Cross-sample entropy of foreign exchange time series

The correlation of foreign exchange rates in currency markets is investigated based on the empirical data of DKK/USD, NOK/USD, CAD/USD, JPY/USD, KRW/USD, SGD/USD, THB/USD and TWD/USD for a period from 1995 to 2002. Cross-SampEn (cross-sample entropy) method is used to compare the returns of every two exchange rate time series to assess their degree of asynchrony. The calculation method of confidence interval of SampEn is extended and applied to cross-SampEn. The cross-SampEn and its confidence interval for every two of the exchange rate time series in periods 1995-1998 (before the Asian currency crisis) and 1999-2002 (after the Asian currency crisis) are calculated. The results show that the cross-SampEn of every two of these exchange rates becomes higher after the Asian currency crisis, indicating a higher asynchrony between the exchange rates. Especially for Singapore, Thailand and Taiwan, the cross-SampEn values after the Asian currency crisis are significantly higher than those before the Asian currency crisis. Comparison with the correlation coefficient shows that cross-SampEn is superior to describe the correlation between time series.     

Multifractal detrending moving average analysis on the US Dollar exchange rates

In this paper, we investigate the multifractal behavior of the US dollar (USD) exchange rates. The results from the multifractal detrending moving average algorithm show that twelve exchange rate series were multifractal. The major source of multifractality are long-range correlations of small and large fluctuations. Fat-tail distributions have important effects on the multifractality of USD/AUR, USD/EUR and CNY/USD exchange rates. We also find evidence that extreme events play an important role in the contributions to multifractality for the USD/EUR exchange rate.     

Scale free effects in world currency exchange network

A large collection of daily time series for 60 world currencies' exchange rates is considered. The correlation matrices are calculated and the corresponding Minimal Spanning Tree (MST) graphs are constructed for each of those currencies used as reference for the remaining ones. It is shown that multiplicity of the MST graphs' nodes to a good approximation develops a power like, scale free distribution with the scaling exponent similar as for several other complex systems studied so far. Furthermore, quantitative arguments in favor of the hierarchical organization of the world currency exchange network are provided by relating the structure of the above MST graphs and their scaling exponents to those that are derived from an exactly solvable hierarchical network model. A special status of the USD during the period considered can be attributed to some departures of the MST features, when this currency (or some other tied to it) is used as reference, from characteristics typical to such a hierarchical clustering of nodes towards those that correspond to the random graphs. Even though in general the basic structure of the MST is robust with respect to changing the reference currency some trace of a systematic transition from somewhat dispersed – like the USD case – towards more compact MST topology can be observed when correlations increase.     

The relationships between Shanghai stock market and CNY/USD exchange rate: New evidence based on cross-correlation analysis,structural cointegration and nonlinear causality test

This paper explores the co-movement of Shanghai stock market and China Yuan (CNY) exchange rates. First, we find that stock price and exchange rate are significantly cross-correlated. Second, employing a cointegration test allowing for a structural break, we find that the Shanghai Composite Index (SCI) is not cointegrated with the exchange rate of CNY/USD. The so-called “cointegration” found in previous studies is just caused by the shock of the recent financial crisis. Third, using linear and nonlinear Granger causality tests, we find no causality between stock prices and exchange rates during the period before the recent financial crisis. After the financial crisis, a unidirectional causality behavior running from exchange rates to stock index is present.     

World currency exchange rate cross-correlations

World currency network constitutes one of the most complex structures that is associated with the contemporary civilization. On a way towards quantifying its characteristics we study the cross correlations in changes of the daily foreign exchange rates within the basket of 60 currencies in the period December 1998–May 2005. Such a dynamics turns out to predominantly involve one outstanding eigenvalue of the correlation matrix. The magnitude of this eigenvalue depends however crucially on which currency is used as a base currency for the remaining ones. Most prominent it looks from the perspective of a peripheral currency. This largest eigenvalue is seen to systematically decrease and thus the structure of correlations becomes more heterogeneous, when more significant currencies are used as reference. An extreme case in this later respect is the USD in the period considered. Besides providing further insight into subtle nature of complexity, these observations point to a formal procedure that in general can be used for practical purposes of measuring the relative currencies significance on various time horizons.     

集合经验模态分解在区域降水变化多尺度分析及气候变化响应研究中的应用

集合经验模态分解(EEMD)是一种适用于非线性、非平稳序列的信号分析方法, 将EEMD 应用于气候要素时间序列, 可提取可靠真实的气候变化信号, 同时, EEMD可以得到气候变化的固有时间尺度.本文使用EEMD方法, 从气候时间序列中提取气候信号中各个尺度的变化, 对渭河流域过去50年来的秋季降水进行多尺度分析,结果显示, 对于20世纪70年代末80年代初的全球气候突变, 渭河流域的秋季降水也有很好的响应, 而且大尺度上的响应要早于中小尺度, 其中在大尺度上主要表现为波动形式, 即降水距平正负位相持续期的变化, 从持续正位相到正负位相周期性交替出现; 而在中小尺度上主要是振幅大小, 即降水距平正负位相量级的变化, 量级从相对较大变为相对较小再逐渐增大. 关键词： 集合经验模态分解 多尺度变化 秋季降水 渭河流域     

Source identification of gasoline engine noise based on continuous wavelet transform and EEMD–RobustICA

In order to separate noise source of gasoline engine, ensemble empirical mode decomposition (EEMD), robust independent component analysis (RobustICA) and continuous wavelet transform (CWT) are applied to study the blind source separation and noise source identification of gasoline engine. After the signal is decomposed with EEMD into a set of intrinsic mode function (IMFs), RobustICA has been applied to extract independent sources. The combined technique alleviates the problem of mode mixing in EMD and overcomes the problem that the number of sensors must be larger than or equal to the number of separated components. At the same time, RobustICA’s cost efficiency and robustness are particularly remarkable for short sample length in the absence of pre-whiten. CWT using the Complex Morlet Wavelet (CMW) is used for its better time–frequency localization features to analyze time–frequency characteristics of the ICA results. Combining the time–frequency results with different noise sources frequency spectrums, the corresponding relation of the different noise sources of gasoline engine and the independent components is determined. It turns out that these independent components correspond to the exhaust, combustion and piston slap noise of the gasoline engine respectively.     

False Euro (FEUR) exchange rate correlated behaviors and investment strategy

We have searched for correlations and anticorrelations with respect to currencies as CHF, DKK, JPY, and USD in order to understand the EUR behavior. In order to do so we have invented a false euro (FEUR) dating back to 1993 and have derived simulated exchange rates of the FEUR. Within the Detrended Fluctuation Analysis (DFA) statistical method we have obtained the power law behavior describing the rms. deviation of the fluctuations as a function of time. We have compared the time-dependent exponent for these four exchange rates, and observe the role of the DEM, and the other currencies forming the EUR. A simple investment strategy based on the local DFA technique shows one can obtain appreciable gains, even taking into account some modest transaction fee. We compare the time dependent α exponent of the DFA for various exchange rates as in a correlation matrix for estimating respective influences. Received 31 August 2000     

Correlation structures in short-term variabilities of stock indices and exchange rates

Financial data usually show irregular fluctuations and some trends. We investigate whether there are correlation structures in short-term variabilities (irregular fluctuations) among financial data from the viewpoint of deterministic dynamical systems. Our method is based on the small-shuffle surrogate method. The data we use are daily closing price of Standard & Poor's 500 and the volume, and daily foreign exchange rates, Euro/US Dollar (USD), British Pound/USD and Japanese Yen/USD. We found that these data are not independent.     

A Markov model of financial returns

We address the general problem of how to quantify the kinematics of time series with stationary first moments but having non stationary multifractal long-range correlated second moments. We show that a Markov process is sufficient to model important aspects of the multifractality observed in financial time series and propose a kinematic model of price fluctuations. We test the proposed model by analyzing index closing prices of the New York Stock Exchange and the DEM/USD tick-by-tick exchange rates obtained from Reuters EFX. We show that the model captures the characteristic features observed in actual financial time series, including volatility clustering, time scaling and fat tails in the probability density functions, power-law behavior of volatility correlations and, most importantly, the observed nonuniversal multifractal singularity spectrum. Motivated by our finding of strong agreement between the model and the data, we argue that at least two independent stochastic Gaussian variables are required to adequately model price fluctuations.     

Analysis on acoustic characteristics of opposed multi-burner gasifier

Hilbert–Huang Transformation and Statistical Theory are used to analyze the impinging flame noise signals of a gasifier. The characteristic of the flame noise energy is studied by standard deviation and probability density, and frequency–time distribution is generated by the empirical mode decomposition (EMD) method and Hilbert spectrum. The results show that, in different conditions, the value of standard deviation of four burners impinging flame noise is greater than that of the two burners, but not for the probability density. The change of the standard deviation and probability density of four burners is smaller than that of two burners. It means that the flame of four burners combusts severely but stably. Under the condition of low feed and oxygen ratio, the two flame burner noise signals frequency and energy distribute mainly in 100 Hz regions; and four burners flame noise distribution is concentrated in the low-frequency bands below 45 Hz and the 45–100 Hz bands.     

Frequency analysis of tick quotes on the foreign exchange market and agent-based modeling: A spectral distance approach

High-frequency financial data of the foreign exchange market (EUR/CHF, EUR/GBP, EUR/JPY, EUR/NOK, EUR/SEK, EUR/USD, NZD/USD, USD/CAD, USD/CHF, USD/JPY, USD/NOK, and USD/SEK) are analyzed by utilizing the Kullback-Leibler divergence between two normalized spectrograms of the tick frequency and the generalized Jensen-Shannon divergence among them. The temporal structure variations of the similarity between currency pairs is detected and characterized. A simple agent-based model in which N market participants exchange M currency pairs is proposed. The equation for the tick frequency is approximately derived theoretically. Based on the analysis of this model, the spectral distance of the tick frequency is associated with the similarity of the behavior (perception and decision) of the market participants in exchanging these currency pairs.     

Dynamics of Quantum Discord in Asymmetric and Local Non-Markovian Environments

The non-Markovian decoherence of quantum and classical correlationsis analytically obtained when two qubits are asymmetrically subjected to the bit flip channel and phase flip channel. For one class of initial mixed states, quantum correlations quantified by quantum discord decay synchronously with classical correlations. The discovery that the decaying rates of quantum and classical correlations suddenly change at the characteristic time is physically interpreted by the distance from quantum state to the closest classical states. In a large time interval, quantum correlations are greater than classical correlations. The quantum and classical correlations can be preserved over a longer period of time via the kernel characterizing the environment memory effects.     

利用经验模态分解的高频水声信号滤波方法*

研究了一种高频水声信号的滤波问题,提出了一种改进的经验模态分解加小波阈值滤波方法。首先对信号进行带通滤波处理,再进行经验模态分解,将分解得到的各个模态转换为频域信号,采用小波软阈值方法对这些频域信号进行滤波,最后对信号进行重构,并转换为时域信号。经数值仿真与试验数据验证表明此方法是可行有效的,与原基于经验模态分解的小波阈值滤波方法相比,本方法滤波效果较好:对不同输入信噪比的仿真信号进行滤波后,本方法的输出信噪比最大提高17.41 d B,滤波后所得信号与加噪前纯信号的相关系数最大提高0.90;对实验数据进行滤波后,不同时间段信号的相关系数最大提高0.62。     

Exciton correlations and input–output relations in non-equilibrium exciton superfluids

The photoluminescence (PL) measurements on photons and the transport measurements on excitons are the two types of independent and complementary detection tools to search for possible exciton superfluids in electron–hole semi-conductor bilayer systems. In fact, it was believed that the transport measurements can provide more direct evidences on superfluids than the spectroscopic measurements. It is important to establish the relations between the two kinds of measurements. In this paper, using quantum Heisenberg–Langevin equations, we establish such a connection by calculating various exciton correlation functions in the putative exciton superfluids. These correlation functions include both normal and anomalous greater, lesser, advanced, retarded, and time-ordered exciton Green functions and also various two exciton correlation functions. We also evaluate the corresponding normal and anomalous spectral weights and the Keldysh distribution functions. We stress the violations of the fluctuation and dissipation theorem among these various exciton correlation functions in the non-equilibrium exciton superfluids. We also explore the input–output relations between various exciton correlation functions and those of emitted photons such as the angle resolved photon power spectrum, phase sensitive two mode squeezing spectrum and two photon correlations. Applications to possible superfluids in the exciton–polariton systems are also mentioned. For a comparison, using conventional imaginary time formalism, we also calculate all the exciton correlation functions in an equilibrium dissipative exciton superfluid in the electron–electron coupled semi-conductor bilayers at the quantum Hall regime at the total filling factor ν_T=1${\nu }_T=1$. We stress the analogies and also important differences between the correlations functions in the two exciton superfluid systems.     

Temporal variations of serial correlations of trading volume in the US stock market

Serial correlations in the trading volume of the US stock market are investigated in this paper. The use of the detrended fluctuation analysis implemented within a rolling window indicated that, for the period 1929–2011, the strength of correlations exhibits important temporal variations with a trend shift by the 1990s, and 4-year and 21-year cycles. These empirical findings are compared to those obtained for mature international stock markets (FTSE-100 and Nikkei) and discussed in terms of potential economic and financial implications.     

基于EMD方法的非线性/非平稳时间序列的气候预测研究

目前，大多数统计预测模型均假设时间序列或观测数据是线性和平稳的。然而，自然界的观测资料是非线性和非平稳的，通常很难用这些数学模型预测它们。本文针对这一问题提出了一个新的预测方案，即首先利用经验模态分解方法将非线性/非平稳时间序列平稳化，得到一系列本征模函数(IMF)；其次用均生函数模型预测各IMF分量；最后以所有IMF的预测值为新样本对源序列作最优子集回归模型的拟合及预测。结果表明每个IMF，尤其是特征IMF(即特征层次)比源序列有更高的可预测性。该方案为气候预测开辟了一条新的有效途径。     

核爆与雷电电磁脉冲识别

用经验模态分解和分形分析相结合的方法对核爆和雷电电磁脉冲信号进行了识别研究。计算了核爆和雷电电磁脉冲原始信号的盒维数,以及原始信号经验模态分解后前4阶固有模态分量（IMF）的盒维数。用最近邻法对核爆和雷电进行了识别,实验结果表明:原始信号经验模态分解后一阶、二阶IMF盒维数的识别率要略高于三阶、四阶IMF盒维数的识别率;原始信号盒维数的识别率高于经验模态分解后各阶IMF盒维数的识别率;二维和三维特征的识别率要高于一维特征的识别率,另外二维和三维特征的识别率更加趋于稳定,并且三维特征的识别率都在90%以上。     

总体经验模态分解能量向量用于ECG能量分布的研究

总体经验模态分解(EEMD)改进了经验模态分解(EMD)存在的模态混叠问题, 依据信号自身的波动特点将信号分解, 特别适合非线性非平稳信号的分析处理. ECG信号能量分布有一定的规律, 疾病会引起能量分布的变化, 研究ECG能量分布的改变对心脏疾病的研究和临床诊断有重要意义. 本文将ECG信号通过EEMD方法分解为多个本征模态函数(IMF)分量, 观察IMF分量的波动规律, 指出了ECG信号在不同时间尺度上的波动特点和物理意义. 将IMF分量分别计算能量, 得到ECG的能量向量, 并对健康人和三种心脏疾病患者能量向量进行对比分析. 结果表明心脏疾病导致EEMD能量向量的高频分量显著降低, 尤其是p₁分量具有较好的区分度, 可以作为心脏疾病诊断的参考依据. 相比较传统的频域分析方法单纯关注频率而忽略信号自身特点和信号成分之间的相互作用, EEMD的分解结果依赖于ECG信号本身, 因此更能够反映ECG信号的真实情况, 揭示年龄和疾病对ECG能量分布的影响.