Unit Root Tests in Time Series Volume 2

Patterson, Kerry

doi:10.1057/9781137003317

Cited by 18 publications

(9 citation statements)

References 204 publications

(514 reference statements)

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“…There are key issues to consider when introducing a structural break in a model. First, it is important to specify the effect of the break; the full impact of the break can be immediate or sequentially distributed over time (Patterson, ). Perron () distinguishes two types of structural break models, the additive outlier (AO) and the innovative outlier (IO).…”

Section: Econometric Methodsmentioning

confidence: 99%

Testing for nonlinear unit roots in the presence of a structural break with an application to the qualified PPP during the 1997 Asian financial crisis

2018

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This paper applies Monte Carlo simulations to evaluate the size and power properties in the presence of a structural break, for the standard Augmented Dickey‐Fuller (ADF) test versus nonlinear exponential smooth transition autoregressive unit root tests. The break causes the tests to be undersized, and the statistical power considerably decreases. Moreover, the effect is intensified in small samples and very much increased for more persistent nonlinear series. As a remedy, we modify the standard ADF and exponential smooth transition autoregressive unit root tests in order to adjust for a structural break. This improves both the power and the size considerably, even though the empirical size still is lower than the nominal one. More persistent series are more affected by structural breaks, and the new tests are most powerful under the existence of a rather persistent nonlinear data generating process (which is an empirically relevant and common type of data generating process). The proposed tests are applied to investigate mean reversion in the real effective exchange rates of 5 East and Southeast Asian countries, taking into account the structural change in exchange rate regime brought about by the 1997 Asian financial crisis. The empirical findings corroborate our simulation results; the modified more powerful tests are able to reject the unit root in all 5 countries, whereas the tests that do not consider the structural break could only reject in one of these cases.

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Section: Econometric Methodsmentioning

confidence: 99%

Testing for nonlinear unit roots in the presence of a structural break with an application to the qualified PPP during the 1997 Asian financial crisis

2018

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“…The null hypothesis and alternative hypothesis of KSS test are now H0: d = 0 and H1: d < 0. See Kapetanios et al (2006Kapetanios et al ( , 2003 and Patterson (2012) for more details about KSS test characteristics.…”

Section: Non-stationary Processes and Unit-root Testmentioning

confidence: 99%

Evaluation of dynamic cointegration-based pairs trading strategy in the cryptocurrency market

Tadi

Kortchemski

2021

SEF

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Purpose This paper aims to demonstrate a dynamic cointegration-based pairs trading strategy, including an optimal look-back window framework in the cryptocurrency market and evaluate its return and risk by applying three different scenarios. Design/methodology/approach This study uses the Engle-Granger methodology, the Kapetanios-Snell-Shin test and the Johansen test as cointegration tests in different scenarios. This study calibrates the mean-reversion speed of the Ornstein-Uhlenbeck process to obtain the half-life used for the asset selection phase and look-back window estimation. Findings By considering the main limitations in the market microstructure, the strategy of this paper exceeds the naive buy-and-hold approach in the Bitmex exchange. Another significant finding is that this study implements a numerous collection of cryptocurrency coins to formulate the model’s spread, which improves the risk-adjusted profitability of the pairs trading strategy. Besides, the strategy’s maximum drawdown level is reasonably low, which makes it useful to be deployed. The results also indicate that a class of coins has better potential arbitrage opportunities than others. Originality/value This research has some noticeable advantages, making it stand out from similar studies in the cryptocurrency market. First is the accuracy of data in which minute-binned data create the signals in the formation period. Besides, to backtest the strategy during the trading period, this study simulates the trading signals using best bid/ask quotes and market trades. This study exclusively takes the order execution into account when the asset size is already available at its quoted price (with one or more period gaps after signal generation). This action makes the backtesting much more realistic.

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“…This is not an exhaustive review, as there are too many URTs to cover in a single article. For more thorough reviews see Refs .…”

Section: Urt Surveymentioning

confidence: 99%

“…A relatively short yet very comprehensive book on URTs which has been referred to in this article is Ref , which includes many topics not included in this review such as additional URTs, fractional unit roots, panel unit roots, seasonal unit roots and Bayesian inference methods in unit roots. Perhaps the most extensive and complete books on URTs covering key concepts and extensions Refs 11 and 12.…”

mentioning

confidence: 99%

Unit root tests

Herranz

2017

WIREs Computational Stats

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Unit roots are nonstationary autoregressive (AR) or autoregressive moving average (ARMA) time series processes which may include an intercept and/or a trend. These processes are used often in economics and finance, but can also be found in other scientific fields. Unit root tests address the null hypothesis of a unit root, and an alternative hypothesis of a stationary (or trend stationary) time series. Critical values for unit root tests are typically derived via simulation of limiting distributions expressed as functionals of Brownian motions. The critical values for the Dickey Fuller unit root test with a constant and linear trend are derived via simulation in the R language. Simulation studies are presented showing that linear regressions with unit root processes often produce spurious results. Additional simulation studies are reviewed providing statistical evidence that near-unit roots can often result in spurious cointegration relationships. Various unit root tests are presented, including ones that allow for structural breaks in intercept and/or trend. Threshold unit root tests are introduced. Simulation studies are used to compare the unit root tests under various scenarios. The case where the analyzed time series may have stationary and nonstationary segments is also considered.

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Unit Root Tests in Time Series Volume 2

Cited by 18 publications

References 204 publications

Testing for nonlinear unit roots in the presence of a structural break with an application to the qualified PPP during the 1997 Asian financial crisis

Testing for nonlinear unit roots in the presence of a structural break with an application to the qualified PPP during the 1997 Asian financial crisis

Evaluation of dynamic cointegration-based pairs trading strategy in the cryptocurrency market

Unit root tests

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