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How to cite this paper
APA: Ghosh, I & Chaudhuri, T. (2019). A wavelet approach towards examining dynamic association, causality and spillovers. International Journal of Data and Network Science, 3(1), 23-36.
Chicago/Turabian: Ghosh, I & Chaudhuri, T. 2019. "A wavelet approach towards examining dynamic association, causality and spillovers." International Journal of Data and Network Science 3, no. 1 (2019): 23-36.
AMA: Ghosh, I & Chaudhuri, T. A wavelet approach towards examining dynamic association, causality and spillovers. International Journal of Data and Network Science. 2019;3(1):23-36.
References
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Arouri, M. E. H., Jouini, J., & Nguyen, D. K. (2012). On the impacts of oil price fluctuations on Euro-pean equity markets: Volatility spillover and hedging effectiveness. Energy Economics, 34(2), 611-617.
Baek, E., & Brock, W. (1992). A general test for nonlinear Granger causality: Bivariate model, Iowa State University and University of Wisconsin At Madison, Working Paper (1992).
Basher, S. A., & Sadorsky, P. (2016). Hedging emerging market stock prices with oil, gold, VIX, and bonds: A comparison between DCC, ADCC and GO-GARCH. Energy Economics, 54, 235–247.
Bhatia, V., Das, D., Tiwari, A. K., Shabaz, M., & Hasim, H. M. (2018). Do precious metal spot prices influence each other? Evidence from anonparametric causality-in-quantiles approach. Resources Pol-icy, 55, 244–252.
Das, D., Kannadhasan, M., Al-Yahyaee, K. H., & Yoon, S. M. (2018). A wavelet analysis of co-movements in Asian gold market. Physica A: Statistical Mechanics and its Applications, 492, 192-206.
Das, D., Kannadhasan, M., Tiwari, A. K., & Al-Yahyaee, K. H. (2018). Has co-movement dynamics in emerging stock markets changed after global financial crisis? New evidence from wavelet analysis. Applied Economics Letters, 25, 1447-1453.
Diks, C., & Panchenko, V. (2006). A new statistic and practical guidelines for nonparametric Granger causality testing. Journal of Economic Dynamics and Control, 9, 1647–1669.
Genc, T. S. (2017). OPEC and demand response to crude oil prices. Energy Economics, 66, 238-246.
Ghosh, I., & Datta Chaudhuri, T. (2016). Understanding and forecasting stock market volatility through wavelet decomposition, statistical learning and econometric methods. SSRN Electronic Journal, DOI: 10.2139/ssrn.2930876.
Ghosh, I., & Datta Chaudhuri, T. (2017). Fractal investigation and maximal overlap discrete wavelet transformation (MODWT)-based machine learning framework for forecasting exchange rates. Stud-ies in Microeconomics, 5, 105-131.
Hiemstra, C., & Jones, J. D. (1994). Testing for linear and nonlinear Granger causality in the stock price-volume relation. Journal of Finance, 49, 1639–1664.
Jammazi, R., Ferrer, R., Jareno, F., & Shahzad, J. (2017). Time-varying causality between crude oil and stock markets: What can we learn from a multiscale perspective? International Review of Economics & Finance, 49, 453-483.
Jothimoni, D., Shankar, R., & Yadav, S. S. (2015). Discrete wavelet transform-based prediction of stock index: A study on national stock exchange fifty index. Journal of Financial Management and Analysis, 28, 35-49.
Kalbaska, A., & Gatkowski, M. (2012). Eurozone sovereign contagion: Evidence from the CDS market (2005–2010), Journal of Economic Behavior & Organization, 83, 657-673.
Kaura, R., Kishor, N., & Rajput, N. (2018). Price discovery and volatility Spillvers: Evidence from non-agricultural commodity market in India. Iup journal of Financial Risk Management, 15, 7-31.
Kazemi, H., & Sohrabji, N. (2012). Contagion in Europe: Examining the PIIGS crisis. International Ad-vances in Economic Research, 18, 455-456.
Klößner, S., & Sekkel, R. (2014) International spillovers of policy uncertainty. Economics Letters, 124, 508–512.
Liu, X., An, H., Huang, S., & Wen, S. (2017). The evolution of spillover effects between oil and stock markets across multi-scales using wavelet based GARCH-BEKK model. Physica A: Statistical Me-chanics and its Applications, 465, 374-383.
Mensi, W., Tiwari, A., Bouri, E., Roubaud, D., & Al-Yahyaee, K. (2017). The dependence structure across oil, wheat, and corn: A wavelet-based copula approach using implied volatility indices. Ener-gy Economics, 66, 122-139.
Polanco-Martinez, J. M., Fernandez-Macho, J., Neumann, M. B., & Faria, S. H. (2018). A pre-crisis vs. crisis analysis of peripheral EU stock markets by means of wavelet transform and a nonlinear causali-ty test. Physica A: Statistical Mechanics and its Applications, 490, 1211-1227.
Reboredo, J. C., Rivera-Castro, M. A., & Ugolini, A. (2017). Wavelet-based test of co-movement and causality between oil and renewable energy stock prices. Energy Economics, 61, 241–252.
Sadorsky, P. (2014). Modeling volatility and correlations between emerging market stock prices and the prices of copper, oil and wheat. Energy Economics, 43, 72–81.
Sen, J., & Datta Chaudhuri, T. (2016). An investigation of the structural characteristics of the Indian IT sector and the capital goods sector – An application of the R programming in time series decomposi-tion and forecasting. Journal of Insurance and Financial Management, 1, 68-131.
Singhal, S., & Ghosh, S. (2016). Returns and volatility linkages between international crude oil price, metal and other stock indices in India: Evidence from VAR-DCC-GARCH models. Resources Poli-cy, 50, 276-288.
Shahbaz, M., Balcilar, M., & Ozdemir, Z. A. (2017). Does oil predict gold? A nonparametric causality-in-quantiles approach. Resources Policy, 52, 257–265.
Arouri, M. E. H., Jouini, J., & Nguyen, D. K. (2012). On the impacts of oil price fluctuations on Euro-pean equity markets: Volatility spillover and hedging effectiveness. Energy Economics, 34(2), 611-617.
Baek, E., & Brock, W. (1992). A general test for nonlinear Granger causality: Bivariate model, Iowa State University and University of Wisconsin At Madison, Working Paper (1992).
Basher, S. A., & Sadorsky, P. (2016). Hedging emerging market stock prices with oil, gold, VIX, and bonds: A comparison between DCC, ADCC and GO-GARCH. Energy Economics, 54, 235–247.
Bhatia, V., Das, D., Tiwari, A. K., Shabaz, M., & Hasim, H. M. (2018). Do precious metal spot prices influence each other? Evidence from anonparametric causality-in-quantiles approach. Resources Pol-icy, 55, 244–252.
Das, D., Kannadhasan, M., Al-Yahyaee, K. H., & Yoon, S. M. (2018). A wavelet analysis of co-movements in Asian gold market. Physica A: Statistical Mechanics and its Applications, 492, 192-206.
Das, D., Kannadhasan, M., Tiwari, A. K., & Al-Yahyaee, K. H. (2018). Has co-movement dynamics in emerging stock markets changed after global financial crisis? New evidence from wavelet analysis. Applied Economics Letters, 25, 1447-1453.
Diks, C., & Panchenko, V. (2006). A new statistic and practical guidelines for nonparametric Granger causality testing. Journal of Economic Dynamics and Control, 9, 1647–1669.
Genc, T. S. (2017). OPEC and demand response to crude oil prices. Energy Economics, 66, 238-246.
Ghosh, I., & Datta Chaudhuri, T. (2016). Understanding and forecasting stock market volatility through wavelet decomposition, statistical learning and econometric methods. SSRN Electronic Journal, DOI: 10.2139/ssrn.2930876.
Ghosh, I., & Datta Chaudhuri, T. (2017). Fractal investigation and maximal overlap discrete wavelet transformation (MODWT)-based machine learning framework for forecasting exchange rates. Stud-ies in Microeconomics, 5, 105-131.
Hiemstra, C., & Jones, J. D. (1994). Testing for linear and nonlinear Granger causality in the stock price-volume relation. Journal of Finance, 49, 1639–1664.
Jammazi, R., Ferrer, R., Jareno, F., & Shahzad, J. (2017). Time-varying causality between crude oil and stock markets: What can we learn from a multiscale perspective? International Review of Economics & Finance, 49, 453-483.
Jothimoni, D., Shankar, R., & Yadav, S. S. (2015). Discrete wavelet transform-based prediction of stock index: A study on national stock exchange fifty index. Journal of Financial Management and Analysis, 28, 35-49.
Kalbaska, A., & Gatkowski, M. (2012). Eurozone sovereign contagion: Evidence from the CDS market (2005–2010), Journal of Economic Behavior & Organization, 83, 657-673.
Kaura, R., Kishor, N., & Rajput, N. (2018). Price discovery and volatility Spillvers: Evidence from non-agricultural commodity market in India. Iup journal of Financial Risk Management, 15, 7-31.
Kazemi, H., & Sohrabji, N. (2012). Contagion in Europe: Examining the PIIGS crisis. International Ad-vances in Economic Research, 18, 455-456.
Klößner, S., & Sekkel, R. (2014) International spillovers of policy uncertainty. Economics Letters, 124, 508–512.
Liu, X., An, H., Huang, S., & Wen, S. (2017). The evolution of spillover effects between oil and stock markets across multi-scales using wavelet based GARCH-BEKK model. Physica A: Statistical Me-chanics and its Applications, 465, 374-383.
Mensi, W., Tiwari, A., Bouri, E., Roubaud, D., & Al-Yahyaee, K. (2017). The dependence structure across oil, wheat, and corn: A wavelet-based copula approach using implied volatility indices. Ener-gy Economics, 66, 122-139.
Polanco-Martinez, J. M., Fernandez-Macho, J., Neumann, M. B., & Faria, S. H. (2018). A pre-crisis vs. crisis analysis of peripheral EU stock markets by means of wavelet transform and a nonlinear causali-ty test. Physica A: Statistical Mechanics and its Applications, 490, 1211-1227.
Reboredo, J. C., Rivera-Castro, M. A., & Ugolini, A. (2017). Wavelet-based test of co-movement and causality between oil and renewable energy stock prices. Energy Economics, 61, 241–252.
Sadorsky, P. (2014). Modeling volatility and correlations between emerging market stock prices and the prices of copper, oil and wheat. Energy Economics, 43, 72–81.
Sen, J., & Datta Chaudhuri, T. (2016). An investigation of the structural characteristics of the Indian IT sector and the capital goods sector – An application of the R programming in time series decomposi-tion and forecasting. Journal of Insurance and Financial Management, 1, 68-131.
Singhal, S., & Ghosh, S. (2016). Returns and volatility linkages between international crude oil price, metal and other stock indices in India: Evidence from VAR-DCC-GARCH models. Resources Poli-cy, 50, 276-288.
Shahbaz, M., Balcilar, M., & Ozdemir, Z. A. (2017). Does oil predict gold? A nonparametric causality-in-quantiles approach. Resources Policy, 52, 257–265.