Cross-correlation Properties Research Articles

Does the weather affect the Chinese stock markets? Evidence from the analysis of DCCA cross-correlation coefficient

Recent studies confirm that weather affects the Chinese stock markets, based on a linear model. This paper revisits this topic using DCCA cross-correlation coefficient (ρDCCA(n)), which is a nonlinear method, to determine if weather variables (i.e., temperature, humidity, wind and sunshine duration) affect the returns/volatilities of the Shanghai and Shenzhen stock markets. We propose an asymmetric ρDCCA(n) by improving the traditional ρDCCA(n) to determine if different cross-correlated properties exist when one time series trending is either positive or negative. Further, we improve a statistical test for the asymmetric ρDCCA(n). We find that cross-correlation exists between weather variables and the stock markets on certain time scales and that the cross-correlation is asymmetric. We also analyze the cross-correlation at different intervals; that is, the relationship between weather variables and the stock markets at different intervals is not always the same as the relationship on the whole.

Performance Analysis of New Binary User Codes for DS-CDMA Communication

This paper analyzes new binary spreading codes through correlation properties and also presents their performance over additive white Gaussian noise (AWGN) channel. The proposed codes are constructed using gray and inverse gray codes. In this paper, a n-bit gray code appended by its n-bit inverse gray code to construct the 2n-length binary user codes are discussed. Like Walsh codes, these binary user codes are available in sizes of power of two and additionally code sets of length 6 and their even multiples are also available. The simple construction technique and generation of code sets of different sizes are the salient features of the proposed codes. Walsh codes and gold codes are considered for comparison in this paper as these are popularly used for synchronous and asynchronous multi user communications respectively. In the current work the auto and cross correlation properties of the proposed codes are compared with those of Walsh codes and gold codes. Performance of the proposed binary user codes for both synchronous and asynchronous direct sequence CDMA communication over AWGN channel is also discussed in this paper. The proposed binary user codes are found to be suitable for both synchronous and asynchronous DS-CDMA communication.

The coupling analysis of stock market indices based on cross-permutation entropy

It is an interesting subject to analyze the coupling dependence between time series. Many information-theoretic methods have been proposed for this purpose. In this article, we propose a new permutation-based entropy for the detection of coupling structures between stock markets. It is inspired by inner composition alignment method that we use the number of crossing points instead of mode \(\pi \) in permutation entropy definition to define the probability distribution. The measure is named as cross-permutation entropy (CPE), and can be used to infer the cross-correlation properties as well as the direction of couplings. The capabilities of CPE to correctly infer couplings together with their directionality are compared against transfer entropy for artificial signals as well as stock market time series. The results show that CPE is efficient in the analysis of cross-correlation between signals. Besides, in the analysis of financial time series, we found the coupling between stock markets in a same country are generally stronger than what would be expected from different countries.

Alleviation Interference Scheme Analysis Using Flexible Cross Correlation (FCC) Code for SAC-OCDMA Systems

This paper presents a new Alleviation Interference Scheme (AIS) for Spectral Amplitude Coding (SAC) - Optical Code Division Multiple Access (OCDMA) coding approaches. The AIS SAC-OCDMA systems is demonstrated by utilizing the Flexible Cross Correlation (FCC) code. The FCC code has advantages, such as flexible cross-correlation property at any given number of users and weights, as well as effectively reduces the impacts of phase induced intensity noise (PIIN) and multiple-access interference (MAI). The results indicated good performance whereas the FCC code offers 100%, 207% and 471% percentage larger number of active users compared to MDW W=4, Hadamard and MFH W=8 codes, respectively. Finally, the FCC code has low receive power Psr = -18 dBm which is expected to be more significant for future SAC-OCDMA coding systems.

Sequence Design for Cognitive CDMA Communications under Arbitrary Spectrum Hole Constraint

To support interference-free quasi-synchronous code-division multiple-access (QS-CDMA) communication with low spectral density profile in a cognitive radio (CR) network, it is desirable to design a set of CDMA spreading sequences with zero-correlation zone (ZCZ) property. However, traditional ZCZ sequences (which assume the availability of the entire spectral band) cannot be used because their orthogonality will be destroyed by the spectrum hole constraint in a CR channel. To date, analytical construction of ZCZ CR sequences remains open. Taking advantage of the Kronecker sequence property, a novel family of sequences (called "quasi-ZCZ" CR sequences) which displays zero cross-correlation and near-zero auto-correlation zone property under arbitrary spectrum hole constraint is presented in this paper. Furthermore, a novel algorithm is proposed to jointly optimize the peak-to-average power ratio (PAPR) and the periodic auto-correlations of the proposed quasi-ZCZ CR sequences. Simulations show that they give rise to single-user bit-error-rate performance in CR-CDMA systems which outperform traditional non-contiguous multicarrier CDMA and transform domain communication systems; they also lead to CR-CDMA systems which are more resilient than non-contiguous OFDM systems to spectrum sensing mismatch, due to the wideband spreading.

Localization and Tracking of Objects Using Cross-Correlation of Shadow Fading Noise

Multipath and shadow fading are the primary cause for positioning errors in a Received Signal Strength Indicator (RSSI) based localization scheme. While fading, in general, is detrimental to localization accuracy, cross-correlation and divergence properties of shadow fading residuals may be utilized to improve localization and tracking accuracy of mobile IEEE 802.15.4 transmitters. Therefore, this paper begins by presenting a stochastic filter that models the fast changing multipath fading as a mean reverting Ornstein-Uhlenbeck (OU) process followed by a Generalized Auto Regressive Conditional Heteroskedasticity (GARCH) filtering to isolate the slow changing shadow fading residuals from measured RSSI values. Subsequently, a novel wireless transmitter localization scheme that combines the measured cross-correlation in shadow fading residuals between adjacent receivers using a Student-t Copula likelihood function is proposed. However, the long convergence time for this highly non-convex copula function might render our method unsuitable for tracking applications. Therefore, we present a faster tracking method where the velocity and heading of a mobile transmitter are estimated from α-Divergence between shadow fading signals and an onboard gyroscope respectively. To bind the localization error in this tracking method, the transmitter location estimates are smoothed by a Bayesian particle filter. The performance of our proposed localization and tracking method is validated over simulations and hardware experiments.

Asymmetric multiscale detrended cross-correlation analysis of financial time series

We propose the asymmetric multiscale detrended cross-correlation analysis (MS-ADCCA) method and apply MS-ADCCA method to explore the existence of asymmetric cross-correlation for daily price returns in US and Chinese stock markets and to assess the properties of these asymmetric cross-correlations. The results all show the existences of asymmetric cross-correlations, while small asymmetries at small scales and larger asymmetries at larger scales are also displayed. There is a strong similarity between S&P500 and DJI, and we reveal that the asymmetries depend more on the cross-correlations of S&P500 vs. DJI, S&P500 vs. NQCI, DJI vs. NQCI, and ShangZheng vs. ShenCheng when the market is falling than rising, respectively. By comparing the spectra of S&P500 vs. NQCI and DJI vs. NQCI with uptrends and downtrends, we detect some new characteristics which lead to some new conclusions. Likewise, some new conclusions also can be drawn by the new characteristics displayed through the comparison between the spectra of ShangZheng vs. HSI and ShenCheng vs. HSI. Obviously, we conclude that although the overall spectra are similar and one market has the same effect when it is rising and falling in the study of asymmetric cross-correlations between it and different markets, the cross-correlations and asymmetries on the trends of the different markets are all different. MS-ADCCA method can detect the differences on the asymmetric cross-correlations by different trends of markets. Moreover, the uniqueness of cross-correlation between NQCI and HSI can be detected in the study of the asymmetric cross-correlations, which confirms that HSI is unique in the Chinese stock markets and NQCI is unique in the US stock markets further.

Detrended cross-correlation analysis of temperature, rainfall, PM10 and ambient dioxins in Hong Kong

Using detrended cross-correlation analysis (DCCA), we investigate the long-term influence of some factors, specifically precipitation, average temperature and PM10 concentrations on the evolution of Polychlorinated dibenzo-p-dioxins (PCDDs) and dibenzofurans (PCDFs) concentrations in Hong Kong. The 15 years regular monitoring data from two general urban sites, Central/Western District and Tsuen Wan, are analyzed. The results show that the relationships between ambient dioxins and precipitation (or PM10) display long-term cross-correlation at the time scale ranging from one month to one year; while, no cross-correlation with each other have observed in longer temporal scaling regimes (greater than one year). Meantime, differentiated from the previous study, we found that precipitation has the greatest influence on ambient PCDD/PCDFs at the long-term time scaling (about one year) in Hong Kong. And no significant relationships are found between ambient dioxins and average temperature at long-term time scale. These results correspond to atmospheric circulation and regional transport hypothesis and are explained in detail. The long-term cross-correlation property is discussed further, considering the strong influence of the Asian monsoon system.

Computational design of optimal waveforms for MIMO radar via multi-dimensional iterative spectral approximation

We propose an approach to design waveform sets with good auto- and cross-correlation properties. The designed waveform sets can be used for multiple-input multiple-output radars to minimize the cross-interference, and consequently improve the radar performance. Firstly, we transform the original correlation optimization problem into a spectral approximation problem. Secondly, we define the objective function based on the square error between the designed waveform matrix and the ideal one. Finally, the problem is solved by using an algorithm based on alternating projection and phase retrieval. We further improve the proposed method, and derive an extended version to design waveforms with sparse spectrum and good correlation property for combating electronic jamming. The algorithms are computationally efficient because their main steps are based on fast Fourier transform. The effectiveness of the proposed approach is demonstrated by numerical simulations.

미디어 인게이지먼트의 효과를 활용한 정치캠페인의 전략 연구

본 연구는 미디어 인게이지먼트의 개념을 적용하여 정치캠페인에 적용할 수 있는 모델로서, 정치후보자를 지지하는 유권자의 표심을 읽어보고자 2012년 12.19, 18대 대통령선거(서울 외 12개 지역)와 2013년 4.24 재보궐 선거에서 총 선거권을 가진 유권자 729명을 대상으로 피플미터 CATI프로그램을 활용한 전화조사였다. 연구문제는 미디어 인게이지먼트 5개 속성(관심,몰입,연관,참여,만족)간 상관성과 사회경제적 차이와 매체이용 등이 이들의 5개 속성에 조절변수(moderating variable)역할을 하는 가를 분석했다. 분석결과 미디어 인게이지먼트의 5개 속성요인의 인과적 상관관계에서 연관성이 중요한 매개변수(mediating variable)역할의 변수라는 점이 밝혀졌다. 또한 매체(TV, SNS, 인쇄매체)이용정도와 사회경제적 지위(성별, 연령, 소득, 결혼, 직업, 지역)과 관여도, 그리고 대통령선거와 보궐선거 등이 미디어 인게이지먼트의 5개 속성에 조절효과가 있다는 점을 추론할 수 있다. 본 연구결과는 정치캠페인효과를 측정할 수 있는 연구모형으로 정치, 선거, 미디어, 광고 홍보영역 발전도모는 물론 학제간 융합연구에도 크게 기여할 수 있을 것이다. This study is the first model to apply the concept of media engagement to a political campaign by which the voters' mind toward the supporting political candidates, are read. Thus it provides the theoretical and practical implications to the political campaign, and eventually contributes to the development of democracy. For these objectives, the total of 729 people who have the right to vote were telephone surveyed using the peoplemeter, CATI program in the 18th Presidential Election (12 areas including Seoul) of Dec. 19th 2012, and Re and By-election of April 24th 2013. Research question is to examine how the 5 attributes of the media engagement (interest, immersion, relevance, satisfaction and participation), play a role as the moderating variables in cross-correlation, socio-economic status and media properties. The result shows that of the five properties of media engagement, the relevant factor is the important parameter of mediating variable to the causal relationship. The media usage (TV, SNS, print media), socio-economic status (gender, age, income, marriage and area), involvement and the Presidential Election, and Re and By-election are also effective in the five attributes of media engagement. These results suggest that the a study model can measure the campaign effectiveness. This study will contribute significantly to the development of politics, election, media, advertising, and public relations area as well as to promote interdisciplinary research.

On cross-correlation properties of S-boxes and their design using semi-bent functions

In this paper, several methods for constructing substitution boxes S-boxes with good cross-correlation properties are proposed. We firstly analyze the cross-correlation properties of bent functions and derive a sufficient condition that the absolute indicator Δf,g of two bent functions f and g achieve its lowest possible value 2ni¾?2. More precisely, it is sufficient that f+g is also a bent function, which then implies that the absolute indicator of vectorial bent functions equals to 2ni¾?2. This indicates an erroneous conclusion in by Zhou et al., claiming that if f is bent, then Δf,g=2ni¾?2 if and only if g is an affine function, which is not true. Furthermore, because of a strong relationship between the cross-correlation properties and disjoint spectra semi-bent functions, two classes of highly nonlinear vectorial semi-bent functions with very good cross-correlation properties are proposed. In particular, the first class of vectorial semi-bent functions introduced here compares favorably to other methods in terms of the cross-correlation properties of its component functions. In addition, A sufficient condition that the absolute indicator of two bent functions achieves its lowest value is derived.A construction of S-boxes with good auto-correlation properties from vectorial bent functions is given.Two classes of nonlinear vectorial semi-bent functions with good auto-correlation properties are proposed.Copyright © 2014 John Wiley & Sons, Ltd.

MIMO Radar Transmit Beampattern Design Without Synthesising the Covariance Matrix

Compared to phased-array, multiple-input multiple- output (MIMO) radars provide more degrees-of-freedom (DOF) that can be exploited for improved spatial resolution, better parametric identifiability, lower sidelobe levels at the transmitter/receiver, and design variety of transmit beampatterns. The design of the transmit beampattern generally requires the waveforms to have arbitrary auto- and cross-correlation properties. The generation of such waveforms is a two-step complicated process. In the first step, a waveform covariance matrix is synthesized, which is a constrained optimization problem. In the second step, to realize this covariance matrix actual waveforms are designed, which is also a constrained optimization problem. Our proposed scheme converts this two-step constrained optimization problem into a one-step unconstrained optimization problem. In the proposed scheme, in contrast to synthesizing the covariance matrix for the desired beampattern, nT-independent finite-alphabet constant-envelope waveforms are generated and preprocessed, with weight matrix W, before transmitting from the antennas. In this work, two weight matrices are proposed that can be easily optimized for the desired symmetric and nonsymmetric beampatterns and guarantee equal average power transmission from each antenna. Simulation results validate our claims.

LED-ID 시스템을 위한 효율적인 OFDM 프레임 동기화 방식

Abstract In this paper, we propose an efficient OFDM(Orthogonal Frequency Division Multiplexing) frame synchronization scheme for LED- ID(Identification) systems. A frame synchronization is an essential procedure for normal operations of OFDM systems. Bernoulli-Gau-ssian noise is considered in LED-ID systems' environments. In order to enhance the OFDM frame synchronization performance, we add a ROGS(Repeated Orthogonal Gold Sequence) to OFDM signals in the time domain. The power level of a ROGS does not affect a normal operation of the LED-ID systems. Frame synchronization can be achieved successfully over LED-ID channels interfered by impulsive noise owing to good auto and cross-correlation properties of the ROGS.Key words: LED-ID, OFDM, Synchronization, ROGS, m-Sequence \]^MKE/KEIT IT RD Revised January 10, 2014 ; Accepted January 15, 2014. (ID No. 20131210-124)Corresponding Author: Jin-Young Kim (e-mail: jinyoung@kw.ac.kr)

Dependency structure and scaling properties of financial time series are related

We report evidence of a deep interplay between cross-correlations hierarchical properties and multifractality of New York Stock Exchange daily stock returns. The degree of multifractality displayed by different stocks is found to be positively correlated to their depth in the hierarchy of cross-correlations. We propose a dynamical model that reproduces this observation along with an array of other empirical properties. The structure of this model is such that the hierarchical structure of heterogeneous risks plays a crucial role in the time evolution of the correlation matrix, providing an interpretation to the mechanism behind the interplay between cross-correlation and multifractality in financial markets, where the degree of multifractality of stocks is associated to their hierarchical positioning in the cross-correlation structure. Empirical observations reported in this paper present a new perspective towards the merging of univariate multi scaling and multivariate cross-correlation properties of financial time series.

Multiscale multifractal detrended cross-correlation analysis of financial time series

In this paper, we introduce a method called multiscale multifractal detrended cross-correlation analysis (MM-DCCA). The method allows us to extend the description of the cross-correlation properties between two time series. MM-DCCA may provide new ways of measuring the nonlinearity of two signals, and it helps to present much richer information than multifractal detrended cross-correlation analysis (MF-DCCA) by sweeping all the range of scale at which the multifractal structures of complex system are discussed. Moreover, to illustrate the advantages of this approach we make use of the MM-DCCA to analyze the cross-correlation properties between financial time series. We show that this new method can be adapted to investigate stock markets under investigation. It can provide a more faithful and more interpretable description of the dynamic mechanism between financial time series than traditional MF-DCCA. We also propose to reduce the scale ranges to analyze short time series, and some inherent properties which remain hidden when a wide range is used may exhibit perfectly in this way.

Research on Time-Domain Correlation Technique Based on ZC Sequences in OFDM System

OFDM modulation signal based on different Pseudo-random Noise sequences cant be discriminated in time domain in OFDM system. In order to resolve this problem, the time-domain sliding correlation technique based on ZC sequences is proposed, and the relations between the time-domain correlation properties and the length of the sequence are analyzed. On the basis of the analysis of the technique, the optimum scheme of time-domain sliding correlation is done by the aid of the comparison of the auto-correlation gain on the condition of limited symbol length and band-width. Simulation results in AWGN channel show that OFDM demodulation signal based on ZC sequences designed newly in this work has good auto-correlation and cross-correlation properties in time domain.

Binary Sequences for Multiple Access Collision Channel: Identification and Synchronization

In this paper we investigate the identification and synchronization problems on a multiple access collision channel. Following Massey's lead, solutions to these problems are addressed by protocol sequences. This paper considers two different levels of user synchroneity: frame-synchronous access and slot-synchronous access. For the identification problem, we study user-detectable sequences. These are sequences with the cross-correlation property that allows each active user be detected within a bounded delay basing only on the channel activity information observed. Furthermore, we investigate the synchronization problem for delay-detectable sequences under the slot-synchronous access assumption. The goal of the synchronization problem is to determine the offset relations among all the active users. Sequences that allow such determination can be viewed as a special subset of user-detectable sequences. For both of these sequence families, it is desirable that the sequence length should be as short as possible. Hence, it is important to derive the minimum sequence lengths for these respective families. This is an extremely difficult open problem. Nevertheless, lower and upper bounds on these minimum lengths are presented in this paper under different levels of synchroneity assumptions. In addition, the performance of these sequences is demonstrated via numerical simulation.

Modeling Complex System Correlation Using Detrended Cross-Correlation Coefficient

The understanding of complex systems has become an area of active research for physicists because such systems exhibit interesting dynamical properties such as scale invariance, volatility correlation, heavy tails, and fractality. We here focus on traffic dynamic as an example of a complex system. By applying the detrended cross-correlation coefficient method to traffic time series, we find that the traffic fluctuation time series may exhibit cross-correlation characteristic. Further, we show that two traffic speed time series derived from adjacent sections exhibit much stronger cross-correlations than the two speed series derived from adjacent lanes. Similarly, we also demonstrate that the cross-correlation property between the traffic volume variables from two adjacent sections is stronger than the cross-correlation property between the volume variables of adjacent lanes.

The theoretical limits of watermark spread spectrum sequence.

At present, the spread spectrum (SS) sequences used in watermark include i.i.d. random sequences and the sequences used in SS communications. They appear earlier than digital watermark. Almost no researchers pay attention to whether they are really fit for watermark. In this paper, we compare the SS watermark channel and the traditional SS communication channel. We find out that their correlation property is different. Considering cropping and translation attacks, we define watermark auto- and cross-correlation and propose Loose Autocorrelation and Tight Cross-Correlation (LAC&TCC) properties for SS watermark. The LAC&TCC properties are that, whether or not synchronized, the autocorrelation is equal or close to 1 and the cross-correlation is equal or close to 0. Accordingly, the peak correlation is divided into the peak autocorrelation R a(l) and the peak cross-correlation R c(l). We establish the lower bound of R c(l) and the higher bound of R a(l), respectively. The two bounds indicate that, no matter how small the cover is reserved, the extractor can always find a threshold to distinguish auto- and cross-correlation in theory.

Cross-Correlation Properties of Generalized Chirp-Like Sequences and Their Application to Zero-Correlation Zone Sequences

Cross-Correlation Properties of Generalized Chirp-Like Sequences and Their Application to Zero-Correlation Zone Sequences