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Multi-scale tests for serial correlation

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Cited by:

  1. Mengya Liu & Fukan Zhu & Ke Zhu, 2020. "Multi-frequency-band tests for white noise under heteroskedasticity," Papers 2004.09161, arXiv.org.
  2. Shahzad, Syed Jawad Hussain & Kumar, Ronald Ravinesh & Ali, Sajid & Ameer, Saba, 2016. "Interdependence between Greece and other European stock markets: A comparison of wavelet and VMD copula, and the portfolio implications," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 8-33.
  3. Li, Linyuan & Duchesne, Pierre & Liou, Chu Pheuil, 2021. "On diagnostic checking in ARMA models with conditionally heteroscedastic martingale difference using wavelet methods," Econometrics and Statistics, Elsevier, vol. 19(C), pages 169-187.
  4. Zhang, Hao & Cai, Guixin & Yang, Dongxiao, 2020. "The impact of oil price shocks on clean energy stocks: Fresh evidence from multi-scale perspective," Energy, Elsevier, vol. 196(C).
  5. Bekiros, Stelios & Boubaker, Sabri & Nguyen, Duc Khuong & Uddin, Gazi Salah, 2017. "Black swan events and safe havens: The role of gold in globally integrated emerging markets," Journal of International Money and Finance, Elsevier, vol. 73(PB), pages 317-334.
  6. Xyngis, Georgios, 2017. "Business-cycle variation in macroeconomic uncertainty and the cross-section of expected returns: Evidence for scale-dependent risks," Journal of Empirical Finance, Elsevier, vol. 44(C), pages 43-65.
  7. Yazgan, M. Ege & Özkan, Harun, 2015. "Detecting structural changes using wavelets," Finance Research Letters, Elsevier, vol. 12(C), pages 23-37.
  8. Boubaker Heni & Canarella Giorgio & Miller Stephen M. & Gupta Rangan, 2017. "Time-varying persistence of inflation: evidence from a wavelet-based approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(4), pages 1-18, September.
  9. Bekiros, Stelios & Gupta, Rangan, 2015. "Predicting stock returns and volatility using consumption-aggregate wealth ratios: A nonlinear approach," Economics Letters, Elsevier, vol. 131(C), pages 83-85.
  10. Fosten, Jack, 2019. "CO2 emissions and economic activity: A short-to-medium run perspective," Energy Economics, Elsevier, vol. 83(C), pages 415-429.
  11. Faria, Gonçalo & Verona, Fabio, 2018. "Forecasting stock market returns by summing the frequency-decomposed parts," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 228-242.
  12. Uddin, Gazi Salah & Hernandez, Jose Areola & Shahzad, Syed Jawad Hussain & Yoon, Seong-Min, 2018. "Time-varying evidence of efficiency, decoupling, and diversification of conventional and Islamic stocks," International Review of Financial Analysis, Elsevier, vol. 56(C), pages 167-180.
  13. Yan Ding & Yue Liu & Pierre Failler, 2022. "The Impact of Uncertainties on Crude Oil Prices: Based on a Quantile-on-Quantile Method," Energies, MDPI, vol. 15(10), pages 1-35, May.
  14. Li, Meiyu & Gençay, Ramazan, 2017. "Tests for serial correlation of unknown form in dynamic least squares regression with wavelets," Economics Letters, Elsevier, vol. 155(C), pages 104-110.
  15. Thomas Conlon & John Cotter & Ramazan Gençay, 2015. "Long-run international diversification," Working Papers 201502, Geary Institute, University College Dublin.
  16. Conlon, Thomas & Cotter, John & Gençay, Ramazan, 2018. "Long-run wavelet-based correlation for financial time series," European Journal of Operational Research, Elsevier, vol. 271(2), pages 676-696.
  17. Mo, Bin & Chen, Cuiqiong & Nie, He & Jiang, Yonghong, 2019. "Visiting effects of crude oil price on economic growth in BRICS countries: Fresh evidence from wavelet-based quantile-on-quantile tests," Energy, Elsevier, vol. 178(C), pages 234-251.
  18. Li, Zijian & Meng, Qiaoyu, 2022. "Time and frequency connectedness and portfolio diversification between cryptocurrencies and renewable energy stock markets during COVID-19," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
  19. Antonis A. Michis, 2022. "Multiscale Partial Correlation Clustering of Stock Market Returns," JRFM, MDPI, vol. 15(1), pages 1-22, January.
  20. Bruzda, Joanna, 2017. "Real and complex wavelets in asset classification: An application to the US stock market," Finance Research Letters, Elsevier, vol. 21(C), pages 115-125.
  21. Zhu, Huiming & Meng, Liang & Ge, Yajing & Hau, Liya, 2020. "Dependent relationships between Chinese commodity markets and the international financial market: Evidence from quantile time-frequency analysis," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
  22. Yang, Lu & Cai, Xiao Jing & Zhang, Huimin & Hamori, Shigeyuki, 2016. "Interdependence of foreign exchange markets: A wavelet coherence analysis," Economic Modelling, Elsevier, vol. 55(C), pages 6-14.
  23. Saâdaoui, Foued & Naifar, Nader & Aldohaiman, Mohamed S., 2017. "Predictability and co-movement relationships between conventional and Islamic stock market indexes: A multiscale exploration using wavelets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 552-568.
  24. Roy, Archi & Soni, Anchal & Deb, Soudeep, 2023. "A wavelet-based methodology to compare the impact of pandemic versus Russia–Ukraine conflict on crude oil sector and its interconnectedness with other energy and non-energy markets," Energy Economics, Elsevier, vol. 124(C).
  25. Yonghong JIANG & Juan MENG & He NIE, 2018. "Visiting the Economic Policy Uncertainty Shocks - Economic Growth Relationship: Wavelet-based Granger-Causality in Quantiles Approac," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 80-94, December.
  26. Berger, Theo & Gençay, Ramazan, 2018. "Improving daily Value-at-Risk forecasts: The relevance of short-run volatility for regulatory quality assessment," Journal of Economic Dynamics and Control, Elsevier, vol. 92(C), pages 30-46.
  27. Lao, Jiashun & Nie, He & Jiang, Yonghong, 2018. "Revisiting the investor sentiment–stock returns relationship: A multi-scale perspective using wavelets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 420-427.
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