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The interaction between stock prices and interest rates in Turkey:empirical evidence from ARDL bounds test cointegration

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Financial Innovation 2019年第1期5卷 110-121页

作者： Turgut Tursoy Department of Banking and Finance Near East UniversityNicosia99138North Cyprus10 MersinTurkey

This paper demonstrates a significant,long-running relationship between stock prices and domestic interest rates in Turkey’s financial markets for the period of 2001 M1-2017 *** analysis is investigated using the autoregressivedistributed lag bounds(ARDL Bounds)test and vector autoregressive ***,cointegrating equations such as the fully modified ordinary least square,dynamic ordinary least squares,and canonical cointegrating regression are applied to check the long-run elasticities in the concerned *** ARDL Bounds and Johansen cointegration test results show that,dynamically,both prices are significantly related to each *** cointegrating equation outcomes demonstrate elasticities whereby both coefficients have negative ***,the same results are corroborated by the impulse response where all variables respond negatively to each other.

关键词： Stock price Interest rates cointegration ARDL VAR

Application of cointegration to Forecasting Foreign Trade in China

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Systems Science and Systems Engineering 2000年第4期10卷 420-428页

作者： WANG Zhen\|quan 1,2 ,\ XU Shan\|ying 1 1. Academy of Mathematics and System Sciences, The Chinese Academy of Sciences, Beijing 100080, China 2. Department of Economic Management, Nanhua University, Hengyang 421001, China

Monthly forecast of export and import of China is investigated in this paper. Export, import, exchange rates and foreign reserve of China are coincided with in a vector error corrected model, on which seasonal export and import can be forecasted in a reasonable precision. With impulse response analysis, impact of exchange rate to export is discussed.

关键词： foreign trade forecast cointegration empirical stu

cointegration of event-related potential (ERP) signals in experiments with different electromagnetic field (EMF) conditions

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Health 2010年第5期2卷 400-406页

作者： Argiro E. Maganioti Hountala D. Chrissanthi Papageorgiou C. Charalabos Rabavilas D. Andreas Papadimitriou N. George Capsalis N. Christos National Technical University of Athens Department of Electrical Engineering Division of Information Transmission Systems and Material Technology Department of Psychiatry Eginition Hospital University of Athens University Mental Health Research Inst

Due to their non-stationarity, ERP signals are difficult to study. The concept of cointegration might overcome this problem and allow for the study of the co-variability between whole ERP signals. In this context cointegration factor is defined as the ability of an ERP signal to co-vary with other ERP signals. The aim of the present study was to investigate whether the cointegration factor is dependent on different EMF conditions and gender, as well as the locations of the electrodes on the scalp. The findings revealed that women have a significantly higher cointegration factor than men, while all subjects have increased cointegration factors in the presence of EMF. The cointegration factor is location dependent, creating a distinct cluster of high coin- tegration capacity at the central and lateral electrodes of the scalp, in contrast to clusters of low cointegration capacity at the anterior and posterior electrodes There seem to be distinct similarities of the present findings with those from standard methodologies of the ERPs. In conclusion cointegration is a promising tool towards the study of functional interactions between different brain locations.

关键词： EMF ERP Stationarity cointegration ACF

cointegration Analysis on the Relation between Urbanization and Economic Growth in China

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Asian Agricultural Research 2011年第3期3卷 133-136页

作者： LIU Ai-ying1,YAO Li-fen2,LI Qing-chen3 1.School of Business Administration,Hebei University of Economics & Business,Shijiazhuang 050061,China 2.School of Tourism,Hebei University of Economics & Business,Shijiazhuang 050061,China 3.Institute of Geographical Sciences,Hebei Academy of Science,Shijiazhuang 050011,China School of Business Administration Hebei University of Economics & Business School of Tourism Hebei University of Economics & Business Institute of Geographical Sciences Hebei Academy of Science

This paper utilizes cointegration theory,error correcting model and Granger causality testing theory to make an empirical research on the relation between urbanization and GDP in China,and also implements a comparative analysis to the relation between three industries and degree of urbanization,the related coeffecient is 0.97,0.95,0.97,*** the result shows a long-term balance between these two factors,and the promoting effect to tertiary industry by urbanization is more *** and economic growth are the long-term balanced *** the long-term balance,every 1% increment of urbanization can make 4.82% increment of GDP;In short-term balance,if the balance depart from the long-term balance at the i-th term,the model will take automatic reversal adjustment with-0.06 adjusting strength at the(i+1)th term,to make it move to the long-term *** economic growth onto urbanization is one-way causality relationship,the primary and secondary industry onto urbanization is also one-way causality ***,the tertiary industry onto urbanization is both-way causality relationship.

关键词： Economic growth Urbanization cointegration test Er

Bayesian Factorized cointegration Analysis

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Open Journal of Statistics 2012年第5期2卷 504-511页

作者： Kai Cui Wenshan Cui Department of Statistical Science Duke University Durham USA School of Science and Information Qingdao Agricultural University Qingdao China

The concept of cointegration is widely used in applied non-stationary time series analysis to describe the co-movement of data measured over time. In this paper, we proposed a Bayesian model for cointegration test and analysis, based on the dynamic latent factor framework. Efficient computational algorithms are also developed based on Markov Chain Monte Carlo (MCMC). Performance and efficiency of the the model and approaches are assessed by simulated and real data analysis.

关键词： cointegration Bayesian Dynamic Factor Non-Stationary Root Structure MCMC

Bayesian Markov Regime-Switching Models for cointegration

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Applied Mathematics 2012年第12期3卷 1892-1897页

作者： Kai Cui Wenshan Cui Department of Statistical Science Duke University Durham USA School of Science and Information Qingdao Agricultural University Qingdao China

This paper introduces a Bayesian Markov regime-switching model that allows the cointegration relationship between two time series to be switched on and off over time. Unlike classical approaches for testing and modeling cointegration, the Bayesian Markov switching method allows for estimation of the regime-specific model parameters via Markov Chain Monte Carlo and generates more reliable estimation. Inference of regime switching also provides important information for further analysis and decision making.

关键词： cointegration Regime-Switching Bayesian MCMC

Problems Existed in Applications of cointegration Theory in China

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Chinese Business Review 2007年第2期6卷 43-46页

作者： WANG Rui-ze School of Economics Tianjin Polytechnic University Tianjin 300384 China

Although the cointegration Theory was founded by the C.W.J Granger and other economists in the 1980s, it was not widely used in China until C.W.J Granger was awarded with Nobel Prize in 2003. Since then, a lot of economic papers introducing or applying cointegration Theory have emerged, but the phenomenon of misuse of this theory possibly arose at the same time. Based on some of these papers obtained from web site （***）, this paper explores the applications of cointegration Theory in China and draws some initial conclusions. Most of these applications are reasonable, but some of them are a bit blindfold or even contradictory in conclusions, which indicates that the overall application quality has a large room to get improved and should be paid more attention by academe.

关键词： cointegration non-stationary time series unit root testing

The Relationship between Carbon Dioxide Emission Intensity and Economic Growth in China:cointegration,Linear and Nonlinear Granger Causality

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Journal of Resources and Ecology 2016年第2期7卷 122-129页

作者：涂雄苓江西财经大学统计学院南昌330013 江西财经大学应用统计研究中心南昌330013

This study is to use cointegration, linear and non-linear Granger causality test to investigate the relationship between carbon dioxide （CO2） emissionand economic growth （GDP） in China for the period 1961-2010. Our analysis shows that CO2 emission and GDP are balanced in the long-run. The results suggest that there is evidence that economic development can improve environmental degradation in the long-run. Moreover, the result of linear and non-linear Granger causality test indicates a long-run unidirectional causality running from GDP to CO2 emissions. The study suggests that in the long run, economic growth may have an adverse effect on the CO2 emissions in China. Government should take into account the environment in their current policies, which may be of great importance for policy decision-makers to develop economic policies to preserve economic growth while curbing of carbon emissions.

关键词： cointegration Linear and Nonlinear Granger Causality CO2 emission economic growth

A fault tolerant model for multi-sensor measurement

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Chinese Journal of Aeronautics 2015年第3期28卷 874-882页

作者： Li Liang Shi Wei Information and Ecommerce Institute University of Electronic Science & Technology of China China Gas Turbine Establishment

Abstract Multisensor systems are very powerful in the complex environments. The cointegration theory and the vector error correction model, the statistic methods which widely applied in economic analysis, are utilized to create a fitting model for homogeneous sensors measurements. An algorithm is applied to implement the model for error correction, in which the signal of any sensor can be esti mated from those of others. The model divides a signal series into two parts, the training part and the estimated part. By comparing the estimated part with the actual one, the proposed method can iden tify a sensor with possible faults and repair its signal. With a small amount of training data, the right parameters for the model in real time could be found by the algorithm. When applied in data analysis for aero engine testing, the model works well. Therefore, it is not only an effective method to detect any sensor failure or abnormality, but also a useful approach to correct possible errors.

关键词： cointegration Fault tolerant Measurement Multi-sensor Turbine engine