|
on Econometric Time Series |
| By: | Keiko Yamaguchi |
| Abstract: | In this paper, we propose a new test for the presence of noise in the long-memory signal plus white noise model. A similar test was proposed by Sun-Phillips(2003), so we conduct simulation experiments to examine and compare the finite sample properties of these two tests. It is well-known that the realized volatility(RV) follows a long memory process, so we apply these tests to the RVs calculated using the 1- and 5-minutes returns of the Nikkei 225 stock index. |
| Keywords: | long-term memory, realized volatility, observation error, semi-parametric, local Whittle model |
| JEL: | C22 |
| Date: | 2008–01 |
| URL: | http://d.repec.org/n?u=RePEc:hst:hstdps:d07-230&r=ets |
| By: | M. Hashem Pesaran (CIMF, University of Cambridge, USC and IZA); L. Vanessa Smith (CFAP, University of Cambridge); Takashi Yamagata (University of York) |
| Abstract: | This paper extends the cross sectionally augmented panel unit root test proposed by Pesaran (2007) to the case of a multifactor error structure. The basic idea is to exploit information regarding the unobserved factors that are shared by other time series in addition to the variable under consideration. Importantly, our test procedure only requires specification of the maximum number of factors, in contrast to other panel unit root tests based on principal components that require in addition the estimation of the number of factors as well as the factors themselves. Small sample properties of the proposed test are investigated by Monte Carlo experiments, which suggest that it controls well for size in almost all cases, especially in the presence of serial correlation in the error term, contrary to alternative test statistics. Empirical applications to Fisher’s inflation parity and real equity prices across different markets illustrate how the proposed test works in practice. |
| Keywords: | panel unit root tests, cross section dependence, multi-factor residual structure, Fisher inflation parity, real equity prices |
| JEL: | C12 C15 C22 C23 |
| Date: | 2007–12 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp3254&r=ets |
| By: | Valle e Azevedo, João |
| Abstract: | We derive the limit of the expected periodogram in the unit-root case under general conditions. This function is seen to be time-independent, thus sharing a fundamental property with the stationary case equivalent. We discuss the consequences of this result to the frequency domain interpretation of filtered integrated time series. |
| Keywords: | Periodogram; Unit root |
| JEL: | C22 |
| Date: | 2007–09–21 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:6553&r=ets |
| By: | Valle e Azevedo, João |
| Abstract: | We develop a multivariate filter which is an optimal (in the mean squared error sense) approximation to the ideal filter that isolates a specified range of fluctuations in a time series, e.g., business cycle fluctuations in macroeconomic time series. This requires knowledge of the true second-order moments of the data. Otherwise these can be estimated and we show empirically that the method still leads to relevant improvements of the extracted signal, especially in the endpoints of the sample. Our filter is an extension of the univariate filter developed by Christiano and Fitzgerald (2003). Specifically, we allow an arbitrary number of covariates to be employed in the estimation of the signal. We illustrate the application of the filter by constructing a business cycle indicator for the U.S. economy. The filter can additionally be used in any similar signal extraction problem demanding accurate real-time estimates. |
| JEL: | E32 C14 C22 |
| Date: | 2008–01–02 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:6555&r=ets |
| By: | Valle e Azevedo, João |
| Abstract: | We resort to a rigorous definition of spectrum of an integrated time series in order to characterise the implications of applying linear filters to such series. We conclude that in the presence of integrated series the transfer function of the filters has exactly the same interpretation as in the covariance stationary case, contrary to what many authors suggest. This disagreement leads to different conclusions regarding the link of the original fluctuations with the transformed fluctuations in the time series data, embodied in various unjustified criticisms to the application of detrending filters. Despite this, and given the frequency domain characteristics of filtered macroeconomic integrated series, we acknowledge that the choice of a particular detrending filter is far from being a neutral task. |
| Keywords: | Unit roots; Band-pass filters; Pseudo-spectrum |
| JEL: | E32 C22 |
| Date: | 2007–09–21 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:6574&r=ets |
| By: | Caiado, Jorge; Crato, Nuno; Peña, Daniel |
| Abstract: | The comparison and classification of time series is an important issue in practical time series analysis. For these purposes, various methods have been proposed in the literature, but all have shortcomings, especially when the observed time series have different sample sizes. In this paper, we propose spectral domain methods for handling time series of unequal length. The methods make the spectral estimates comparable, by producing statistics at the same frequency. A first sensible approach may consist on zero-padding the shorter time series in order to increase the corresponding number of periodogram ordinates. We show that this works well provided the sample sizes are not very different, but does not give good results in case the time series lengths are very unbalanced. For this latter case, we study some periodogram-based comparison methods and construct a test. Both the methods and the test display reasonable properties for series of any lengths. Additionally and for reference, we develop a parametric comparison method. The procedures are assessed by a Monte Carlo simulation study. As an illustrative example, a periodogram method is used to compare and cluster industrial production series of some developed countries. |
| Keywords: | Cluster analysis; Interpolated periodogram; Reduced periodogram; Spectral analysis; Time series; Zero-padding. |
| JEL: | C32 C0 C12 |
| Date: | 2007–12 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:6605&r=ets |
| By: | Caiado, Jorge; Crato, Nuno |
| Abstract: | This paper proposes spectral and asymmetric-volatility based methods for cluster analysis of stock returns. Using the information about both the periodogram of the squared returns and the estimated parameters in the TARCH equation, we compute a distance matrix for the stock returns. Clusters are formed by looking to the hierarchical structure tree (or dendrogram) and the computed principal coordinates. We employ these techniques to investigate the similarities and dissimilarities between the "blue-chip" stocks used to compute the Dow Jones Industrial Average (DJIA) index. For reference, we investigate also the similarities among stock returns by mean and squared correlation methods. |
| Keywords: | Asymmetric effects; Cluster analysis; DJIA stock returns; Periodogram; Threshold ARCH model; Volatility |
| JEL: | C32 G10 |
| Date: | 2007–12 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:6607&r=ets |
| By: | Rao, B. Bhaskara; Singh, Rup; Kumar, Saten |
| Abstract: | It is argued that whether or not there is a need for unit roots and cointegration based econometric methods is a methodological issue. An alternative is the econometrics of the London School of Economics (LSE) and Hendry approach based on the simpler classical methods of estimation. This is known as the general to specific method (GETS). Like all other methodological issues this is also difficult to resolve but we think that GETS is very useful. |
| Keywords: | GETS; Cointegration; Box-Jenkin’s Equations; Hendry; Granger |
| JEL: | C0 C1 |
| Date: | 2008–01–09 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:6627&r=ets |
| By: | Stengos, T.; Kourtellos, A.; Tan, C.M. |
| Date: | 2008 |
| URL: | http://d.repec.org/n?u=RePEc:gue:guelph:2008-1&r=ets |