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Journal articles on the topic 'Time-Varying Integration'

Author: Grafiati
Published: 4 June 2021
Last updated: 3 February 2022

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1

BEKAERT, GEERT, and CAMPBELL R. HARVEY. "Time-Varying World Market Integration." Journal of Finance 50, no. 2 (June 1995): 403–44. http://dx.doi.org/10.1111/j.1540-6261.1995.tb04790.x.

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2

BATTEN, JONATHAN A., PETER MORGAN, and PETER G. SZILAGYI. "TIME VARYING ASIAN STOCK MARKET INTEGRATION." Singapore Economic Review 60, no. 01 (March 2015): 1550006. http://dx.doi.org/10.1142/s021759081550006x.

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We employ an asset pricing framework with varying estimation lengths to show that there has been an increasing degree of integration between Asian and international stock markets, but very little with Japan. This finding is consistent with prior studies and highlights the impact of recent regulatory and economic reform undertaken throughout the region. Our results show that instability in the asset variance structure underpins the observed varying degrees of financial market integration. In particular, modeling integration using shorter estimation periods helps explain the time varying nature of financial market integration and the benefits that may accrue to international and domestic investors.
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3

Baele, Lieven, and Koen Inghelbrecht. "Time-varying integration, interdependence and contagion." Journal of International Money and Finance 29, no. 5 (September 2010): 791–818. http://dx.doi.org/10.1016/j.jimonfin.2009.12.008.

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4

Gupta, Priyanshi, Sanjay Sehgal, and Florent Deisting. "Time-Varying Bond Market Integration in EMU." Journal of Economic Integration 30, no. 4 (December 15, 2015): 708–60. http://dx.doi.org/10.11130/jei.2015.30.4.708.

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5

Baele, Lieven, and Koen Inghelbrecht. "Time-varying Integration and International diversification strategies." Journal of Empirical Finance 16, no. 3 (June 2009): 368–87. http://dx.doi.org/10.1016/j.jempfin.2008.11.001.

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6

Abad, Pilar, Helena Chuliá, and Marta Gómez-Puig. "Time-varying Integration in European Government Bond Markets." European Financial Management 20, no. 2 (March 2014): 270–90. http://dx.doi.org/10.1111/j.1468-036x.2011.00633.x.

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7

Birg, Gregory, and Brian M. Lucey. "Integration of smaller European equity markets: a time-varying integration score analysis." Applied Financial Economics Letters 2, no. 6 (November 2006): 395–400. http://dx.doi.org/10.1080/17446540600749379.

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8

Barari, Mahua. "Equity market integration in Latin America: A time-varying integration score analysis." International Review of Financial Analysis 13, no. 5 (January 2004): 649–68. http://dx.doi.org/10.1016/j.irfa.2004.02.019.

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9

Alotaibi, Abdullah R., and Anil V. Mishra. "Time varying international financial integration for GCC stock markets." Quarterly Review of Economics and Finance 63 (February 2017): 66–78. http://dx.doi.org/10.1016/j.qref.2016.03.001.

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10

Caldwell, Timothy M., and Todd D. Murphey. "Single Integration Optimization of Linear Time-Varying Switched Systems." IEEE Transactions on Automatic Control 57, no. 6 (June 2012): 1592–97. http://dx.doi.org/10.1109/tac.2011.2174694.

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11

Batten, Jonathan A., Harald Kinateder, Peter G. Szilagyi, and Niklas F. Wagner. "Time-varying energy and stock market integration in Asia." Energy Economics 80 (May 2019): 777–92. http://dx.doi.org/10.1016/j.eneco.2019.01.008.

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12

Kusumah, Hayun, Marwan Asri, Kusdhianto Setiawan, and Bowo Setiyono. "Time-varying Integration of Stock Markets from Global and Regional Perspective in Asia-Pacific." Jurnal Keuangan dan Perbankan 25, no. 3 (August 2, 2021): 466–91. http://dx.doi.org/10.26905/jkdp.v25i3.5822.

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This study investigates the time-varying integration of stock markets from a global and regional perspective, the consequences of two major global financial crises, i.e., the Asian Financial Crisis and the subprime mortgage, and the Crisis triggered by COVID-19. We contribute to the growing amount of literature on market integration, especially on the role of regional to global market integration. Although regional integration encourages an acceleration of global integration, the effect of a regional factor is not uniform among regions. It is important to understand regional to global market integration and the consequences during the crises. This study employs time-series data from economic territories based on the Morgan Stanley Capital International (MSCI) Asia-Pacific classification. It introduces an alternative measurement of time-varying integration by considering the correlation of regional and global markets using a simple international model, equivalent to the capital asset pricing model (CAPM). The result shows that the market integrations are time-varying both globally and regionally. The domestic markets are affected by the global market and its regional market, as the role of a regional market emerges during the financial crisis period. We find the different responses of stock markets during the Covid-19 period as a dominant factor to exacerbate the market return globally. In the long run, the upward trend for the regional market integration in both developed and emerging markets is inherent to the global market integration.DOI: 10.26905/jkdp.v25i3.5822
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13

Peake, Charles F. "Time-Varying Market Integration and Expected Returns in Emerging Markets." CFA Digest 36, no. 2 (May 2006): 48–50. http://dx.doi.org/10.2469/dig.v36.n2.4108.

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14

Karras, Georgios, and Houston H. Stokes. "Time-varying criteria for monetary integration: evidence from the EMU." International Review of Economics & Finance 10, no. 2 (June 2001): 171–85. http://dx.doi.org/10.1016/s1059-0560(00)00077-0.

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15

Guesmi, Khaled, and Duc Khuong Nguyen. "Time-varying regional integration of stock markets in Southeast Europe." Applied Economics 46, no. 11 (February 7, 2014): 1279–90. http://dx.doi.org/10.1080/00036846.2013.870656.

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16

Berger, Tino, and Lorenzo Pozzi. "Measuring time-varying financial market integration: An unobserved components approach." Journal of Banking & Finance 37, no. 2 (February 2013): 463–73. http://dx.doi.org/10.1016/j.jbankfin.2012.09.015.

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17

Zhang, MengQiu, Gang Li, Wenjuan Yan, ShaoHui Wang, and Ling Lin. "Reducing the spectral nonlinearity error caused by varying integration time." Infrared Physics & Technology 94 (November 2018): 48–54. http://dx.doi.org/10.1016/j.infrared.2018.08.024.

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18

DEJONG, F., and F. DEROON. "Time-varying market integration and expected returns in emerging markets." Journal of Financial Economics 78, no. 3 (December 2005): 583–613. http://dx.doi.org/10.1016/j.jfineco.2004.10.010.

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19

Pozzi, Lorenzo, and Guido Wolswijk. "The time-varying integration of euro area government bond markets." European Economic Review 56, no. 1 (January 2012): 36–53. http://dx.doi.org/10.1016/j.euroecorev.2011.05.006.

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20

Lee, Hyunchul, and Heeho Kim. "Time varying integration of European stock markets and monetary drivers." Journal of Empirical Finance 58 (September 2020): 369–85. http://dx.doi.org/10.1016/j.jempfin.2020.07.004.

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21

Smith, H. Allison, J. Geoffrey Chase, and Wen-Hwa Wu. "Efficient Integration of the Time Varying Closed-Loop Optimal Control Problem." Journal of Intelligent Material Systems and Structures 6, no. 4 (July 1995): 529–36. http://dx.doi.org/10.1177/1045389x9500600410.

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22

Wang, Ming-Chieh, and Feng-Ming Shih. "Time-Varying World and Regional Integration in Emerging European Equity Markets." European Financial Management 19, no. 4 (November 13, 2011): 703–29. http://dx.doi.org/10.1111/j.1468-036x.2011.00623.x.

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23

YANG, CHING-YU. "Using a functional integration matrix to solve time-varying bilinear systems." International Journal of Systems Science 26, no. 6 (June 1995): 1321–31. http://dx.doi.org/10.1080/00207729508929101.

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24

Wang, Xianghua, Xiangrong Wang, Chee Pin Tan, and Rui Yang. "Integration of Time-Varying threshold-based Fault Detection and Tolerant Control." IFAC-PapersOnLine 51, no. 24 (2018): 806–11. http://dx.doi.org/10.1016/j.ifacol.2018.09.667.

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25

Renou-Maissant, Patricia. "Toward the integration of European natural gas markets:A time-varying approach." Energy Policy 51 (December 2012): 779–90. http://dx.doi.org/10.1016/j.enpol.2012.09.027.

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26

Lee, Stephen. "Time-Varying Integration of REITs with Stocks: A Kalman Filter Approach." Journal of Real Estate Portfolio Management 26, no. 2 (July 2, 2020): 150–60. http://dx.doi.org/10.1080/10835547.2020.1858009.

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27

Ourir, Awatef, and Essahbi Essaadi. "An analysis of Asia-Pacific regional integration: Time-varying SVAR approach." International Journal of Economics and Business Research 1, no. 1 (2022): 1. http://dx.doi.org/10.1504/ijebr.2022.10040749.

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28

WANG, PING, and TOMOE MOORE. "STOCK MARKET INTEGRATION FOR THE TRANSITION ECONOMIES: TIME-VARYING CONDITIONAL CORRELATION APPROACH." Manchester School 76 (September 2008): 116–33. http://dx.doi.org/10.1111/j.1467-9957.2008.01083.x.

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29

Tuomainen, Jyrki, Tobias Andersen, Kaisa Tiippana, and Mikko Sams. "Audio‐visual integration of speech with time‐varying sine wave speech replicas." Journal of the Acoustical Society of America 112, no. 5 (November 2002): 2358. http://dx.doi.org/10.1121/1.4779556.

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30

Lu, XinJiang, and MingHui Huang. "Two-Level Modeling Based Intelligent Integration Control for Time-Varying Forging Processes." Industrial & Engineering Chemistry Research 54, no. 21 (May 21, 2015): 5690–96. http://dx.doi.org/10.1021/acs.iecr.5b01052.

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31

Sehgal, Sanjay, Piyush Pandey, Florent Deisting, and David McMillan. "Time varying integration amongst the South Asian equity markets: An empirical study." Cogent Economics & Finance 6, no. 1 (January 1, 2018): 1452328. http://dx.doi.org/10.1080/23322039.2018.1452328.

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32

Xi, Yang, Qi Li, Mengchao Zhang, Lin Liu, and Jinglong Wu. "Characterizing the Time-Varying Brain Networks of Audiovisual Integration across Frequency Bands." Cognitive Computation 12, no. 6 (November 2020): 1154–69. http://dx.doi.org/10.1007/s12559-020-09783-9.

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33

Cho, Sungjun, Stuart Hyde, and Ngoc Nguyen. "Time-varying regional and global integration and contagion: Evidence from style portfolios." International Review of Financial Analysis 42 (December 2015): 109–31. http://dx.doi.org/10.1016/j.irfa.2014.10.007.

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34

Zhou, Zheng-hua, Yu-huan Wang, Quan Liu, Xiao-tao Yin, and Cheng Yang. "A varying time-step explicit numerical integration algorithm for solving motion equation." Acta Seismologica Sinica 18, no. 2 (March 2005): 239–44. http://dx.doi.org/10.1007/s11589-005-0071-3.

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35

Fan, Rong, Chao Sheng Song, Zhen Liu, and Wen Ji Liu. "Coupled Dynamic and Vibration Analysis of Beveloid Geared System." Applied Mechanics and Materials 215-216 (November 2012): 917–20. http://dx.doi.org/10.4028/www.scientific.net/amm.215-216.917.

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Dynamic modeling of beveloid gears is less developed than that of spur gears, helical gears and hypoid gears because of their complicated meshing mechanism and 3-dimsional dynamic coupling. In this study, a nonlinear systematic coupled vibration model is created considering the time-varying mesh stiffness, time-varying transmission error, time-varying rotational radius and time-varying friction coefficient. Numerical integration applying the explicite Runge-Kutta formula and the implicit direct integration is used to solve the nonlinear dynamic model. Also, the dynamic characteristics of the marine gear system are investigated.
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36

Das, Debojyoti, and Kannadhasan Manoharan. "Emerging stock market co-movements in South Asia: wavelet approach." International Journal of Managerial Finance 15, no. 2 (April 1, 2019): 236–56. http://dx.doi.org/10.1108/ijmf-11-2017-0255.

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Purpose The purpose of this paper is to study the co-movement and market integration dynamics of the emerging/frontier stock markets in South Asia (India, Pakistan and Sri Lanka) with a portfolio management perspective. Design/methodology/approach Scholars in the past have documented the limitation of standard econometric techniques such as co-integration analysis to capture this phenomenon. The other econometric technique widely used in integration and comovement literature is dynamic conditional correlation-generalized autoregressive conditional heteroskedasticity. This method captivates the time-varying correlations, although frequency information is absent. The wavelet-based analysis decomposes the time-series data in a time-frequency domain, which is largely useful to fund managers and policy makers. This study examines the regional integration in selected South Asian markets using wavelet analysis. Findings The results suggest some degree of market integration, however weak as compared to regional integrations in developed markets. Pakistan and India were found to be the potential leaders at varying time scales in the region. Weaker co-movement phenomena may offer ample arbitrage opportunities to investors in this region. In addition, the authors also find that the structure of correlation changes after some of the major macroeconomic events. Originality/value This study is among the first to examine co-movement and integration of stock returns in a time-frequency domain for South Asia. In addition, the authors also highlight weak integration in these markets, which may be beneficial for portfolio diversification.
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37

Salahuddin, Sultan, Muhammad Kashif, and Mobeen Ur Rehman. "Time Varying Stock Market Integration and Diversification Opportunities within Emerging and Frontier Markets." Pénzügyi Szemle = Public Finance Quarterly 65, no. 2 (2020): 168–95. http://dx.doi.org/10.35551/pfq_2020_2_2.

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38

Zhu, Shuai, Jiayuan Zhou, Xiao-Mei Liu, and Shi-Lie Weng. "A modified homogenized highly precise direct integration method for time-varying nonhomogeneous systems." Advances in Mechanical Engineering 9, no. 11 (November 2017): 168781401773053. http://dx.doi.org/10.1177/1687814017730535.

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39

Panchenko, Valentyn, and Eliza Wu. "Time-varying market integration and stock and bond return concordance in emerging markets." Journal of Banking & Finance 33, no. 6 (June 2009): 1014–21. http://dx.doi.org/10.1016/j.jbankfin.2008.10.016.

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40

Liang, Xin-Guang, Zhen-Qiang Yao, Lei Luo, and Jun Hu. "An improved numerical integration method for predicting milling stability with varying time delay." International Journal of Advanced Manufacturing Technology 68, no. 9-12 (February 9, 2013): 1967–76. http://dx.doi.org/10.1007/s00170-013-4813-4.

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41

Posedel Šimović, Petra, Marina Tkalec, Maruška Vizek, and Junsoo Lee. "Time-varying integration of the sovereign bond markets in European post-transition economies." Journal of Empirical Finance 36 (March 2016): 30–40. http://dx.doi.org/10.1016/j.jempfin.2015.12.005.

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42

Zhou, Xiang, KongFatt Wong-Lin, and Holmes Philip. "Time-Varying Perturbations Can Distinguish Among Integrate-to-Threshold Models for Perceptual Decision Making in Reaction Time Tasks." Neural Computation 21, no. 8 (August 2009): 2336–62. http://dx.doi.org/10.1162/neco.2009.07-08-817.

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Several integrate-to-threshold models with differing temporal integration mechanisms have been proposed to describe the accumulation of sensory evidence to a prescribed level prior to motor response in perceptual decision-making tasks. An experiment and simulation studies have shown that the introduction of time-varying perturbations during integration may distinguish among some of these models. Here, we present computer simulations and mathematical proofs that provide more rigorous comparisons among one-dimensional stochastic differential equation models. Using two perturbation protocols and focusing on the resulting changes in the means and standard deviations of decision times, we show that for high signal-to-noise ratios, drift-diffusion models with constant and time-varying drift rates can be distinguished from Ornstein-Uhlenbeck processes, but not necessarily from each other. The protocols can also distinguish stable from unstable Ornstein-Uhlenbeck processes, and we show that a nonlinear integrator can be distinguished from these linear models by changes in standard deviations. The protocols can be implemented in behavioral experiments.
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43

Guesmi, Khaled, Frederic Teulon, and Amine Lahiani. "Australias Integration Into The ASEAN-5 Region." Journal of Applied Business Research (JABR) 29, no. 6 (October 29, 2013): 1607. http://dx.doi.org/10.19030/jabr.v29i6.8198.

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This paper attempts to evaluate the time-varying integration of Australian stock market in ASEAN-5 region (ASEAN + Australia, Korea, China, India and Japan) by using a conditional version of the international capital asset pricing model (ICAPM) allowing for dynamic changes in the degree of market integration, regional market risk price, currency risk price and domestic market risk price. Main findings are as follows: i) the prices of risk in Australia are extremely sensitive to major international economic and political events such as the different monetary and financial crises in international financial market; ii) the level of market openness and development of the stock market satisfactorily explain the time-varying degree of Australian stock integration.
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44

Das, Sudipta, and Parama Barai. "Time-varying industry beta in Indian stock market and forecasting errors." International Journal of Emerging Markets 10, no. 3 (July 20, 2015): 521–34. http://dx.doi.org/10.1108/ijoem-02-2013-0035.

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Purpose – The purpose of this paper is to empirically estimate industry beta in Indian stock market with three alternative models and compare the accuracy of forecasting error to find the most suitable model for time-varying beta estimation. Design/methodology/approach – The paper applies the standard regression model, Kalman filter model, other statistical approaches and secondary material. Findings – The paper finds that the existence of dynamic beta in Indian market. The results also indicate systematic risk or beta of Indian industries is susceptible to the global economic effect. Finally, the Kalman filter generates the lower forecasting error compared to the other method for almost all the industries. Practical implications – The accurate estimation of beta which is a measure of systematic risk helps investors to make investment decision easier. The implication of this result is important for finance practitioners such as portfolio managers, investment advisors and security analysts. This study will help to determine the country risk with respect to the global index and analyze the global financial market integration effect on India. Originality/value – This paper reliably estimate industry portfolio beta for India. The time-varying beta is estimated using Kalman filter method which is rarely applied in Indian literature. This paper contributes by extending the knowledge of existing literature by introducing a new data set with Indian data which is not affected by the “data snooping” bias. This study will also help to determine the country risk with respect to the global index and analyze the global financial market integration effect on India.
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45

Lauzon, A. M., and J. H. Bates. "Estimation of time-varying respiratory mechanical parameters by recursive least squares." Journal of Applied Physiology 71, no. 3 (September 1, 1991): 1159–65. http://dx.doi.org/10.1152/jappl.1991.71.3.1159.

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Continuous estimation of time-varying respiratory mechanical parameters is required to fully characterize the time course of bronchoconstriction. To achieve such estimation, we developed an estimator that uses the recursive linear least-squares algorithm to fit the equation Ptr = RV + EV + K to measurements of tracheal pressure (Ptr) and flow (V). The volume (V) is obtained by numerical integration of V. The estimator has a finite memory with length into the past at each point in time that varies inversely with the difference between the current measurement of Ptr and that predicted by the model, to allow the algorithm to track rapidly varying parameters (R, E, and K). V usually exhibits significant drift and must be corrected. Of the several correction methods investigated, subtraction of the recursively weighted average of V before integration to V was found to perform best. The estimator was tested on simulated noisy data where it successfully followed a fivefold increase in R and a twofold increase in E occurring over 10 s. Three dogs and two cats were anesthetized, paralyzed, tracheostomized, and challenged with a bolus of methacholine (approximately 13 mg/kg iv). Increases of 3- to 10-fold were observed in R and 2- to 3-fold in E, beginning within 10–40 s after the bolus injection. In some animals we found that the increase in E occurred more slowly than that in R, which the V signal suggested was due to dynamic hyperinflation of the lungs. These results demonstrate that our recursive estimator is able to track rapid changes in respiratory mechanical parameters during bronchoconstrictor challenge.
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46

Li, Hong. "Integration versus segmentation in China's stock market: An analysis of time-varying beta risks." Journal of International Financial Markets, Institutions and Money 25 (July 2013): 88–105. http://dx.doi.org/10.1016/j.intfin.2013.01.007.

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47

Dong, Ping, Jianhua Cheng, and Liqiang Liu. "A Novel Anti-Jamming Technique for INS/GNSS Integration Based on Black Box Variational Inference." Applied Sciences 11, no. 8 (April 19, 2021): 3664. http://dx.doi.org/10.3390/app11083664.

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In this paper, a novel anti-jamming technique based on black box variational inference for INS/GNSS integration with time-varying measurement noise covariance matrices is presented. We proved that the time-varying measurement noise is more similar to the Gaussian distribution with time-varying mean value than to the Inv-Gamma or Inv-Wishart distribution found by Kullback–Leibler divergence. Therefore, we assumed the prior distribution of measurement noise covariance matrices as Gaussian, and calculated the Gaussian parameters by the black box variational inference method. Finally, we obtained the measurement noise covariance matrices by using the Gaussian parameters. The experimental results illustrate that the proposed algorithm performs better in resisting time-varying measurement noise than the existing Variational Bayesian adaptive filter.
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48

Zhang, Dayong, Wanli Zhao, Fei Wu, and Qiang Ji. "Financial Integration in Asia: A Systemic View on Currency Markets." Asian Economic Papers 19, no. 2 (June 2020): 41–58. http://dx.doi.org/10.1162/asep_a_00754.

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Using a systemic approach, this study investigates the time-varying linkages among currency markets of Japan, the People's Republic of China, the Republic of Korea, and the five core ASEAN economies to understand financial integration in Asia. We first construct a vector autoregressive model and use the Diebold and Yilmaz ( 2014 ) approach to quantitatively identify the connectedness within the system, accompanied by a rolling-window approach to allow for time-varying dynamics and pairwise Granger causality tests to check the robustness of our main results. We find that though systemic interconnectedness varies over time, the Singapore dollar is constantly a top net contributor, explaining most of the variation in East Asian currency markets.
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49

Bartels, Robert E. "A time integration algorithm based on the state transition matrix for structures with time varying and nonlinear properties." Computers & Structures 81, no. 6 (March 2003): 349–57. http://dx.doi.org/10.1016/s0045-7949(03)00018-x.

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50

Hasnijeh, Saeed Gheisari, Mehrdad Poursina, Bernt Johan Leira, Hossein Karimpour, and Wei Chai. "Stochastic dynamics of a nonlinear time-varying spur gear model using an adaptive time-stepping path integration method." Journal of Sound and Vibration 447 (May 2019): 170–85. http://dx.doi.org/10.1016/j.jsv.2019.02.001.

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