively generated. Here we show that the kinetic energy released during the photodissociation of 1-iodopropane ions depends strongly on the conformation of the ions. Thermodynamic arguments and ab initio calculations indicate that this difference in kinetic energy release results from differences in the reaction mechanism, with gauche-1-iodopropane ions forming 2-propyl ions and anti-1-iodopropane ions forming protonated cyclopropane ions. These findings suggest that the well-known concept of conformation selection forms the basis of a simple scheme for reaction control, thus providing in some cases an attractive alternative for more involved schemes that utilize the phase and pulse shape of laser beams to control chemical reactions.     

Study on Approach for Computer-Aided Design and Machining of General Cylindrical Cam Using Relative Velocity and Inverse Kinematics

Cylindrical Cam Mechanism which is one of the best eq uipments to accomplish an accurate motion transmission is widely used in the fie lds of industries, such as machine tool exchangers, textile machinery and automa tic transfer equipments. This paper proposes a new approach for the shape design and manufacturing of the cylindrical cam. The design approach uses the relative velocity concept and the manufacturing approach uses the inverse kinematics concept. For the shape desig n, the contact points betw...     

Structural and Chemical Diversity of TI-Based Cuprate Superconductors

The first TI一based euprate supereonduetor,TI一Ba-Cu一(),was diseovered by 2.2.Sheng and A.M.Hermann仁1〕. TI beeomes supereondueting at 2.38 K.NumerousTI eompounds and alloys are supereondueting.TIMo6Ses has the highest transition temperature of1 2.2 K among all non一euprate Tl eontaining alloyand eompound supereonduetors.Before thediseovery of the euprate supereonduetors,some TIeontaining oxide supereonduetors were found,among whieh TI。.3W()3 has the highest transitiontemPerature,2.14 K. Sinee the diseovery of TI euPratesuPereonduetors,two distinet families have beenidentified.Soon after the diseovery of TI一Ba一Cu-(),supereonduetivity was eonfirmed in TI一Ba一Ca-Cu一()samples.The ehemieal eompositions anderystal struetures of those eompounds were workedout as T12BaZCu()6,T12BaZCaCuZ()。,andT12BaZCaZCu3OI。[2〕.This 15 the first family of TIeuPrate supereonduetors,whieh features two TIatoms in eaeh ehemieal formula.     

An Adaptive Multiscale Ensemble Learning Paradigm for Nonstationary and Nonlinear Energy Price Time Series Forecasting

For forecasting nonstationary and nonlinear energy prices time series, a novel adaptive multiscale ensemble learning paradigm incorporating ensemble empirical mode decomposition (EEMD), particle swarm optimization (PSO) and least square support vector machines (LSSVM) with kernel function prototype is developed. Firstly, the extrema symmetry expansion EEMD, which can effectively restrain the mode mixing and end effects, is used to decompose the energy price into simple modes. Secondly, by using the fine‐to‐coarse reconstruction algorithm, the high‐frequency, low‐frequency and trend components are identified. Furthermore, autoregressive integrated moving average is applicable to predicting the high‐frequency components. LSSVM is suitable for forecasting the low‐frequency and trend components. At the same time, a universal kernel function prototype is introduced for making up the drawbacks of single kernel function, which can adaptively select the optimal kernel function type and model parameters according to the specific data using the PSO algorithm. Finally, the prediction results of all the components are aggregated into the forecasting values of energy price time series. The empirical results show that, compared with the popular prediction methods, the proposed method can significantly improve the prediction accuracy of energy prices, with high accuracy both in the level and directional predictions. Copyright © 2016 John Wiley & Sons, Ltd.     

Forecasting Government Bond Yields with Neural Networks Considering Cointegration

This paper discusses techniques that might be helpful in predicting interest rates and tries to evaluate a new hybrid forecasting approach. Results of examining government bond yields in Germany and France reported in this study indicate that a hybrid forecasting approach which combines techniques of cointegration analysis with neural network (NN) forecasting models can produce superior results to the use of NN forecasting models alone. The findings documented in this paper could be a consequence of the fact that examining differenced data under certain conditions will lead to a loss of information and that the inclusion of the error correction term from the cointegration model can help to cope with this problem. The paper also discusses some possibly interesting directions for further research. Copyright © 2015 John Wiley & Sons, Ltd.     

Hybrid Forecasting with Estimated Temporally Aggregated Linear Processes

We introduce a new strategy for the prediction of linear temporal aggregates; we call it ‘hybrid’ and study its performance using asymptotic theory. This scheme consists of carrying out model parameter estimation with data sampled at the highest available frequency and the subsequent prediction with data and models aggregated according to the forecasting horizon of interest. We develop explicit expressions that approximately quantify the mean square forecasting errors associated with the different prediction schemes and that take into account the estimation error component. These approximate estimates indicate that the hybrid forecasting scheme tends to outperform the so‐called ‘all‐aggregated’ approach and, in some instances, the ‘all‐disaggregated’ strategy that is known to be optimal when model selection and estimation errors are neglected. Unlike other related approximate formulas existing in the literature, those proposed in this paper are totally explicit and require neither assumptions on the second‐order stationarity of the sample nor Monte Carlo simulations for their evaluation. Copyright © 2014 John Wiley & Sons, Ltd.     

BRD7 regulates the insulin-signaling pathway by increasing phosphorylation of GSK3β

Reduced hepatic expression levels of bromodomain-containing protein 7 (BRD7) have been suggested to play a role in the development of glucose intolerance in obesity. However, the molecular mechanism by which BRD7 regulates glucose metabolism has remained unclear. Here, we show that BRD7 increases phosphorylation of glycogen synthase kinase 3β (GSK3β) in response to activation of the insulin receptor-signaling pathway shortly after insulin stimulation and the nutrient-sensing pathway after feeding. BRD7 mediates phosphorylation of GSK3β at the Serine 9 residue and this effect on GSK3β occurs even in the absence of AKT activity. Using both in vitro and in vivo models, we further demonstrate that BRD7 mediates phosphorylation of ribosomal protein S6 kinase (S6K) and leads to increased phosphorylation of the eukaryotic translation initiation factor 4E-binding protein 1 (4E-BP1) and, therefore, relieves its inhibition of the eukaryotic translation initiation factor 4E (eIF4E). However, the increase in phosphorylation of 4E-BP1 with BRD7 overexpression is blunted in the absence of AKT activity. In addition, using liver-specific BRD7 knockout (LBKO) mice, we show that BRD7 is required for mTORC1 activity on its downstream molecules. These findings show a novel basis for understanding the molecular dynamics of glucose metabolism and suggest the unique function of BRD7 in the regulation of glucose homeostasis.