Does gold act as a hedge against inflation in the UK? Evidence from a fractional cointegration approach over 1257 to 2016

Aye, Goodness C.; Cárcel, Héctor; Gil-Alana, Luís A.; Gupta, Rangan

doi:10.1016/j.resourpol.2017.09.001

Cited by 70 publications

(44 citation statements)

References 39 publications

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“…Second, we apply the mean and variance equality test to check for the equality of the slopes for downward and upward trends. We carry out the Singhal et al (2019) and Aye et al (2017) mean equality tests of, and two variance equality tests of Levene (1960) and Brown and Forsythe (1974) . The results are reported in Table 4 and show evidence of significant mean differences for the Hurst exponent for different trends and sub-periods.…”

Section: Empirical Analysis Resultsmentioning

confidence: 99%

“…Gold is a store of value and is used for investment and hedging purposes. In fact, gold is a safe haven asset in financial markets ( Baur and Lucey, 2010 ), energy markets ( Reboredo, 2013 ), and during inflation growth ( Aye et al, 2017 ) and is further used by many central banks as an asset in their reserves. Moreover, the demand for crude oil and gold has been increasing over the last two decades, particularly due to growing emerging market economies like China.…”

Section: Introductionmentioning

confidence: 99%

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Impact of COVID-19 outbreak on asymmetric multifractality of gold and oil prices

et al. 2020

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This paper examines the impacts of COVID-19 on the multifractality of gold and oil prices based on upward and downward trends. We apply the Asymmetric Multifractal Detrended Fluctuation Analysis (A-MF-DFA) approach to 15-min interval intraday data. The results show strong evidence of asymmetric multifractality that increases as the fractality scale increases. Moreover, multifractality is especially higher in the downside (upside) trend for Brent oil (gold), and this excess asymmetry has been more accentuated during the COVID-19 outbreak. Before the outbreak, the gold (oil) market was more inefficient during downward (upward) trends. During the COVID-19 outbreak period, we see that the results have changed. More precisely, we find that gold (oil) is more inefficient during upward (downward) trends. Gold and oil markets have been inefficient, particularly during the outbreak. The efficiency of gold and oil markets is sensitive to scales, market trends, and to the pandemic outbreak, highlighting the investor sentiment effect.

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Section: Empirical Analysis Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Impact of COVID-19 outbreak on asymmetric multifractality of gold and oil prices

et al. 2020

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“…Matlab computer programs, provided by Nielsen and Popiel (2018) for the calculation of estimators and test statistics in the FCVAR model, have been employed in numerous empirical papers (Baruník and Dvořáková, 2015;Maciel, 2017;Aye et al, 2017;Dolatabadi et al, 2018;Jones, Nielsen and Popiel, 2018;Gil-Alana and Carcel, 2018;etc. ).…”

Section: Fractional Cointegrated Varmentioning

confidence: 99%

Lithium industry and the U.S. crude oil prices. A fractional cointegration VAR and a Continuous Wavelet Transform analysis

Monge

Gil-Alana

2021

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This paper analyzes the dynamics of U.S. lithium mining companies, the lithium industry and West Texas Intermediate (WTI) crude oil prices using a Fractional Cointegration Vector AutoRegressive model (FCVAR model) and a Continuous Wavelet Transform (CWT) for its resolution. The results indicate evidence of a negative relationship between FMC Corp with Albermale and SQM stock prices. These results are similar if we analyze the risk based on the beta term structure of each company. Analyzing the fractional differencing parameter for the stock prices and their logs, we observe that they are very persistent, and there are no long-term deviations in the stock prices. The same happens when analyzing the beta term structure. Based on Continuous Wavelet Transform (CWT) methods, our results show that lithium mining companies and the lithium industry are weakly correlated with WTI crude oil prices at higher frequencies (short-run) and persist through the sample period. At lower frequencies (long-term) the time series reached a high level of dependence between late 2012 to mid 2016, concluding that the lithium mining companies and the lithium industry reflect and foreshadow the responsiveness of the WTI crude oil prices during the period mentioned above.

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“…Additionally, we can find two parameters compared with the CVAR model. The order of fractional integration of the observable time series is represented by d and the level of reduction in the fractional integration order of β 0 X t is represented by the parameter b. Matlab computer programmes for the calculation of estimators and test statistics in the FCVAR model are provided by Nielsen and Popiel (2018) 1 and have been employed in numerous empirical papers (Jones, Nielsen, and Popiel 2014;Baruník and Dvořáková 2015;Maciel 2017;Aye et al, 2017;Dolatabadi et al 2018; Gil-Alana and Carcel 2020; etc. ).…”

Section: Fractional Integrationmentioning

confidence: 99%

Mean reversion in monetary aggregates in Chile

et al. 2020

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In this paper we examine the statistical properties of the monetary aggregates in Chile in order to know if the time series display mean reverting behaviour. For this purpose, we use techniques based on fractional integration. Monthly data of various Chilean monetary aggregates from January 1986 until August 2019 are used, and the results indicate very weak evidence of mean reversion. In fact, this property is only found in the case of the currency on circulation and M1 for some of the series examined; however, for M2 and M3 the results clearly show high persistence with orders of integration substantially higher than 1. Thus, shocks are expected to have a permanent nature in these cases. Another remarkable feature observed in the results is that the level of persistence in the series seems to grow with the amount of the monetary aggregate. In a multivariate context, performing a FCVAR model, evidence of cointegration is found among the monetary aggregates, finding a long run equilibrium relationship between them.

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Does gold act as a hedge against inflation in the UK? Evidence from a fractional cointegration approach over 1257 to 2016

Cited by 70 publications

References 39 publications

Impact of COVID-19 outbreak on asymmetric multifractality of gold and oil prices

Impact of COVID-19 outbreak on asymmetric multifractality of gold and oil prices

Lithium industry and the U.S. crude oil prices. A fractional cointegration VAR and a Continuous Wavelet Transform analysis

Mean reversion in monetary aggregates in Chile

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