nep-ets New Economics Papers
on Econometric Time Series
Issue of 2006‒09‒16
twelve papers chosen by
Yong Yin
SUNY at Buffalo

  1. Assessing and Valuing the Non-Linear Structure of Hedge Fund Returns By Antonio Diez de los Rios; René Garcia
  2. On the Practice of Bayesian Inference in Basic Economic Time Series Models using Gibbs Sampling By Michiel D. de Pooter; René Segers; Herman K. van Dijk
  3. A General Representation Theorem for Integrated Vector Autoregressive Processes By Massimo Franchi
  4. Random Correlation Matrix and De-Noising By Ken-ichi Mitsui; Yoshio Tabata
  5. Nonlinear Time Series Analysis By Bruce Mizrach
  6. Subsampling realised kernels By Ole E. Barndorff-Nielsen; Peter R. Hansen; Asger Lunde; Neil Shephard
  7. Fast estimation methods for time series models in state-space form. By Alfredo Gª Hiernaux; Miguel Jerez; José Casals
  8. Periodically Collapsing Rational Bubbles in Exchange Rates: A Markov-Switching Analysis for a Sample of Industrialised Markets By Jose Eduardo de A. Ferreira
  9. Testing for stationarity in heterogeneous panel data in the presence of cross section dependence By Giulietti, Monica; Otero, Jesus; Smith, Jeremy
  10. Trend Cycle Correlation, Drift Break and the Estimation of Trend and Cycle in Canadian GDP By Arabinda Basistha
  11. Nonlinear Bivariate Comovements of Asset Prices: Theory and Tests By Marco Corazza; A.G. Malliaris; Elisa Scalco
  12. The Decline in German Output Volatility: A Bayesian Analysis By Aßmann, Christian; Hogrefe, Jens; Liesenfeld, Roman

  1. By: Antonio Diez de los Rios; René Garcia
    Abstract: Several studies have put forward the non-linear structure and option-like features of returns associated with hedge fund strategies. The authors provide a statistical methodology to test for such non-linear features with the returns on any benchmark portfolio. They estimate the portfolio of options that best approximates the returns of a given hedge fund, account for this search in the statistical testing of the contingent claim features, and test whether the identified non-linear features have a positive value. The authors find that not all categories of funds exhibit significant non-linearities, and that only a few strategies as a group provide significant value to investors. Individual funds may still provide value in an otherwise poorly performing category.
    Keywords: Econometric and statistical methods; Financial institutions
    JEL: C1 C5 G1
    Date: 2006
    URL: http://d.repec.org/n?u=RePEc:bca:bocawp:06-31&r=ets
  2. By: Michiel D. de Pooter (Faculty of Economics, Erasmus Universiteit Rotterdam); René Segers (Faculty of Economics, Erasmus Universiteit Rotterdam); Herman K. van Dijk (Faculty of Economics, Erasmus Universiteit Rotterdam)
    Abstract: Several lessons learned from a Bayesian analysis of basic economic time series models by means of the Gibbs sampling algorithm are presented. Models include the Cochrane-Orcutt model for serial correlation, the Koyck distributed lag model, the Unit Root model, the Instrumental Variables model and as Hierarchical Linear Mixed Models, the State-Space model and the Panel Data model. We discuss issues involved when drawing Bayesian inference on regression parameters and variance components, in particular when some parameter have substantial posterior probability near the boundary of the parameter region, and show that one should carefully scan the shape of the posterior density function. Analytical, graphical and empirical results are used along the way.
    Keywords: Gibbs sampler; MCMC; serial correlation; non-stationarity; reduced rank models; state-space models; random effects panel data models
    JEL: C11 C15 C22 C23 C30
    Date: 2006–08–31
    URL: http://d.repec.org/n?u=RePEc:dgr:uvatin:20060076&r=ets
  3. By: Massimo Franchi (Department of Economics, University of Copenhagen)
    Abstract: We study the algebraic structure of an I(d) vector autoregressive process, where d is restricted to be an integer. This is useful to characterize its polynomial cointegrating relations and its moving average representation, that is to prove a version of the Granger representation theorem valid for I(d) vector autoregressive processes.
    Keywords: vector autoregressive processes; unit roots; Granger representation theorem; cointegration
    JEL: C32
    Date: 2006–08
    URL: http://d.repec.org/n?u=RePEc:kud:kuiedp:0616&r=ets
  4. By: Ken-ichi Mitsui (Doctor Candidate of Osaka University); Yoshio Tabata (Graduate School of Business Administration, Nanzan Univeristy)
    Abstract: In Finance, the modeling of a correlation matrix is one of the important problems. In particular, the correlation matrix obtained from market data has the noise. Here we apply the de-noising processing based on the wavelet analysis to the noisy correlation matrix, which is generated by a parametric function with random parameters. First of all, we show that two properties, i.e. symmetry and ones of all diagonal elements, of the correlation matrix preserve via the de-noising processing and the efficiency of the de-nosing processing by numerical experiments. We propose that the de-noising processing is one of the effective methods in order to reduce the noise in the noisy correlation matrix.
    Keywords: correlation matrix, calibration, rank reduction, de-noising, wavelet analysis
    JEL: C51 C61 C63 G32
    Date: 2006–09
    URL: http://d.repec.org/n?u=RePEc:osk:wpaper:0626&r=ets
  5. By: Bruce Mizrach (Rutgers University)
    Abstract: This entry for the New Palgrave covers developments in nonlinear time series analysis over the last 25 years.
    Keywords: nonlinear, time series, analysis
    JEL: C22 C14 C45
    Date: 2006–02–25
    URL: http://d.repec.org/n?u=RePEc:rut:rutres:200604&r=ets
  6. By: Ole E. Barndorff-Nielsen; Peter R. Hansen; Asger Lunde; Neil Shephard
    Abstract: In a recent paper we have introduced the class of realised kernel estimators of the increments of quadratic variation in the presence of noise. We showed that this estimator is consistent and derived its limit distribution under various assumptions on the kernel weights. In this paper we extend our analysis, looking at the class of subsampled realised kernels and we derive the limit theory for this class of estimators. We find that subsampling is highly advantageous for estimators based on discontinuous kernels, such as the truncated kernel. For kinked kernels, such as the Bartlett kernel, we show that subsampling is impotent, in the sense that subsampling has no effect on the asymptotic distribution. Perhaps surprisingly, for the efficient smooth kernels, such as the Parzen kernel, we show that subsampling is harmful as it increases the asymptotic variance. We also study the performance of subsampled realised kernels in simulations and in empirical work.
    Keywords: Bipower variation; Long run variance estimator; Market frictions; Quadratic variation; Realised kernel; Realised variance; Subsampling.
    JEL: C13 C22
    Date: 2006
    URL: http://d.repec.org/n?u=RePEc:sbs:wpsefe:2006fe06&r=ets
  7. By: Alfredo Gª Hiernaux (Universidad Complutense de Madrid. Facultad de CC. Económicas y Empresariales. Dpto. Fundamentos del An´alisis Económico II.); Miguel Jerez (Universidad Complutense de Madrid. Facultad de CC. Económicas y Empresariales. Dpto. Fundamentos del An´alisis Económico II.); José Casals (Universidad Complutense de Madrid. Facultad de CC. Económicas y Empresariales. Dpto. Fundamentos del An´alisis Económico II)
    Abstract: We propose two fast, stable and consistent methods to estimate time series models expressed in their equivalent state-space form. They are useful both, to obtain adequate initial conditions for a maximum-likelihood iteration, or to provide final estimates when maximum-likelihood is considered inadequate or costly. The state-space foundation of these procedures implies that they can estimate any linear fixed-coefficients model, such as ARIMA, VARMAX or structural time series models. The computational and finitesample performance of both methods is very good, as a simulation exercise shows.
    Date: 2005
    URL: http://d.repec.org/n?u=RePEc:ucm:doicae:0504&r=ets
  8. By: Jose Eduardo de A. Ferreira
    Abstract: This paper investigates the presence of periodically collapsing rational bubbles in exchange rates for a sample of industrialised countries. A periodically collapsing rational bubble is defined as an explosive deviation from economic fundamentals with distinct expansion and contraction phases in finite time. By using Markov-switching regime models we were not able to find robust evidence of a bubble driving the exchange rate away from fundamentals. Moreover, the results also revealed significant non-linearities and different regimes. The importance of these findings suggests that linear monetary models may not be appropriate to examine exchange rate movements.
    Keywords: Foreign Exchange; Bubbles; Fundamentals; Markov-Switching; Assets
    JEL: F31 F37 F41
    Date: 2006–09
    URL: http://d.repec.org/n?u=RePEc:ukc:ukcedp:0604&r=ets
  9. By: Giulietti, Monica (Aston Business School, University of Aston); Otero, Jesus (Facultad de Economia, Columbia); Smith, Jeremy (Department of Economics, University of Warwick)
    Abstract: The panel variant of the KPSS tests developed by Hadri (2000) for the null of stationarity suffers from size distortions in the presence of cross section dependence. However, applying the bootstrap methodology we find that these tests are approximately correctly sized.
    Keywords: Heterogeneous dynamic panels ; Monte Carlo ; bootstrap ; unit root tests ; cross section dependence.
    JEL: C12 C15 C22 C23
    Date: 2006
    URL: http://d.repec.org/n?u=RePEc:wrk:warwec:758&r=ets
  10. By: Arabinda Basistha (Department of Economics, West Virginia University)
    Abstract: This paper argues, using Monte Carlo experiments, that bivariate correlated unobserved components (UC) framework delivers more accurate estimation results for trend and cycle parameters than the univariate framework.The paper estimates stochastic trend and cyclical fluctuations in Canada from a bivariate, correlated UC model with drift breaks. In contrast to the univariate results, bivariate estimation shows a fairly volatile stochastic trend after accounting for the drift break along with a negative trend-cycle shock correlation. The estimated cyclical component is moderately large, persistent and consistent with ECRI denoted Canadian recessions.
    Keywords: Stochastic trend, Inflation, GDP, Unobserved components model
    JEL: E31 E32 E50
    Date: 2005
    URL: http://d.repec.org/n?u=RePEc:wvu:wpaper:05-07&r=ets
  11. By: Marco Corazza (Department of Applied Mathematics, University of Venice); A.G. Malliaris (Department of Economics, Loyola University of Chicago); Elisa Scalco (Department of Applied Mathematics, University of Venice)
    Abstract: Comovements among asset prices have received a lot of attention for several reasons. For example, comovements are important in cross-hedging and cross-speculation; they determine capital allocation both domestically and in international meanÐvariance portfolios and also, they are useful in investigating the extent of integration among financial markets. In this paper we propose a new methodology for the nonÐlinear modelling of bivariate comovements. Our approach extends the ones presented in the recent literature. In fact, our methodology outlined in three steps, allows the evaluation and the statistical testing of non-linearly driven comovements between two given random variables. Moreover, when such a bivariate dependence relationship is detected, our approach solves for a polynomial approximation. We illustrate our threeÐsteps methodology to the time series of energy related asset prices. Finally, we exploit this dependence relationship and its polynomial approximation to obtain analytical approximations of the Greeks for the European call and put options in terms of an asset whose price comoves with the price of the underlying asset.
    Keywords: Comovement, asset prices, bivariate dependence, non-linearity, t-test, polynomial approximation, energy asset, (vanilla) European call and put options, crossÐGreeks.
    JEL: C59 G19 Q49
    Date: 2006–09
    URL: http://d.repec.org/n?u=RePEc:vnm:wpaper:137&r=ets
  12. By: Aßmann, Christian; Hogrefe, Jens; Liesenfeld, Roman
    Abstract: Empirical evidence suggests a sharp volatility decline of the growth in U.S. gross domestic product (GDP) in the mid-1980s. Using Bayesian methods, we analyze whether a volatility reduction can also be detected for the German GDP. Since statistical inference for volatility processes critically depends on the specification of the conditional mean we assume for our volatility analysis different time series models for GDP growth. We find across all specifications evidence for an output stabilization around 1993, after the downturn following the boom associated with the German reunification. However, the different GDP models lead to alternative characterizations of this stabilization : In a linear AR model it shows up as smaller shocks hitting the economy, while regime switching models reveal as further sources for a stabilization, a narrowing gap between growth rates during booms and recessions or flatter trajectories characterizing the GDP growth rates. Furthermore, it appears that the reunification interrupted an output stabilization emerging already around 1987.
    Keywords: business cycle models, Gibbs sampling, Markov Chain Monte Carlo, regime switching, structural breaks
    JEL: C11 C15 C32 E32
    Date: 2005
    URL: http://d.repec.org/n?u=RePEc:zbw:cauewp:4134&r=ets

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