A unit root model for trending time-series energy variables

By Paresh Kumar Narayan, Ruipeng Liu. 2015

148 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/812d3ebd992862756d48d1cd80acbbe0057df699

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Citations in the corpus

Modelling oil price-inflation nexus: The role of asymmetries (2017, background): “…Iraq in 2003, 2004/2005 OPEC’s agreement to reduce official production, 2007 global financial crisis, and the current civil unrest in the middle east have been documented to have influenced the behaviour of oil price globally [see Noguera, 2013; Salisu and Fasanya, 2013; and Narayan and Liu, 2015].”
Pandemics and the Asia-Pacific Islamic Stocks (2020, unknown): “Further application of Narayan and Liu (2015) unit root model for trending time series.”
Uncertainty Due to Infectious Diseases and Energy Market Volatility (2020, methodology): “The GARCH-based unit root test is the one proposed by Narayan and Liu (2015) and it is considered an alternative to the Narayan and Popp (2010) test due to the data frequency used in this study (see also Salisu & Adeleke, 2016). where is the energy volatility based on the CBOE calculations; is the…”
Assessing the safe haven property of the gold market during COVID-19 pandemic (2021, methodology): “The model is specified in such as to control for endogeneity bias (that may result from omitting other predictors of gold returns), conditional heteroscedasticity effect (due to the use of high frequency data) and persistence (which is typical of most financial and economic time series) (see Westerl”
Improving the predictability of the oil–US stock nexus: The role of macroeconomic variables (2019, methodology): “Here, the model for the single-factor case ( Sk ) is the parsimonious model, having been found to be a good predictive model for US stock returns by Westerlund and Narayan (2015), while the model for the multiple-factor case ( Mk ) is the larger model.”