Price–volume cross-correlation analysis of CSI300 index futures

We investigate the cross-correlation between price returns and trading volumes for the China Securities Index 300 (CSI300) index futures, which are the only stock index futures traded on the China Financial Futures Exchange (CFFEX). The basic statistics suggest that distributions of these two time series are not normal but exhibit fat tails. Based on the detrended cross-correlation analysis (DCCA), we obtain that returns and trading volumes are long-range cross-correlated. The existence of multifractality in the cross-correlation between returns and trading volumes has been proven with the multifractal detrended cross-correlation analysis (MFDCCA) algorithm. The multifractal analysis also confirms that returns and trading volumes have different degrees of multifractality. We further perform a cross-correlation statistic to verify whether the cross-correlation significantly exists between returns and trading volumes for CSI300 index futures. In addition, results of the test for lead-lag effect demonstrate that contemporaneous cross-correlation of return and trading volume series is stronger than cross-correlations of leaded or lagged series.     

Duration and its application in continuous speech recognition

1IntroductiontraditionalHMM(HiddenMarkovModel)ishomogeneousMarkovprocess,itsstateselftransitionprobabilityailisaconstantindependentoftime.ThendurationTofstatesatisfyexponentialdistribution:Thisisinappropriateaccordingtothenatureofspeech.SincethisdefectoftraditionHMMiscognizedbypeople,theresearchondurationisthefocusinthefieldofspeechrecognition.Lotsofpapershavebeenpublishedininternationalconferencesandperiodicals,andmuchachievementhasbeedobtained.Followingarethemostimportantmethodsamongthe…     

Are developed and emerging agricultural futures markets multifractal? A comparative perspective

Although there are many reports on the empirical evidence of the existence of multifractality in various financial or commodity markets in current literature, few can be found to compare the multifractal properties of emerging and developed economies, especially for agricultural futures markets in those countries (regions). We therefore chose China as the representative of the transition and emerging economies, and USA as the representative of developed ones. We attempt to find the answers to the following questions: (1) Are all those different markets multifractal? (2) What are the dynamical causes for multifractality in those markets (if any)? (3) Are the multifractality strengths in those markets of the transition and emerging economies weaker (or stronger) than those of the developed ones? To answer these questions, Multifractal Detrended Fluctuation Analysis (MF-DFA) are applied to study some of the representative agricultural futures markets in China and USA, namely, wheat, soy meal, soybean and corn. Our results suggest that all the markets of China and USA exhibit multifractal properties except US soybean market, which is much closer to mono-fractal comparing with China’s soybean market. To investigate the sources of multifractality, shuffling and phase randomization procedures are applied to destroy the temporal correlations and non-Gaussian distributions respectively. We found that multifractality can be mainly attributed to the non-Gaussian probability distribution and secondarily to the nonlinear temporal correlation mechanism for all the markets, except US soybean and soy meal, which derives from some other unknown factors. Furthermore, the average of τ(q) are applied to obtain the multifractal spectra of the two markets as a whole. The results show that the width of the multifractal spectrum of US agricultural futures markets is significantly narrower than that of China’s. Based on our findings, we proposed a hypothesis that the strength of multifractality in developed economies may be weaker than that in emerging and transition ones.     

Are crude oil markets multifractal? Evidence from MF-DFA and MF-SSA perspectives

In this article, we investigated the multifractality and its underlying formation mechanisms in international crude oil markets, namely, Brent and WTI, which are the most important oil pricing benchmarks globally. We attempt to find the answers to the following questions: (1) Are those different markets multifractal? (2) What are the dynamical causes for multifractality in those markets (if any)? To answer these questions, we applied both multifractal detrended fluctuation analysis (MF-DFA) and multifractal singular spectrum analysis (MF-SSA) based on the partition function, two widely used multifractality detecting methods. We found that both markets exhibit multifractal properties by means of these methods. Furthermore, in order to identify the underlying formation mechanisms of multifractal features, we destroyed the underlying nonlinear temporal correlation by shuffling the original time series; thus, we identified that the causes of the multifractality are influenced mainly by a nonlinear temporal correlation mechanism instead of a non-Gaussian distribution. At last, by tracking the evolution of left- and right-half multifractal spectra, we found that the dynamics of the large price fluctuations is significantly different from that of the small ones. Our main contribution is that we not only provided empirical evidence of the existence of multifractality in the markets, but also the sources of multifractality and plausible explanations to current literature; furthermore, we investigated the different dynamical price behaviors influenced by large and small price fluctuations.     

Bi-mel-scale frequency cepstrum and its application in telephone speech recognition

1IntroductionVariouskindsoffeatureshaveeverbeenusedforspeechrecognition.Thesefeaturesmaybesplitintothreegroups'(l)thetimedomainbasedfeatures,suchaszero-crossingnum-ber,short-timeenergy,peakamplitude,pitchperiod,andautocorrelationcoefficients,(2)thespectraldomainbasedparameters,suchformants,spectrum,powerspectrum,LinearPredic-tionCoefficients(LPC),andpolesoftheLPCspectrum;and(3)thecepstraldomainbasedfeatures,suchasLinearPredicationCepstrumCoefficents(LPCC),Mel-scaleFrequencyCep-strumCoe…     

Auditory model inversion and its application

Auditory model has been applied to several aspects of speech signal processing field, and appears to be effective in performance. This paper presents the inverse transform of each stage of one widely used auditory model. First of all it is necessary to invert correlogram and reconstruct phase information by repetitious iterations in order to get auditory-nerve firing rate. The next step is to obtain the negative parts of the signal via the reverse process of the HWR (Half Wave Rectification). Finally the functions of inner hair cell/synapse model and Gammatone filters have to be inverted. Thus the whole auditory model inversion has been achieved. An application of noisy speech enhancement based on auditory model inversion algorithm is proposed. Many experiments show that this method is effective in reducing noise. Especially when SNR of noisy speech is low it is more effective than other methods. Thus this auditory model inversion method given in this paper is applicable to speech enhancement field.     

Comment on ‘multifractal diffusion entropy analysis on stock volatility in financial markets’ [Physica A 391 (2012) 5739–5745]

In their recent article ‘multifractal diffusion entropy analysis on stock volatility in financial markets’ Huang, Shang and Zhao (2012) [6] suggested a generalization of the diffusion entropy analysis method with the main goal of being able to reveal scaling exponents for multifractal times series. The main idea seems to be replacing the Shannon entropy by the Rényi entropy, which is a one-parametric family of entropies. The authors claim that based on their method they are able to separate long range and short correlations of financial market multifractal time series. In this comment I show that the suggested new method does not bring much valuable information in obtaining the correct scaling for a multifractal/mono-fractal process beyond the original diffusion entropy analysis method. I also argue that the mathematical properties of the multifractal diffusion entropy analysis should be carefully explored to avoid possible numerical artefacts when implementing the method in analysis of real sequences of data.     

High-reflectivity non-periodic sub-wavelength gratings with small-angle beam-steering ability and its application in Fabry–Perot cavity

We report a high-reflectivity non-periodic sub-wavelength gratings (SWGs) mirror with small-angle beam-steering ability for reflect light. It presents a distinctive characteristic of flexibly controlling the width of oscillation optical field for the improved Fabry–Perot (F–P) cavity. We propose a detailed principle analysis of the improved cavity. By finding out a set of SWGs with the designed structural parameters, both high reflectivity (>?93%) and beam steering (1°) can be implemented. By setting beam-steering angle and cavity length, we can control the width of oscillation optical field in the improved cavity. Beam steering ability and property of controlling the oscillation width are numerically investigated by finite element method. Simulation results prove that cavity length and steering angle can effectively control the main width of oscillation optical field, and the width is linearly associated with the cavity length.     

Empirical study of the scaling behavior of the amplitude–frequency distribution of the Hilbert–Huang transform and its application in sunspot time series analysis

Investigating long-range correlation by the Hurst exponent, H$H$, is crucial in the study of time series. Recently, empirical-mode-decomposition-based arbitrary-order Hilbert spectral analysis (EMD-HSA) has been proposed to numerically obtain without proof a scaling relationship, generated from the amplitude–frequency distribution, related to H$H$. We propose a formalism to empirically study EMD-HSA, to deduce its scaling exponent ξ(q)$\xi \left(q\right)$ from the perspective of EMD-based arbitrary-order Hilbert marginal spectrum (EMD-HMS), and to numerically compare the results with the expected H$H$. EMD-HSA and EMD-HMS experiments show that, by incompletely removing (quasi-)periodic trends, the sunspot series should have an H$H$ value around 0.12.     

Theory of multinonlinear media and its application to the soliton processes in ferrite–ferroelectric structures

A theory is developed to describe the wave processes that occur in waveguide media having several types of nonlinearity, specifically, multinonlinear media. It is shown that the nonlinear Schrödinger equation can be used to describe the general wave process that occurs in such media. The competition between the electric wave nonlinearity and the magnetic wave nonlinearity in a layered multinonlinear ferrite–ferroelectric structure is found to change a total repulsive nonlinearity into a total attractive nonlinearity.     

Dynamics of bid–ask spread return and volatility of the Chinese stock market

The bid–ask spread is taken as an important measure of the financial market liquidity. In this article, we study the dynamics of the spread return and the spread volatility of four liquid stocks in the Chinese stock market, including the memory effect and the multifractal nature. By investigating the autocorrelation function and the Detrended Fluctuation Analysis (DFA), we find that the spread return is the lack of long-range memory, while the spread volatility is long-range time correlated. Besides, the spread volatilities of different stocks present long-range cross-correlations. Moreover, by applying the Multifractal Detrended Fluctuation Analysis (MF-DFA), the spread return is observed to possess a strong multifractality, which is similar to the dynamics of a variety of financial quantities. Different from the spread return, the spread volatility exhibits a weak multifractal nature.     

An extended functional transformation method and its application in some evolution equations

In this paper, an extended functional transformation is given to solve some nonlinear evolution equations. This function, in fact,is a solution of the famous KdV equation, so this transformation gives a transformation between KdV equation and other soliton equations. Then many new exact solutions can be given by virtue of the solutions of KdV equation.     

Formation of high density TiN nanocrystals and its application in non-volatile memories

Non-volatile memory based on TiN nanocrystal （TiN-NC） charge storage nodes embedded in SiO2 has been fabricated and its electrical properties have been measured. It was found that the density and size distribution of TiN-NCs can be controlled by annealing temperature. The formation of well separated crystalline TiN nano-dots with an average size of 5 nm is confirmed by transmission electron microscopy and x-ray diffraction, x-ray photoelectron spectroscopy confirms the existence of a transition layer of TiNxOy/SiON oxide between TiN-NC and SiO2, which reduces the barrier height of tunnel oxide and thereby enhances programming/erasing speed. The memory device shows a memory window of 2.5V and an endurance cycle throughout 10^5. Its charging mechanism, which is interpreted from the analysis of programming speed （dVth/dt） and the gate leakage versus voltage characteristics （Ig vs Vg）, has been explained by direct tunnelling for tunnel oxide and Fowler Nordheim tunnelling for control oxide at programming voltages lower than 9V, and by Fowler-Nordheim tunnelling for both the oxides at programming voltages higher than 9V.     

The PNO–MP2 gradient and its application to molecular geometry optimisations

A preliminary implementation of a gradient for MP2 based on the pair natural orbital approximation (PNO–MP2) is presented. The accuracy of the PNO approximation for geometries is investigated by comparing bond lengths and bond angles of the PNO–MP2 structures with results from canonical MP2. Special emphasis is put on the optimisation of weakly bound complexes, such as differently sized water clusters. It is found that the error introduced by the PNO approximation is already for moderate PNO thresholds negligible compared to the inherent error of MP2. However, too loose PNO thresholds lead to convergence difficulties in geometry optimisations. This is observed in particular for floppy groups as, for example, methyl groups with low rotational barriers. Compared to optimisations with canonical MP2, the convergence thresholds have to be mainly energy and less coordinate based to comply with the slight roughness of the potential energy surface which is introduced by the PNO selection.     

Microplasma generated at solid–solid interface and its application to nanostructure formation

The dynamics of the microplasmas created at a transparent solid–solid interface were investigated extensively. Microplasmas were generated at an interface between a carbon (C) or a germanium (Ge) target and a SiO₂ substrate by irradiating a KrF excimer laser beam onto the target, and the dynamics of the plasmas were investigated with the aid of optical emission spectroscopy. Although the emission spectra that contained the characteristic emission lines and the absorption bands originated from C and Ge species were observed from the C and Ge plasmas without the SiO₂ substrate, identical spectra were obtained from both the plasmas created at the C–SiO₂ and Ge–SiO₂ interfaces. Furthermore, the target and the Si substrate surfaces were examined with a scanning electron microscope. The SiO₂ substrate was smoothly etched and a nanostructure of a chain-like morphology was also observed in the deposits on the SiO₂ substrate.     

Surface and volume waves in ferrodielectric–magnetically active material structures

The propagation of surface waves along the interface between a ferrodielectric and a material that represents an array of amorphous ferromagnetic microwires has been studied. The dispersion characteristic of a magnetically controlled TE wave has been obtained, and frequency intervals have been found in which surface or localized, partially localized, and volume waves may exist. It has been shown that a TM wave in the given structure cannot be a surface wave.     

Characteristics of holographic scattering and its application in determining kinetic parameters in PQ-PMMA photopolymer

This paper characterizes holographic scattering and demonstrates its application in determining the kinetic parameters in materials with high transmittance and strong holographic scattering like phenanthrenequinone doped poly (methyl methacrylate) (PQ-PMMA). We define a polymerization rate parameter which can be determined by the temporal evolution of the scattering losses. Two basic kinetic parameters, quantum yield and molar-absorption coefficient, are obtained by nonlinear fitting the curve of the polymerization rate parameter as a function of the thickness, which are 1.9×10⁻⁶ mol/einstein and 2.1×10⁴ cm²/mol for a wavelength of 532 nm respectively. These results improve the understanding of photochemical behaviors and allow us to describe the grating formation in the photopolymer reasonably.     

Synthesis and characterization of Ni(II) complex functionalized silica-based magnetic nanocatalyst and its application in C–N and C–C cross-coupling reactions

Molecular Diversity - A new magnetically recoverable silica-based nickel(II) nanocatalyst was synthesized by a simple cost-effective procedure, which was characterized by TEM, SEM, XRD, VSM...     

A new relativistic viscous hydrodynamics code and its application to the Kelvin–Helmholtz instability in high-energy heavy-ion collisions

The European Physical Journal C - It has been shown that the thin brane model in a five-dimensional Weyl gravity can deal with the wrong-signed Friedmann-like equation in the...