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Publications
Publications (51)
Bootstrapping time series requires dealing with the dependence that may exist within the sample. Several strategies have been proposed, but their validity has only been proven for short memory series and there has been little progress in their theoretical properties under long memory, where strong persistence may invalidate conventional techniques....
Estimation of the Value at risk (VaR) requires prediction of the future volatility. Whereas this is a simple task in ARCH and related models, it becomes much more complicated in Stochastic Volatility (SV) processes where the volatility is a function of a latent variable that is not observable. In‐sample (present and past values) and out‐of‐sample (...
A generalization of the Exact Local Whittle estimator in Shimotsu and Phillips (2005, Annals of Statistics 33, 1890–1933) is proposed for jointly estimating all the memory parameters in general long memory time series that possibly display standard, seasonal, and/or other cyclical strong persistence. Consistency and asymptotic normality are proven...
This paper consider the classical principal component analysis (PCA) in multivariate time series with conditional heteroscedasticity, since ignore these features may lead to erroneous conclusions , if the PCA is adopted in techniques such as dimensionality reduction, factor analysis, cluster analysis, source identification, detection of outliers, l...
This article seeks to extend knowledge of the mackerel (Scomber scombrus) market in the Basque Country (a region in Spain) by analysing possible relationships between this and other species with similar characteristics such as the sardine (Sardina pilchardus), the horse mackerel (Trachurus trachurus) and the Atlantic chub mackerel (Scomber colias),...
The Local Whittle estimator is one of the most popular techniques for estimating the memory parameter in long memory series due to its simple implementation and nice asymptotic properties under mild conditions. However, its empirical performance depends heavily on the bandwidth, that is the band of frequencies used in the estimation. Different choi...
Estimating the in-sample volatility is one of the main difficulties that face Stochastic Volatility models when applied to financial time series. A non-parametric strategy based on Singular Spectrum Analysis is proposed to solve this problem. Its main advantage is its generality as it does not impose any parametric restriction on the volatility com...
This paper analyses the activity of the Basque fleet during the mackerel fishing season and presents an economic analysis of the equilibrium of this fishery. It seeks to determine whether its economic structure represents an internal factor explaining the fishermen’s behaviour. The inverse demand function and the average cost function are therefore...
This article analyses the potential links between regional first-sale markets for mackerel in Spain using fractional cointegration techniques. The results indicate that this is not an integrated market, and we demonstrate that there are no links, at least in the long term, between any of Spain's five regional markets. This result has significant im...
The asymptotic properties of the Local Whittle estimator of the memory parameter have been widely analysed and its consistency and asymptotic distribution have been obtained for values of in a wide range of situations. However, the asymptotic distribution may be a poor approximation of the exact one in several cases, e.g. with small sample sizes or...
Long memory in stochastic volatility (LMSV) models are flexible tools for the modeling of persistent dynamic volatility, which is a typical characteristic of financial time series. However, their empirical applicability is limited because of the complications inherent in the estimation of the model and in the extraction of the volatility component....
This paper explores seasonal and long-memory time series properties by using the fractional ARIMA model when the data have one and two seasonal periods and short-memory components. The stationarity and invertibility parameter conditions are established for the model studied. To estimate the seasonal fractional long-memory parameters, a semiparametr...
This article analyses the potential links between regional first-sale markets for mackerel in Spain using fractional cointegration techniques. The results indicate that this is not an integrated market, and we demonstrate that there are no links, at least in the long term, between any of Spain's five regional markets. This result has significant im...
Strong cyclical persistence is a common phenomenon that has been documented not only in the levels but also in the volatility of many time series, specially in astronomical or business cycle data. The class of doubly fractional models is extended to include the possibility of long memory in cyclical (non-zero) frequencies in both levels and volatil...
Time series with cyclical long memory are characterized by a spectral pole at some frequency ω between 0 and π such that the series has a persistent cycle of period 2π/ω, implying a quasi-periodic behaviour that slightly evolves with time. Accurate estimation of ω is needed for a precise determination of the characteristic of the series (e.g. for b...
This study compares eight different alternatives of detection and correction of Easter and pre-Easter effect. These are two calendar effects, which are usually subtracted from the time series analyzed before its decomposition into trend/cycle, seasonality and irregular part. The proposed alternatives differ by the duration of these effects and are...
This paper analyzes weekly prices for mackerel landed by the inshore fleet at the ports of the Basque Country in 1995–2008, using recently proposed econometric techniques applied to the fishing market. The idea is to learn to what extent fishermen can pass on the effects of negative shocks (e.g. fuel price increases) to their ex-vessel prices. This...
This paper explores seasonal and long-memory time series properties by using the seasonal fractional ARIMA model when the seasonal data has one and two seasonal periods and short-memory counterparts. The stationarity and invertibility parameter conditions are established for the model studied. To estimate the memory parameters, the method given in...
The historical series of many economic variables, such as inflation, are characterized by a strong persistent behaviour in
the form of long memory, not only in the long run or at zero frequency but often also at seasonal frequencies. In financial
series, long memory is not apparent in levels but strong persistence in higher order moments such as vo...
This paper proposes an extension of the log periodogram regression in perturbed long memory series that accounts for the added noise, also allowing for correlation between signal and noise, which represents a common situation in many economic and ¯nancial series. Consistency (for d
This paper proposes an extension of the log periodogram regression in perturbed long memory series that accounts for the added noise, also allowing for correlation between signal and noise, which represents a common situation in many economic and financial series. Consistency (for d < 1) and asymptotic normality (for d < 3/4) are shown with the sam...
This paper analyses weekly prices for mackerel landed by the inshore fleet at the ports of the Basque Country in 1995-2008, using new econometric techniques never before applied to the fishing market. The idea is to learn to what extent fishermen can pass on the effects of negative shocks (e.g. fuel price increases) to their ex-vessel prices. This...
The choice of the bandwidth in the local log-periodogram regression is of crucial importance for estimation of the memory parameter of a long memory time series. Different choices may give rise to completely different estimates, which may lead to contradictory conclusions, for example about the stationarity of the series. We propose here a data-dri...
The log periodogram regression is widely used in empirical applications because of its simplicity to estimate the memory parameter, d, its good asymp-totic properties and its robustness to misspecification of the short term behavior of the series. However, the asymptotic distribution is a poor approximation of the (unknown) finite sample distributi...
Log periodogram regression is widely applied in empirical applications to estimate the memory parameter, d, of long memory time series. This estimator is consistent for d<1 and pivotal asymptotically normal for d<3/4. However, the asymptotic distribution is a poor approximation of the (unknown) finite sample distribution if the sample size is small...
The choice of the bandwidth in the local log-periodogram regression is of crucial importance for estimation of the memory parameter of a long memory time series. Different choices may give rise to completely different estimates, which may lead to contradictory conclusions, for example about the stationarity of the series. We propose here a data dri...
This paper describes semiparametric techniques recently proposed for the analysis of seasonal or cyclical long memory and applies them to a monthly Spanish inflation series. One of the conclusions is that this series has long memory not only at the origin but also at some but not all seasonal frequencies, suggesting that the fractional difference o...
The estimation of the memory parameter in perturbed long memory (LM) series has recently attracted attention. This has been mainly motivated by the adequacy of LM signal plus noise processes to model the behaviour of many financial and economic time series. In this context frequency domain semiparametric techniques are natural choices for the estim...
This paper considers semi-parametric frequency domain inference for seasonal or cyclical time series with asymmetric long memory properties. It is shown that tapering the data reduces the bias caused by the asymmetry of the spectral density at the cyclical frequency. We provide a joint treatment of different tapering schemes and of the log-periodog...
Semiparametric estimation of the memory parameter in economic time series raises the problem of the small sample size and the poor approximation of the asymptotic distribution to the finite sample counterpart. This paper considers the bootstrap to improve the finite sample distribution of the popular log peridogram regression and shows that it can...
This paper considers the persistence found in the volatility of many financial time series by means of a local Long Memory in Stochastic Volatility model and analyzes the performance of the Gaussian semiparametric or local Whittle estimator of the memory parameter in a long memory signal plus noise model which includes the Long Memory in Stochastic...
The concept of SCLM (seasonal or cyclical long memory) implies the existence of one or more spectral poles or zeros. The processes traditionally used to model such a behaviour assume the same persistence across different frequencies. In this paper, we propose semiparametric Wald and Lagrange multiplier (LM) tests of the equality of memory parameter...
This paper considers the persistence found in the volatility of many financial time series by means of a local Long Memory in Stochastic Volatility model and analyzes the performance of the Gaussian semiparametric or local Whittle estimator of the memory parameter in a long memory signal plus noise model which includes the Long Memory in Stochastic...
Several semiparametric estimates of the memory parameter in standard long memory time series are now available. They consider only local behaviour of the spectrum near zero frequency, about which the spectrum is symmetric. However long-range dependence can appear as a spectral pole at any Nyqvist frequency (reflecting seasonal or cyclical long-memo...
The long memory property of a time series has long been studied and several estimates of the memory or persistence parameter at zero frequency, where the spectral density function is symmetric, are now available. Perhaps the most popular is the log periodogram regression introduced by J. Geweke and S. Porter-Hudak [J. Time Ser. Anal. 4, 221–238 (19...
Several semiparametric estimates of the memory parameter in standard long memory time series are now available. They consider only local behaviour of the spectrum near zero frequency, about which the spectrum is symmetric. However, long-range dependence can appear as a spectral pole at any Nyqvist frequency (reflecting seasonal or cyclical long mem...
This paper contributes empirically to our understanding of informed traders. It analyzes traders' characteristics in a foreign exchange electronic limit order market via anonymous trader identities. We use six indicators of informed trading in a cross-sectional multivariate approach to identify traders with high price impact. More information is co...
The long memory property of a time series has long been studied and several estimates of the memory or persistence parameter at zero frequency where the spectral density function is symmetric are now available. Perhaps the most popular is the log periodogram regression introduced by Geweke and Porter-Hudak (1983). In this paper we analyse the asymp...
Gaussian semiparametric or local Whittle estimation of the memory parameter in standard long memory processes was proposed by Robinson (1995b). This technique shows several advantages over the popular log-periodogram regression introduced by Geweke and Porter-Hudak (1983). In particular under milder assumptions than those needed in the log periodog...
Calendar effects concern special days such as Christmas and Eastern and usually are associated with economic activity fluctuations. In analysis in which time series are seasonally adjusted it is necessary to detect and correct these calendar effects using suitable procedures. This article compares different methods of processing of these effects us...
Resumen En este trabajo se analizan las posibles interrelaciones entre los mercados regionales de primera venta de verdel en España. Con este objetivo se utiliza una nueva metodología de análisis de cointegración fraccional (Hualde, 2009) basada en la propuesta de Gómez-Biscarri y Hualde (2010) para cointegración entera, que no ha sido aplicada con...
