Analysis of financial stock markets through multidimensional scaling based on information measures

In this paper, a novel multidimensional scaling (MDS) based on information measures method is proposed to analyze financial stock markets. In order to examine the effectiveness of this method, we applied it to the classification of two types of artificial series, the logistic map model and the cubic map model, as well as stock time series. Moreover, the traditional MDS using Euclidean dissimilarity is also provided as a reference for comparisons. The results show that the MDS based on information measures can give us more detailed, exact and clearer information on the classification of simulation series and stock time series than the MDS using Euclidean dissimilarity. In addition, the proposed graphical method may also assist in the construction of multivariate econometric models.     

The effect of interfacial miscibility on the cell morphology of polyethylene terephthalate/bisphenol a polycarbonate blend foams

Annealing polyethylene terephthalate (PET)/polycarbonate (PC) blends enhance the transesterification reaction and increase the amount of copolymer at the interface of both polymers. The copolymer enhances the compatibility of PET with PC, because it contains both PET and PC blocks, which causes the interface between PET and PC to become fuzzy. When the PET/PC undergoes batch physical foaming with CO₂, the copolymer significantly changes the resulting cell morphology, that is, the annealing time. Before annealing or in the absence of the copolymer, bubble nucleation occurs and dominates growth at the interface. When the PET/PC blends are annealed, the interface impedes bubble nucleation and growth. The polymer is stretched at the interface by bubble growth, forming fibril‐like structures connecting two polymer domains at the interface. Increased annealing time causes the interface to become more homogeneous and makes heterogeneous bubble nucleation difficult. At higher copolymer concentrations, the interface of PET and PC becomes fuzzy and the cell morphology becomes like those of foamed homogeneous polymers. © 2012 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys, 2012     

Improved electrochemical performance of nano-crystalline Li2FeSiO4/C cathode material prepared by the optimization of sintering temperature

Li₂FeSiO₄/C cathode materials have been prepared using the conventional solid-state method by varying the sintering temperature (650 °C, 700 °C and 750 °C), and the structure and electrochemical performance of Li₂FeSiO₄/C materials are investigated by X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), galvanostatic charge–discharge tests, respectively. The results show that Li₂FeSiO₄ nano-crystals with a diameter of about 6–8 nm are inbedded in the amorphous carbon, and the Li₂FeSiO₄/C material obtained at 700 °C exhibits an initial discharge capacity of 195 mA?h g^?1 at 1/16 C in the potential range of 1.5–4.8 V. The excellent electrochemical performance of Li₂FeSiO₄/C attributes to the improvement of conductivity and reduction of impurity by the optimization of the sintering temperature.     

The application of Hölder exponent to traffic congestion warning

In this paper, we applied multifractal modeling techniques to analyze the traffic data collected from the Beijing Yuquanying. The results indicated that multifractal characteristics obviously exist in the traffic system; the degree of fractality of these traffic data tends to increase as the traffic system becomes congested; the Hölder exponent that measures the local rate of fractality may be used as indicators to predict the presence of the traffic congestion.     

A multifunctional silicotungstic acid-modified Li-rich manganese-based cathode material with excellent electrochemical properties

Journal of Solid State Electrochemistry - Li-rich layered oxide (LrLO) cathode has attracted much attention for Li-ion batteries in recent years due to its superior capacity of exceeding...     

Fractional empirical mode decomposition energy entropy based on segmentation and its application to the electrocardiograph signal

In this paper, based on the Hirota bilinear method, a kind of lump solutions and two classes of interaction solutions are discussed to the \((2+1)\)-dimensional generalized KdV equation with the aid of symbolic computation system Mathematica. Analyticity is naturally guaranteed by taking special choices of the involved parameters to achieve a positive constant term. Particularly, these solutions with special values of the included parameters are plotted, as illustrative example.     

Topological entropy and geometric entropy and their application to the horizontal visibility graph for financial time series

Seismic wave control is very important both in civil and mechanical engineering. Common passive methods for isolating a building or a device include base isolators and tuned mass dampers. In the present paper, a time-varying controllable spring is considered as a vibration isolator for a linear mechanical system. The controller works as follows: When the seismic movement is active, the velocity of the moving mass is monitored as the reference velocity. When such reference velocity is positive, the stiffness is reduced; when it is negative, the stiffness is increased. Numerical investigations show that the controller is capable of filtering seismic excitation close to the natural frequency of the controlled system and reducing the total seismic energy transfer up to 5 times. The role played by the gravity in the active vibration filtering is pointed out by showing that no filtering action can be observed in gravity-free simulations. Moreover, control effectiveness has been proven for a measured seismic signal, showing its robustness in presence of noise.     

The cross-correlations of stock markets based on DCCA and time-delay DCCA

In this paper, the Detrended Fluctuation Analysis (DFA) and Detrended Cross-Correlation Analysis (DCCA) are used to investigate the stock markets. The DFA method is a widely-used method for the determination and detection of long-range correlations in stock time series. DCCA is a recently developed method to quantify the cross-correlations of two non-stationary time series. We report the results of correlation and cross-correlation behaviors in US and Chinese stock markets by using the DFA and DCCA methods, respectively. The DCCA shows that there exists some crossovers in the cross-correlation fluctuation function versus time scale of stock absolute returns. The cross-correlations in Chinese stock markets are stronger than those between Chinese and US stock markets. After documenting the equal-time cross-correlations using DCCA method, we study the dynamics of cross-correlations of stock series based on a time-delay. The time-dependence of the underlying cross-correlations is monitored using a time window by step of 1 day. An interesting finding is that the cross-correlation exponents and crossovers demonstrate periodical uncertainty changing with the time-delay.     

Multifractal Detrended Cross-Correlation Analysis of BVP model time series

The Bonhoeffer?Cvan der Pol (BVP) oscillator has widely application in the modeling of biological processes, and it also has rich nonlinear behavior including different topological properties between the continuous-time BVP oscillator and the discrete one. Multifractal Detrended Cross-Correlation Analysis (MF-DCCA) has proved useful in describing the correlations and detecting the scaling exponent of time series. We investigate the autocorrelations and cross-correlations of the time series in BVP model by using the MF-DCCA method. Our results show that there exist long range autocorrelations and cross-correlations in the BVP model time series, and that multifractal features are significant in the analyzed BVP model.