Long-Term Dependency Structure and Structural Breaks: Evidence from the U.S. Sector Returns and Volatility

2018 ◽  
Vol 21 (02) ◽  
pp. 1850008 ◽  
Author(s):  
Geoffrey Ngene ◽  
Ann Nduati Mungai ◽  
Allen K. Lynch
Keyword(s):  
Long Memory ◽  
Structural Breaks ◽  
Parameter Estimates ◽  
Dependency Structure ◽  
Fractional Differencing ◽  
Short Memory ◽  
The Impact ◽  
Sector Returns ◽  
Daily Returns

The study investigates the impact of structural breaks on the long memory of daily returns and variance of 11 sectors. Using multiple sequential structural breaks tests, we uncover numerous and roughly shared structural breaks. Results from two non-parametric, three semi-parametric, and three parametric fractional differencing models using break-adjusted and break-unadjusted returns reveal incidence of short memory and anti-persistence in sector returns. Regarding variance, we find that the removal of breaks from the sector series dampens the fractional differencing parameter estimates. Therefore, the observed long memory in variance may be attributable to the occurrence of structural breaks in the sector series.

Testing for long memory in the presence of a general trend

2001 ◽  
Vol 38 (04) ◽  
pp. 1033-1054 ◽  
Author(s):  
Liudas Giraitis ◽  
Piotr Kokoszka ◽  
Remigijus Leipus
Keyword(s):  
Long Memory ◽  
Change Point ◽  
General Trend ◽  
Quantitative Description ◽  
Stationary Sequence ◽  
Change Points ◽  
Asymptotic Size ◽  
Short Memory ◽  
The Impact ◽  
Do So

The paper studies the impact of a broadly understood trend, which includes a change point in mean and monotonic trends studied by Bhattacharyaet al.(1983), on the asymptotic behaviour of a class of tests designed to detect long memory in a stationary sequence. Our results pertain to a family of tests which are similar to Lo's (1991) modifiedR/Stest. We show that both long memory and nonstationarity (presence of trend or change points) can lead to rejection of the null hypothesis of short memory, so that further testing is needed to discriminate between long memory and some forms of nonstationarity. We provide quantitative description of trends which do or do not fool theR/S-type long memory tests. We show, in particular, that a shift in mean of a magnitude larger thanN-½, whereNis the sample size, affects the asymptotic size of the tests, whereas smaller shifts do not do so.

Testing for long memory in the presence of a general trend

2001 ◽  
Vol 38 (4) ◽  
pp. 1033-1054 ◽  
Author(s):  
Liudas Giraitis ◽  
Piotr Kokoszka ◽  
Remigijus Leipus
Keyword(s):  
Long Memory ◽  
Change Point ◽  
General Trend ◽  
Quantitative Description ◽  
Stationary Sequence ◽  
Change Points ◽  
Asymptotic Size ◽  
Short Memory ◽  
The Impact ◽  
Do So

The paper studies the impact of a broadly understood trend, which includes a change point in mean and monotonic trends studied by Bhattacharyaet al.(1983), on the asymptotic behaviour of a class of tests designed to detect long memory in a stationary sequence. Our results pertain to a family of tests which are similar to Lo's (1991) modifiedR/Stest. We show that both long memory and nonstationarity (presence of trend or change points) can lead to rejection of the null hypothesis of short memory, so that further testing is needed to discriminate between long memory and some forms of nonstationarity. We provide quantitative description of trends which do or do not fool theR/S-type long memory tests. We show, in particular, that a shift in mean of a magnitude larger thanN-½, whereNis the sample size, affects the asymptotic size of the tests, whereas smaller shifts do not do so.

Modeling volatility of Indian exchange rates under the impact of regime shifts: A study with economic significance analysis

2018 ◽  
Vol 12 (1) ◽  
pp. 43-59
Author(s):  
Dilip Kumar
Keyword(s):  
Exchange Rates ◽  
Long Memory ◽  
Structural Breaks ◽  
Forecast Accuracy ◽  
Regime Shifts ◽  
Policy Implications ◽  
Economic Significance ◽  
Volatility Model ◽  
Modeling Volatility ◽  
The Impact

In this paper, we assess the impact of regime shifts on the long memory properties of the Indian exchange rates. We make use of Sanso, Arago and Carrion (2004) Iterated Cumulative Sum of Squares (hereafter referred as AIT-ICSS) algorithm to detect the points of structural breaks in volatility series. Our findings indicate that incorporating the impact of sudden changes in volatility in the model indeed reduces the magnitude of long memory parameter. In the case of INR/JPY, we observe a shift in characteristics from long memory to mean reversion when the impact of regime shifts is included in the volatility model. Our findings also highlight that incorporating the impact of regime shifts in the model also improves the volatility forecast accuracy. Moreover, we implement a trading strategy based on risk-averse investor and find that the volatility forecasts based on the model which incorporate the impact of structural breaks provide substantial gains in return in comparison to volatility models with no structural breaks. These findings have important policy implications for financial market participants, investors and policy makers.

Revisiting the nexus between financial development, FDI, and growth: New evidence from second generation econometric procedures in the Turkish context

2014 ◽  
Vol 64 (1) ◽  
pp. 73-89 ◽  
Author(s):  
Hasan Güngör ◽  
Salih Katircioglu ◽  
Mehmet Mercan
Keyword(s):  
Financial Development ◽  
Structural Breaks ◽  
Second Generation ◽  
Real Income ◽  
Annual Data ◽  
Multiple Structural Breaks ◽  
Equilibrium Relationship ◽  
The Impact ◽  
First Time

This study investigates the impact of the selected financial development proxies and foreign direct investment (FDI) on the growth in the case of Turkey, using annual data for the 1960–2011 period. The second-generation econometric procedure has been applied for the first time to the Turkish data with this respect. Unit root tests by Carrion-i-Silvestre et al. (2009) assume that real income, financial development proxies, and FDI are non-stationary at levels, but become stationary at first differences through multiple structural breaks. Cointegration results by Maki (2012) confirm the existence of a long-term equilibrium relationship between real income growth, financial development, and FDI, again through multiple structural breaks. Finally, this paper confirms that financial development and FDI are long-term drivers of real income, which enable it to react to its long-term path significantly.

scholarly journals Testing for long memory in volatility in the Indian Forex market

2014 ◽  
Vol 59 (203) ◽  
pp. 75-90 ◽  
Author(s):  
Anoop Kumar
Keyword(s):  
Long Memory ◽  
Foreign Exchange Market ◽  
Memory Models ◽  
Conditional Variance ◽  
Forecast Performance ◽  
Conditional Mean ◽  
The Us ◽  
Short Memory ◽  
Two Measures

This article attempts to verify the presence of long memory in volatility in the Indian foreign exchange market using daily bilateral returns of the Indian Rupee against the US dollar from 17/02/1994 to 08/11/2013. In the first part of the analysis the presence of long-term dependence is confirmed in the return series as well as in two measures of unconditional volatility (absolute returns and squared returns) by employing three measures of long memory. Next, the presence of long memory in conditional volatility is tested using ARMA-FIGARCH and ARMA-FIAPARCH models under various distributional assumptions. The results confirm the presence of long memory in conditional variance for two models. In the last part, the presence of long memory in conditional mean and conditional variance is verified using ARFIMA-FIGARCH and ARFIMA-FIAPARCH models. It is also found that long-memory models fare well compared to short-memory models in sample forecast performance.

scholarly journals Short memory or long memory: an empirical survey of daily rainfall data

2012 ◽  
Vol 9 (10) ◽  
pp. 12271-12291
Author(s):  
F. Yusof ◽  
I. L. Kane
Keyword(s):  
Long Memory ◽  
Structural Breaks ◽  
Structural Break ◽  
Daily Rainfall ◽  
Least Square ◽  
Rainfall Data ◽  
Data Sets ◽  
Original Series ◽  
Daily Rainfall Data ◽  
Short Memory

Abstract. A short memory process that encounters occasional structural breaks in mean can show a slower rate of decay in the autocorrelation function and other properties of fractional integrated I (d) processes. In this paper we employed a procedure for estimating the fractional differencing parameter in semi parametric contexts proposed by Geweke and Porter-Hudak to analyze nine daily rainfall data sets across Malaysia. The results indicate that all the data sets exhibit long memory. Furthermore, an empirical fluctuation process using the Ordinary Least Square (OLS) based cumulative sum (CUSUM) test with F-statistic for the break date were applied, break dates were detected in all data sets. The data sets were partitioned according to their respective break date and further test for long memory was applied for all subseries. Results show that all subseries follows the same pattern with the original series. The estimate of the fractional parameters d1 and d2 on the subseries obtained by splitting the original series at the break-date, confirms that there is a long memory in the DGP. Therefore this evidence shows a true long memory not due to structural break.

Regime switching with structural breaks in output convergence

2018 ◽  
Vol 22 (3) ◽  
Author(s):  
Fuat C. Beylunioğlu ◽  
Thanasis Stengos ◽  
M. Ege Yazgan
Keyword(s):  
Long Memory ◽  
Regime Switching ◽  
Structural Breaks ◽  
Viterbi Algorithm ◽  
Markov Switching ◽  
Gap Series ◽  
Statistical Computation ◽  
The Em Algorithm ◽  
Fractional Differencing ◽  
Over Time

AbstractIn this paper, we examine empirically GDP per capita convergence using an approach that explicitly allows for regime switching in the long memory parameterdwithin the context of a Markov Switching (MS)–ARFIMA framework. As existing methods used in the estimation of standard MS models, such as the EM algorithm are no longer appropriate, we will make use of the Viterbi algorithm to estimate the long memory MS model used by Tsay and Härdle (Tsay, W.-J., and W. K. Härdle. 2009. “A Generalized Arfima Process with Markov-Switching Fractional Differencing Parameter.”Journal of Statistical Computation and Simulation79: 731–745.). We will classify the output gap series into two regimes, a highdand a lowdregime, where a highdclose to unity would imply persistence and lack of convergence. By examining the path ofdparameter over time which enables us to observe non-convergent behavior in more detail, we find that converging behavior is diminishing over time and divergence is the dominant force.

scholarly journals Examining the Impact of Structural Breaks on Long Memory of Stock Returns: Evidence from Bombay Stock Exchange of India Long Memory

2020 ◽  
Vol 19 (1) ◽  
Author(s):  
Anju Bala
Keyword(s):  
Stock Returns ◽  
Long Memory ◽  
Hurst Exponent ◽  
Structural Breaks ◽  
Stock Exchange ◽  
Subprime Crisis ◽  
Range Analysis ◽  
Rescaled Range Analysis ◽  
Daily Stock Returns ◽  
The Impact

This study examines the presence of long memory of Stock Returns in India with reference to structural breaks. The study used the Hurst Exponent in Rescaled Range Analysis as proposed by Lo (1991) to measure the presence of long memory on daily stock returns of the Bombay Stock Exchange Indices from January 2000 to December 2017. The analysis indicates that all indices show long memory effects. It is also evident that all indices exhibit long memory effect in the pre and post subprime crisis period. These findings are consistent with Bhattacharya and Bhattacharya (2018), Jha et al.(2018), Goudarzi (2010) and Lillo and Farmer (2004). KEYWORDS: Long Memory, Hurst exponent, Market Efficiency. Structural Breaks

Long memory in the R$ / US$ exchange rate: A robust analysis

2004 ◽  
Vol 24 (1) ◽  
pp. 109 ◽  
Author(s):  
Márcio Poletti Laurini ◽  
Marcelo Savino Portugal
Keyword(s):  
Exchange Rate ◽  
Long Memory ◽  
Structural Breaks ◽  
Monte Carlo Study ◽  
Markov Switching Model ◽  
Switching Model ◽  
Short Memory ◽  
Variance Parameters ◽  
Short Memory Process ◽  
Unconditional Variance

This article shows that the evidence of long memory for the daily R$ /US$ exchange rate series after the implementation of the Real Plan is not robust when we analyze the existence of structural breaks in this series. We demonstrate that the long memory observed is caused by changes in the structure of variance, captured by a Markov Switching model in all the parameters. A Monte Carlo study shows that the long memory structure can be induced by changes in the unconditional variance parameters, and that the data generating mechanism is a short memory process.

On the estimation of short memory components in long memory time series models

2016 ◽  
Vol 20 (4) ◽  
Author(s):  
Richard T. Baillie ◽  
George Kapetanios
Keyword(s):  
Time Series ◽  
Long Memory ◽  
Time Series Models ◽  
Memory Process ◽  
Long Memory Process ◽  
Fractional Differencing ◽  
Memory Time ◽  
Short Memory ◽  
Short Memory Process ◽  
Memory Parameter

AbstractA substantial amount of recent time series research has emphasized semi-parameteric estimators of a long memory parameter and we provide a selective review of the literature on this issue. We consider such estimators applied to the issue of estimating the parameters relating to a short memory process which is embedded within the long memory process. We consider the fractional differencing filter and the subsequent properties of a two step estimator of the short memory parameters. We conclude that while the semi-parametric estimators can have excellent properties in terms of estimating the long memory parameter, they do not have good properties when applied to the two step estimator of short memory

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