Spurious Relationships for Nearly Non-Stationary Series

Cheng, Yushan; Hui, Yi; McAleer, Michael; Wong, Wing‐Keung

doi:10.3390/jrfm14080366

Cited by 6 publications

(4 citation statements)

References 21 publications

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“…This paper uses panel autoregressive distributed lag (ARDL) models to examine the effect of economic policy uncertainty, gold, oil, and Bitcoin prices on sustainable investment returns. Extensions of our paper could include using our approach to study other important issues, for example funding liquidity (Abbas et al 2021), examining four-moment modified value at risk and conditional value at risk (using Cornish-Fisher Expansion) of different mixed portfolios pairing the assets under study (equity-oil and equity-gold portfolios) (Ali et al 2021) and nearly non-stationary series (Cheng et al 2021). There are many important issues to which academics and practitioners could apply the approach used in this paper.…”

Section: Discussionmentioning

confidence: 99%

The Economic Policy Uncertainty and Its Effect on Sustainable Investment: A Panel ARDL Approach

Darsono

Wong

Nguyen

et al. 2022

JRFM

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This study examines the effect of economic policy uncertainty (EPU) on sustainable investment returns by using panel data of stock market returns and the EPU index from twelve countries for the period from April 2015 to December 2020. In addition, precious metal prices, energy prices, and cryptocurrency prices are used as control variables. To do so, we investigate the impact of EPU, gold prices, oil prices, and Bitcoin prices on stock market returns by using the panel autoregressive distributed lag (ARDL) model to examine both the long-run correlation and short-run effect. Our findings show that EPU, gold prices, oil prices, and Bitcoin prices have a time-varying significant impact on sustainable stock market returns. We discovered that EPU has a significantly negative impact on the returns of the sustainable stocks in the markets over the long run. In contrast, the rise of the gold price, oil price, and Bitcoin price have a significantly positive impact on the returns of the sustainable stocks in the twelve sustainable markets in the long run. On the other hand, EPU in Singapore, Spain, the Netherlands, and Russia has a significant short-run impact on market returns in each country. Based on the findings, managers and investors in the sustainable stock markets are highly recommended to pay more attention to the volatility of EPU, gold prices, oil prices, and Bitcoin prices in the short run to control the risk of returns in the sustainable stock market. Furthermore, policymakers must closely monitor the movement of the EPU index, as it is a major driver of sustainable stock market returns.

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Section: Discussionmentioning

confidence: 99%

The Economic Policy Uncertainty and Its Effect on Sustainable Investment: A Panel ARDL Approach

Darsono

Wong

Nguyen

et al. 2022

JRFM

Self Cite

View full text Add to dashboard Cite

show abstract

“…Checking the stationarity properties of the data is a prerequisite for analyzing the cointegration. The regression estimates based on non-stationary data will generate spurious regression ( Cheng et al, 2021 ). Therefore, to obtain efficient estimates, we have analyzed the stationarity characteristics of the data.…”

Section: Methodology and Modelmentioning

confidence: 99%

Natural resources for policy makers: Revisiting COVID-19 perspective of aggregate South Asian economies

Yang

Jia

2023

Resources Policy

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“…We take into account two types of time series models, a pure AR(1) model and a AR(1) model with a constant or a constant plus linear time trend. Recently, the asymptotic inference for a least squares (LS) estimate when the autoregressive parameter is close to 1 (i.e., the series is nearly non-stationary) has been receiving considerable attention in the statistics and econometric literature, such as Chan [22] and Cheng [23]. Therefore, we are also interested in deriving the asymptotic behavior of the proposed test in the context of the near-unit root.…”

Section: Introductionmentioning

confidence: 99%

Modified Block Bootstrap Testing for Persistence Change in Infinite Variance Observations

Zhang,

Jin,

2024

Mathematics

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This paper investigates the properties of the change in persistence detection for observations with infinite variance. The innovations are assumed to be in the domain of attraction of a stable law with index κ∈(0,2]. We provide a new test statistic and show that its asymptotic distribution under the null hypothesis of non-stationary I(1) series is a functional of a stable process. When the change point in persistence is not known, the consistency is always given under the alternative, either from stationary I(0) to non-stationary I(1) or vice versa. The proposed tests can be used to identify the direction of change and do not over-reject against constant I(0) series, even in relatively small samples. Furthermore, we also consider the change point estimator which is consistent and the asymptotic behavior of the test statistic in the case of near-integrated time series. A block bootstrap method is suggested to determine critical values because the null asymptotic distribution contains the unknown tail index, which results in critical values depending on it. The simulation study demonstrates that the block bootstrap-based test is robust against change in persistence for heavy-tailed series with infinite variance. Finally, we apply our methods to the two series of the US inflation rate and USD/CNY exchange rate, and find significant evidence for persistence changes, respectively, from I(0) to I(1) and from I(1) to I(0).

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Spurious Relationships for Nearly Non-Stationary Series

Cited by 6 publications

References 21 publications

The Economic Policy Uncertainty and Its Effect on Sustainable Investment: A Panel ARDL Approach

The Economic Policy Uncertainty and Its Effect on Sustainable Investment: A Panel ARDL Approach

Natural resources for policy makers: Revisiting COVID-19 perspective of aggregate South Asian economies

Modified Block Bootstrap Testing for Persistence Change in Infinite Variance Observations

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