Asymmetric causality using frequency domain and time-frequency domain (wavelet) approaches

Bahmani‐Oskooee, Mohsen; Chang, Tsangyao; Ranjbar, Omid

doi:10.1016/j.econmod.2016.03.002

Cited by 30 publications

(19 citation statements)

References 23 publications

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“…Our results are in line with that Areal et al, (2016), Fatima and Ahmed (2019). See also (Bahmani-oskooee et al, 2016); (Li et al, 2014); (Jammazi & Reboredo, 2016); (Yang et al, 2017); (Fernández-macho, 2012); (Boubaker & Ali, 2017); (Lawal, Nwanji, Adama & Otekunrin, 2017) The results of the structural breaks show the existence of heterogeneous structural breaks points (Ti). It is appropriate to question whether or not the break points as presented are realistic or coincide with significant changes in the global political and socio-economic space.…”

Section: Conducting Research and Resultsmentioning

confidence: 99%

“…Given the advantages of the frequency-based wavelet unit root tests over the existing time domain unit root tests, the current study employed the former to examine whether or not agricultural commodity prices follow a random walk processes or mean reverting procedure. The use of wavelet analysis is important to economic agents as it can, for instance, offer market practitioners the opportunity to analyze their investment horizons in different frequency bonds of scale when making portfolio decisions (Hathroubi & Aloui, 2016;Bahmani-oskooee, Chang, & Ranjbar, 2016;Yang, Jing, Zhang, & Hamori, 2016;Ayopo, Isola, & Olukayode, 2016a;Jammazi & Reboredo, 2016;(Martín-barragán, Ramos, & Veiga, 2015).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Testing mean-reversion in agricultural commodity prices: Evidence from wavelet analysis

Lawal¹,

Omoju²,

Babajide³

et al. 2019

Journal of International Studies

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This study examines the validity of the random walk hypothesis for some selected soft agricultural commodity prices within the context of heterogeneous market hypothesis and mean reversion hypothesis. The study employs a battery of traditional unit root tests, GARCH-based models and a novel frequency-based wavelet analysis to analyze daily data sourced from 6th of Jan 1986 to 29 th Dec 2018. Contrary to other existing studies that employed only traditional time domain unit root tests, our results reveal that soft commodity prices are mean reverting, suggesting the existence of potential excess returns for investors. Overall, our results show that the selected soft commodity series are inefficient when we factored in heteroscedascity and frequency domain into our model. Our study is an improvement on the existing studies as we analyze our data using both time and frequency domain estimates. Besides, unlike other studies that did not offer structural breaks, the current study provides structural break dates with major events in the global socioeconomic space, which are key to identifying the date of bubbles and potential signs of commodity price bubbles. Our findings have some critical implications for investors, policy makers,

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Section: Conducting Research and Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Testing mean-reversion in agricultural commodity prices: Evidence from wavelet analysis

Lawal¹,

Omoju²,

Babajide³

et al. 2019

Journal of International Studies

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show abstract

“…Knowing that neglecting nonlinearity as well as structural changes in the data generating process distort the results towards accepting the null of a unit root, it is expedient to test for nonlinearity and structural changes in the oil prices by employing unit root test with a Fourier function as proposed by (Bahmani-Oskooee et al, 2016). We estimate equation ( 5) for each integer k = 1 …5, such that a single frequency is used to account for a wide variety of breaks as shown in panel A of Table 3.…”

Section: Resultsmentioning

confidence: 99%

“…Data for the study was obtained from the US EIA. The study followed (Bahmani-Oskooee et al, 2016) to model mean reversion properties in oil prices using both sharp and smooth breaks using the following equation:…”

Section: Methodsmentioning

confidence: 99%

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Lawal¹,

Babajide²,

Nwanji³

et al. 2018

IJEEP

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This study examined the validity of efficiency market hypothesis for the oil market by employing a novel Fourier unit root test that accounts for sharp shifts and smooth breaks based on daily data. Our results established the existence of structural shifts and nonlinearity in the oil market indices suggesting that oil market is inefficient when structural breaks is calibrated into the model. Unlike results obtained from existing traditional unit root test, results from sharp shifts and smooth breaks unit root test suggests the rejection of unit root null for each of the oil indices. The study has some practical and policy implications based on our findings.

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“…Incluso en diseño de filtros, como en [4], donde se propone un algoritmo para la selección automática del filtros que permitan suprimir el ruido generado naturalmente por trenes de pulsos. El análisis en el dominio frecuencial ha sido también aplicado en procesamiento de señales [5], [6], estudio de vibración de estructuras [7], respuestas sísmicas [8], medición de índices de refracción [9], espectroscopia [10], análisis de los sonidos producidos durante perforaciones [11], entre otros [12]- [14]. También, en el campo eléctrico se han desarrollado estudios encaminadas a la implementación de sistemas de conversión de energía mareomotriz usando una turbina regulada por pitch y un generador de inducción, el análisis en el dominio frecuencial en dicha investigación es empleada a la hora de considerar estrategias de control de velocidad que permitan operar al sistema al máximo de su potencia [15].…”

Section: Controlador Plantaunclassified

Diseño de Sistemas de Control Basados en el Análisis del Dominio en Frecuencia

Pinzón¹,

Pavón²

2019

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El trabajo presenta un análisis de los sistemas en el dominio de frecuencias, dado importancia y amplio uso para diferentes áreas de la ciencia y la ingeniería como el diseño de sistemas de control. Vinculado al análisis del dominio en frecuencia, se ocupa del uso de la herramienta gráfica de los diagramas de Bode, que se utiliza para visualizar las acciones necesarias para que los sistemas propuestos sean estables a través de la inclusión de varios controladores como PI o PID. Los resultados obtenidos permiten corroborar la importancia y el potencial del análisis en el dominio de frecuencias para los casos comunes de sistemas expresados como funciones de transferencia.

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Asymmetric causality using frequency domain and time-frequency domain (wavelet) approaches

Cited by 30 publications

References 23 publications

Testing mean-reversion in agricultural commodity prices: Evidence from wavelet analysis

Testing mean-reversion in agricultural commodity prices: Evidence from wavelet analysis

Untitled

Diseño de Sistemas de Control Basados en el Análisis del Dominio en Frecuencia

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