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Journal articles on the topic 'Fractional cointegration analysis'

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Published: 9 March 2023
Last updated: 10 March 2023

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1

Marinucci, D., and P. M. Robinson. "Semiparametric fractional cointegration analysis." Journal of Econometrics 105, no. 1 (November 2001): 225–47. http://dx.doi.org/10.1016/s0304-4076(01)00076-8.

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2

Olaniran, Saidat Fehintola, and Mohd Tahir Ismail. "A Comparative Analysis of Semiparametric Tests for Fractional Cointegration in Panel Data Models." Austrian Journal of Statistics 51, no. 4 (August 26, 2022): 96–119. http://dx.doi.org/10.17713/ajs.v51i4.1170.

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Several authors have studied fractional cointegration in time series data, but little or no consideration has been extended to panel data settings. Therefore, in this paper, we compare the finite sample behaviour of existing fractional cointegration time-series test procedures in panel data settings. This comparison is performed to determine the best tests that can be adapted to fractional cointegration in panel data settings. Specifically, simulation studies and real-life data analysis were performed to study the changes in the empirical type I error rate and power of six semiparametric fractional cointegration tests in panel settings. The various results revealed the limitations of the tests in the nonstationary and low or high correlation of the residual errors conditions. Also, two of the test procedures were recommended for testing the null hypothesis of no fractional cointegration in both time series and panel data settings.
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3

Beliu *, Sonila, and Matthew L. Higgins. "Fractional cointegration analysis of EU convergence." Applied Economics 36, no. 14 (August 10, 2004): 1607–11. http://dx.doi.org/10.1080/0003684042000217931.

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4

Mohanty, Samarendu, E. Wesley F. Peterson, and Darnell B. Smith. "Fractional Cointegration and the False Rejection of the Law of One Price in International Commodity Markets." Journal of Agricultural and Applied Economics 30, no. 2 (December 1998): 267–76. http://dx.doi.org/10.1017/s1074070800008270.

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AbstractThis study examines the Law of One Price (LOP) in international commodity markets using fractional cointegration analysis. For proper evaluation of the LOP, fractional cointegration analysis seems to be appropriate because of its flexibility in capturing a wider range of mean reversion behavior than standard cointegration analysis. Out of nine pairs of price series examined, fractional cointegration supports the existence of the LOP in eight cases, as compared to three cases using standard cointegration procedures. Overall, these results suggest that there is a long-run tendency for the LOP to hold for commodity prices.
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5

Kolaiti, Theoplasti, Mwasi Mboya, and Philipp Sibbertsen. "Volatility Transmission across Financial Markets: A Semiparametric Analysis." Journal of Risk and Financial Management 13, no. 8 (July 24, 2020): 160. http://dx.doi.org/10.3390/jrfm13080160.

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This paper revisits the question whether volatilities of different markets and trading zones have a long-run equilibrium in the sense that they are fractionally cointegrated. We consider the U.S., Japanese and German stock, bond and foreign exchange markets to see whether there is fractional cointegration between the markets in one trading zone or for one market across trading zones. Also the other combinations of different markets in different trading zones are considered. Applying a purely semiparametric approach through the whole analysis shows fractional cointegration can only be found for a small minority of different cases. Investigating further we find that all volatility series show persistence breaks during the observation period which may be a reason for different findings in previous studies.
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6

Kasman, Saadet, Adnan Kasman, and Evrim Turgutlu. "Fisher Hypothesis Revisited: A Fractional Cointegration Analysis." Emerging Markets Finance and Trade 42, no. 6 (December 2006): 59–76. http://dx.doi.org/10.2753/ree1540-496x420604.

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7

Serrano, Camilo, and Martin Hoesli. "Fractional Cointegration Analysis of Securitized Real Estate." Journal of Real Estate Finance and Economics 44, no. 3 (January 7, 2010): 319–38. http://dx.doi.org/10.1007/s11146-009-9231-x.

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8

Martin, Gael M. "BAYESIAN ANALYSIS OF A FRACTIONAL COINTEGRATION MODEL." Econometric Reviews 20, no. 2 (April 30, 2001): 217–34. http://dx.doi.org/10.1081/etc-100103824.

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9

Cheung, Yin-Wong, and Kon S. Lai. "A Fractional Cointegration Analysis of Purchasing Power Parity." Journal of Business & Economic Statistics 11, no. 1 (January 1993): 103. http://dx.doi.org/10.2307/1391310.

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10

Cheung, Yin-Wong, and Kon S. Lai. "A Fractional Cointegration Analysis of Purchasing Power Parity." Journal of Business & Economic Statistics 11, no. 1 (January 1993): 103–12. http://dx.doi.org/10.1080/07350015.1993.10509936.

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11

Gil-Alana, Luis A., and Hector Carcel. "A fractional cointegration var analysis of exchange rate dynamics." North American Journal of Economics and Finance 51 (January 2020): 100848. http://dx.doi.org/10.1016/j.najef.2018.09.006.

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12

Kiran, Burcu. "A fractional cointegration analysis of Fisher hypothesis: evidence from Turkey." Quality & Quantity 47, no. 2 (August 20, 2011): 1077–84. http://dx.doi.org/10.1007/s11135-011-9584-0.

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13

Caporale, Guglielmo Maria, and Luis A. Gil-Alana. "Long-term interest rates in Europe: A fractional cointegration analysis." International Review of Economics & Finance 61 (May 2019): 170–78. http://dx.doi.org/10.1016/j.iref.2019.02.004.

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14

Nielsen, Morten Ørregaard. "Nonparametric cointegration analysis of fractional systems with unknown integration orders." Journal of Econometrics 155, no. 2 (April 2010): 170–87. http://dx.doi.org/10.1016/j.jeconom.2009.10.002.

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15

Selmi, Nadhem. "A Fractional Cointegration Analysis of Purchasing Power Parity: Evidence of ELW." International Journal of Management and Sustainability 3, no. 11 (March 10, 2015): 664–72. http://dx.doi.org/10.18488/journal.11/2014.3.11/11.11.664.672.

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This study examines the long-run relationship between exchange rates and relative prices. We use a long memory techniques that allow for persistence of chock relationships across real exchange rate to examine the existence of weak-form and strong-form Purchasing Power Parity (PPP) between the Tunisian and five partner countries of Tunisia, namely, (Germany, the United States, France, Italy, the UK, Morocco and Libya. The empirical results obtained through the R/S, Modified R/S, GPH and ELW tests; make us consider the PPP as an event in the long run if significant short-term deviations from the PPP cannot exist. Therefore, the analysis of the fractional cointegration makes the deviations, regarding equilibrium, follow a slightly integrated process and therefore capture a much wider group of research parity or mean-reverting behavior.
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16

Hsueh, L. Paul, and Ming-Shiun Pan. "Integration of International Long-Term Interest Rates: A Fractional Cointegration Analysis." Financial Review 33, no. 3 (August 1998): 213–24. http://dx.doi.org/10.1111/j.1540-6288.1998.tb01392.x.

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17

Salisu, Afees A., Umar B. Ndako, Idris A. Adediran, and Raymond Swaray. "A fractional cointegration VAR analysis of Islamic stocks: A global perspective." North American Journal of Economics and Finance 51 (January 2020): 101056. http://dx.doi.org/10.1016/j.najef.2019.101056.

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18

de Menezes, Lilian M., and Melanie A. Houllier. "Reassessing the integration of European electricity markets: A fractional cointegration analysis." Energy Economics 53 (January 2016): 132–50. http://dx.doi.org/10.1016/j.eneco.2014.10.021.

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19

Booth, G. Geoffrey, and Yiuman Tse. "Long memory in interest rate futures markets: A fractional cointegration analysis." Journal of Futures Markets 15, no. 5 (August 1995): 573–84. http://dx.doi.org/10.1002/fut.3990150505.

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20

Seitaridis, Michail I., Nikolaos S. Thomaidis, and Pandelis N. Biskas. "Fundamental Responsiveness in European Electricity Prices." Energies 14, no. 22 (November 15, 2021): 7623. http://dx.doi.org/10.3390/en14227623.

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We estimate fundamental pricing relationships in selected European day-ahead electricity markets. Using a fractionally integrated panel data model with unobserved common effects, we quantify the responsiveness of hourly electricity prices to two fundamental leading indicators of day-ahead markets: the predicted load and renewable generation. The application of fractional cointegration analysis techniques gives further insight into the pricing mechanism of power delivery contracts, enabling us to measure the persistence of fundamental shocks.
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21

Franco, G. C., V. A. Reisen, and F. A. Alves. "Bootstrap tests for fractional integration and cointegration: A comparison study." Mathematics and Computers in Simulation 87 (January 2013): 19–29. http://dx.doi.org/10.1016/j.matcom.2012.11.011.

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22

de Truchis, Gilles. "Approximate Whittle analysis of fractional cointegration and the stock market synchronization issue." Economic Modelling 34 (August 2013): 98–105. http://dx.doi.org/10.1016/j.econmod.2012.12.011.

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23

Caporale, Guglielmo Maria, and Luis Alberiko Gil-Alana. "Gold and silver as safe havens: A fractional integration and cointegration analysis." PLOS ONE 18, no. 3 (March 3, 2023): e0282631. http://dx.doi.org/10.1371/journal.pone.0282631.

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This paper investigates whether gold and silver can be considered safe havens by examining their long-run linkages with 13 stock price indices. More specifically, the stochastic properties of the differential between gold/silver prices and 13 stock indices are analysed applying fractional integration/cointegration methods to daily data, first for a sample from January 2010 until December 2019, then for one from January 2020 until June 2022 which includes the Covid-19 pandemic. The results can be summarised as follows. In the case of the pre-Covid-19 sample ending in December 2019, mean reversion is found for the gold price differential only vis-à-vis a single stock index (SP500). whilst in seven other cases, although the estimated value of d is below 1, the value 1 is inside the confidence interval and thus the unit root null hypothesis cannot be rejected. In the remaining cases the estimated values of d are significantly higher than 1. As for the silver differential, the upper bound is 1 only in two cases, whilst in the others mean reversion does not occur. Thus, the evidence is mixed on whether these precious metals can be seen as safe havens, though it appears that this property characterises gold in a slightly higher number of cases. By contrast, when using the sample starting in January 2020, the evidence in favour of gold and silver as possible safe havens is pretty conclusive since mean reversion is only found in a single case, namely that of the gold differential vis-à-vis the New Zealand stock index.
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24

Nielsen, Morten Ørregaard. "Local Whittle Analysis of Stationary Fractional Cointegration and the Implied–Realized Volatility Relation." Journal of Business & Economic Statistics 25, no. 4 (October 2007): 427–46. http://dx.doi.org/10.1198/073500106000000314.

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25

Liu, Shi-Miin, and Chih-Hsien Chou. "Parities and Spread Trading in Gold and Silver Markets: A Fractional Cointegration Analysis." Applied Financial Economics 13, no. 12 (December 2003): 899–911. http://dx.doi.org/10.1080/0960310032000129626.

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26

Luis, A. Gil Alana, Balparda Borja, and Maria Caporale Guglielmo. "Exchange rate dynamics and monetary unions in Africa: A fractional integration and cointegration analysis." African Journal of Business Management 9, no. 22 (November 28, 2015): 752–61. http://dx.doi.org/10.5897/ajbm2015.7803.

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27

Kiran, Burcu. "Fractional Cointegration Relationship between Oil Prices and Stock Markets: An Empirical Analysis from G7 Countries." Prague Economic Papers 20, no. 2 (January 1, 2011): 177–89. http://dx.doi.org/10.18267/j.pep.395.

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28

Kasman, Adnan, Saadet Kirbas-Kasman, and Evrim Turgutlu. "Nominal and real convergence between the CEE countries and the EU: a fractional cointegration analysis." Applied Economics 37, no. 21 (December 10, 2005): 2487–500. http://dx.doi.org/10.1080/00036840500366312.

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29

Gil-Alana, L. A. "Long-Term Statistical Relationships in Political Science: An Analysis Based on Fractional Integration and Cointegration." Open Political Science Journal 1, no. 1 (February 25, 2007): 5–16. http://dx.doi.org/10.2174/1874949600801010005.

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30

Mosconi, Rocco, and Paolo Paruolo. "A Conversation with Søren Johansen." Econometrics 10, no. 2 (April 13, 2022): 21. http://dx.doi.org/10.3390/econometrics10020021.

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This article was prepared for the Special Issue “Celebrated Econometricians: Katarina Juselius and Søren Johansen” of Econometrics. It is based on material recorded on 30 October 2018 in Copenhagen. It explores Søren Johansen’s research, and discusses inter alia the following issues: estimation and inference for nonstationary time series of the I(1), I(2) and fractional cointegration types; survival analysis; statistical modelling; likelihood; econometric methodology; the teaching and practice of Statistics and Econometrics.
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31

WONG, WING-KEUNG, HABIBULLAH KHAN, and JUN DU. "DO MONEY AND INTEREST RATES MATTER FOR STOCK PRICES? AN ECONOMETRIC STUDY OF SINGAPORE AND USA." Singapore Economic Review 51, no. 01 (April 2006): 31–51. http://dx.doi.org/10.1142/s0217590806002214.

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This paper examines the long-term as well as short-term equilibrium relationships between the major stock indices and selected macroeconomic variables (such as money supply and interest rate) of Singapore and the United States by employing the advanced time series analysis techniques that include cointegration, Johansen multivariate cointegrated system, fractional cointegration and Granger causality. The cointegration results based on data covering the period January 1982 to December 2002 suggest that Singapore's stock prices generally display a long-run equilibrium relationship with interest rate and money supply (M1) but a similar relationship does not hold for the United States. To capture the short-run dynamics of the relationship, we replicate the same experiments with different subsets of data representing shorter time periods. It is evident that stock markets in Singapore moved in tandem with interest rate and money supply before the Asian Crisis of 1997, but this pattern was not observed after the crisis. In the United States, stock prices were strongly cointegrated with macroeconomic variables before the 1987 equity crisis but the relationships gradually weakened and totally disappeared with the emergence of Asian Crisis that also indirectly affected the United States. The results of fractional cointegration and the Johansen multivariate system are consistent with the earlier cointegration results that both Singapore and US stock markets did possess equilibrium relationships with M1 and interest rate at the early days. However, the stability of the systems was disturbed by a series of well-known financial turbulence in the past two decades and eventually weakened for Singapore and completely disappeared for the US. This may imply that monetary authority may take action to respond to the asset price turbulence in order to maintain the stability of monetary economy and thus break the existing equilibrium between stock markets and macroeconomic variables like interest rate and M1. Another possible explanation is that the market became more efficient after 1997 Asian crisis. Finally, the results of Granger causality tests uncover some systematic causal relationships, implying that stock market performance might be a good gauge for Central Bank's monetary policy adjustment.
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32

Gil-Alana, Luis A., OlaOluwa S. Yaya, and Olushina O. Awe. "Time series analysis of co-movements in the prices of gold and oil: Fractional cointegration approach." Resources Policy 53 (September 2017): 117–24. http://dx.doi.org/10.1016/j.resourpol.2017.06.006.

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33

Monge, Manuel, and Luis A. Gil-Alana. "Lithium industry and the U.S. crude oil prices. A fractional cointegration VAR and a Continuous Wavelet Transform analysis." Resources Policy 72 (August 2021): 102040. http://dx.doi.org/10.1016/j.resourpol.2021.102040.

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34

Aloy, Marcel, and Gilles de Truchis. "Optimal Estimation Strategies for Bivariate Fractional Cointegration Systems and the Co-persistence Analysis of Stock Market Realized Volatilities." Computational Economics 48, no. 1 (October 12, 2015): 83–104. http://dx.doi.org/10.1007/s10614-015-9531-6.

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35

Gil-Alana, Luis A., and OlaOluwa S. Yaya. "The relationship between oil prices and the Nigerian stock market. An analysis based on fractional integration and cointegration." Energy Economics 46 (November 2014): 328–33. http://dx.doi.org/10.1016/j.eneco.2014.10.001.

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36

Caporale, Guglielmo Maria, Juncal Cunado, Luis A. Gil-Alana, and Rangan Gupta. "The relationship between healthcare expenditure and disposable personal income in the US states: a fractional integration and cointegration analysis." Empirical Economics 55, no. 3 (July 8, 2017): 913–35. http://dx.doi.org/10.1007/s00181-017-1297-3.

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37

Triki, Mohamed Bilel, and Samir Maktouf. "Purchasing power parity as a long-term memory process." International Journal of Emerging Markets 10, no. 4 (September 21, 2015): 711–25. http://dx.doi.org/10.1108/ijoem-02-2012-0021.

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Purpose – The purpose of this paper is to focus on whether the deviations from the cointegrating relationship possess long memory and the fractional cointegration analyses may capture a wider range of mean-reversion behaviour than standard cointegration analyses. Design/methodology/approach – This paper uses a fractional cointegration technique to test the purchasing power parity (PPP). Findings – The authors found that PPP held, but very weakly, in the long run between the Argentine, Brazil, Chile, Colombia, Indonesia, Korea, Mexico, Thailand and Venezuela and US exchange rate during our floating exchange rate period but that the deviations from it did not follow a stationary process. Nevertheless, it is also found that the deviations from PPP exists and can be characterized by a fractionally integrated process in nine out of 13 countries studied. Originality/value – The findings are consistent with the consensus of the empirical literature, reviewed earlier in this paper, on PPP between Argentine, Brazil, Chile, Colombia, Indonesia, Korea, Mexico, Thailand and Venezuela and the USA.
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38

Jung, Sukwan, and Doohwan Won. "Comovement and Forecast of won/dollar, yuan/dollar, yen/dollar: Application of Fractional Cointegration approach and Causal Analysis of Frequency Domain." International Area Studies Review 21, no. 2 (June 30, 2017): 3–20. http://dx.doi.org/10.21212/iasr.21.2.1.

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39

Masih, A. Mansur M., and Rumi Masih. "Fractional cointegration, low frequency dynamics and long-run purchasing power parity: an analysis of the Australian dollar over its recent float." Applied Economics 36, no. 6 (April 10, 2004): 593–605. http://dx.doi.org/10.1080/0003684042000217634.

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40

Masih, Abul M. M., and Rumi Masih. "A fractional cointegration analysis of the long-run relationship between black and official foreign exchange rates: the case of the Brazilian cruzeiro." Applied Economics 30, no. 7 (July 1998): 853–61. http://dx.doi.org/10.1080/000368498325282.

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41

Poza, Carlos, and Manuel Monge. "A real time leading economic indicator based on text mining for the Spanish economy. Fractional cointegration VAR and Continuous Wavelet Transform analysis." International Economics 163 (October 2020): 163–75. http://dx.doi.org/10.1016/j.inteco.2020.02.002.

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42

Maciel, Leandro Dos Santos, and Rosangela Ballini. "On the predictability of high and low prices: The case of Bitcoin." Brazilian Review of Finance 17, no. 3 (October 15, 2019): 66. http://dx.doi.org/10.12660/rbfin.v17n1.2019.77578.

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<p>Bitcoin has attracted the attention of investors lately due to its significant market capitalization and high volatility. This work considers the modeling and forecasting of daily high and low Bitcoin prices using a fractionally cointegrated vector autoregressive (FCVAR) model. As a flexible framework, FCVAR is able to account for two fundamental patterns of high and low financial prices: their cointegrating relationship and the long memory of their difference (i.e., the range), which is a measure of realized volatility. The analysis comprises the period from January 2012 to February 2018. Empirical findings indicate a significant cointegration relationship between daily high and low Bitcoin prices, which are integrated on an order close to the unity, and the evidence of long memory for the range. Results also indicate that high and low Bitcoin prices are predictable, and the fractionally cointegrated approach appears as a potential forecasting tool for<br />cryptocurrencies market practitioners.</p>
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43

Phillips, Peter C. B. "LOCAL LIMIT THEORY AND SPURIOUS NONPARAMETRIC REGRESSION." Econometric Theory 25, no. 6 (December 2009): 1466–97. http://dx.doi.org/10.1017/s0266466609990223.

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A local limit theorem is proved for sample covariances of nonstationary time series and integrable functions of such time series that involve a bandwidth sequence. The resulting theory enables an asymptotic development of nonparametric regression with integrated or fractionally integrated processes that includes the important practical case of spurious regressions. Some local regression diagnostics are suggested for forensic analysis of such regresssions, including a localR2and a local Durbin–Watson (DW) ratio, and their asymptotic behavior is investigated. The most immediate findings extend the earlier work on linear spurious regression (Phillips, 1986,Journal of Econometrics33, 311–340) showing that the key behavioral characteristics of statistical significance, lowDWratios and moderate to highR2continue to apply locally in nonparametric spurious regression. Some further applications of the limit theory to models of nonlinear functional relations and cointegrating regressions are given. The methods are also shown to be applicable in partial linear semiparametric nonstationary regression.
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44

Serrano, Camilo, and Martin Hoesli. "Fractional Cointegration Analysis of Securitized Real Estate." SSRN Electronic Journal, 2009. http://dx.doi.org/10.2139/ssrn.1365704.

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45

Nielsen, Morten Ørregaard. "Nonparametric Cointegration Analysis of Fractional Systems with Unknown Integration Orders." SSRN Electronic Journal, 2009. http://dx.doi.org/10.2139/ssrn.1326422.

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46

Wajid Shakeel Ahmed, Ahsan Mehmood, Talha Sheikh, and Allah Bachaya. "Unveiling the linkages between emerging stock market indices and cryptocurrencies." Asian Academy of Management Journal 27, no. 2 (December 7, 2022). http://dx.doi.org/10.21315/aamj2022.27.2.9.

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This paper investigated the relationship between cryptocurrencies and emerging stock market indices using fractional integration and co-integration technique. Particularly, fractional integration is applied to examine stochastic properties of individual assets and fractional cointegration to analyse bivariate connectedness. Our findings unveil the absence of mean reversion in majority cases which indicates high persistence in series. Furthermore, bivariate analysis reveals disconnection between cryptocurrencies prices and stock indices. Surprisingly, a different picture emerges on using conditional volatility instead of prices. Like, conditional volatility-based estimation uncovers evidence of mean reversion in univariate analysis as expected. There is some evidence of cointegration on volatility grounds between cryptocurrencies and emerging stock market indices. Our findings implies that investment decision regarding digital currencies should be taken cautiously. As cryptocurrencies are extremely volatile with high degree of persistence which can make them counterproductive.
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47

Rossi, Eduardo, and Paolo Santucci de Magistris. "A No Arbitrage Fractional Cointegration Analysis of the Range Based Volatility." SSRN Electronic Journal, 2009. http://dx.doi.org/10.2139/ssrn.1434792.

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48

Gil-Alana, Luis, Cecilia Font, and Águeda Gil-López. "GDP and population growth: Evidence of fractional cointegration with historical data from 1820 onwards." Journal of Economic Studies ahead-of-print, ahead-of-print (March 11, 2021). http://dx.doi.org/10.1108/jes-06-2020-0307.

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PurposeUsing data from 1820 onwards in a group of seven countries, namely, Australia, Chile, Denmark, France, the UK, Italy and the USA, the authors investigate if there is a long-run equilibrium relationship between the two variables (GDP and population).Design/methodology/approachUsing fractional integration and cointegration methods, this paper deals with the analysis of the relationship between GDP and population using historical data.FindingsThe authors’ results show first that the two series are highly persistent, presenting orders of integration close to or above 1 in practically all cases. Testing cointegration between the two variables, the results are quite variable depending on the methodology and the bandwidth numbers used, but if cointegration takes places, it only occurs in the cases of France, Italy and the UK.Research limitations/implicationsThe fact that the orders of integration of all series is close to 1 indicate high levels of persistence with shocks having permanent effects and requiring strong measures to recover the original trends.Practical implicationsAny shock affecting the series will have a permanent nature, persisting forever.Originality/valueUpdated time series techniques based on concepts such as fractional integration and cointegration are used.
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49

Christensen, Bent Jesper, and Morten Ørregaard Nielsen. "Semiparametric Analysis of Stationary Fractional Cointegration and the Implied-Realized Volatility Relation." SSRN Electronic Journal, 2001. http://dx.doi.org/10.2139/ssrn.279883.

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50

Caporale, Guglielmo Maria, and Luis A. Gil-Alana. "Gold and Silver as Safe Havens: A Fractional Integration and Cointegration Analysis." SSRN Electronic Journal, 2022. http://dx.doi.org/10.2139/ssrn.4279173.

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