nep-ets New Economics Papers
on Econometric Time Series
Issue of 2013‒06‒09
eight papers chosen by
Yong Yin
SUNY at Buffalo

  1. Multifractality and long memory of a financial index By Pablo Su\'arez-Garc\'ia; David G\'omez-Ullate
  2. B-spline techniques for volatility modeling By Sylvain Corlay
  3. Testing for Time-Invariant Unobserved Heterogeneity in Generalized Linear Models for Panel Data By Francesco Bartolucci; Federico Belotti; Franco Peracchi
  4. Trend-cycle decomposition: implications from an exact structural identification By Mardi Dungey; Jan P.A.M. Jacobs; Jing Tian; Simon van Norden
  5. Rejection Probabilities for a Battery of Unit-Root Tests By Maican, Florin G.; Sweeney, Richard J.
  6. Comparison of Methods for Constructing Joint Confidence Bands for Impulse Response Functions By Helmut Lütkepohl; Anna Staszewska-Bystrova; Peter Winker;
  7. Asymptotic theory for the QMLE in GARCH-X models with stationary and non-stationary covariates By Heejoon Han; Dennis Kristensen
  8. Unpredictability in Economic Analysis, Econometric Modeling and Forecasting By David Hendry; Grayham E. Mizon

  1. By: Pablo Su\'arez-Garc\'ia; David G\'omez-Ullate
    Abstract: In this paper we will try to assess the multifractality displayed by the high-frequency returns of Madrid's Stock Exchange IBEX35 index. A Multifractal Detrended Fluctuation Analysis shows that this index has a wide singularity spectrum which is most likely caused by its long memory. Our findings also show that this long-memory can be considered as the superposition of a high-frequency component (related to the daily cycles of arrival of information to the market), over a slowly-varying component that reverberates for long periods of time and which shows no apparent relation with human economic cycles. This later component is therefore postulated to be endogenous to market's dynamics and to be also the most probable source of some of the stylized facts commonly associated with financial time series.
    Date: 2013–06
  2. By: Sylvain Corlay
    Abstract: This paper is devoted to the application of B-splines to volatility modeling, specifically the calibration of the leverage function in stochastic local volatility models and the parameterization of an arbitrage-free implied volatility surface calibrated to sparse option data. We use an extension to the classical B-splines obtained by including basis functions of infinite support. \par We first come back to the application of shape-constrained B-splines to the estimation of conditional expectations, not merely from a scatter plot but also with the given of the marginal distributions. An application is the Monte Carlo calibration of stochastic local volatility models by Markov projection. Then we present a new technique for the calibration of an implied volatility surface to sparse option data. We use a B-spline parameterization of the Radon-Nikodym derivative of the underlying's risk-neutral probability density with respect to a roughly calibrated base model. We show that the method provides smooth arbitrage-free implied volatility surfaces. Eventually, we propose a Galerkin method with B-spline finite elements to the solution of the P.D.E. satisfied by the Radon Nikodym derivative.
    Date: 2013–06
  3. By: Francesco Bartolucci (University of Perugia); Federico Belotti (University of Rome "Tor Vergata"); Franco Peracchi (University of Rome "Tor Vergata" and EIEF)
    Abstract: Recent literature on panel data has emphasized the importance of accounting for time-varying unobserved heterogeneity, which may stem either from time-varying omitted variables or macro-level shocks that affect each individual unit differently. In this paper, we propose a computationally convenient test for the null hypothesis of time-invariant individual effects. The proposed test is an application of Hausman (1978) specification test procedure and can be applied to generalized linear models for panel data, a wide class of models that includes the Gaussian linear model and a variety of nonlinear models typically employed for discrete or categorical outcomes. The basic idea is to compare fixed effects estimators defined as the maximand of full and pairwise conditional likelihood functions. Thus, the proposed approach requires no assumptions on the distribution of the individual effects and, most importantly, it does not require them to be independent of the covariates in the model. We investigate the finite sample properties of the test through a set of Monte Carlo experiments. Our results show that the test performs quite well, with small size distortions and good power properties. A health economics example based on data from the Health and Retirement Study is used to illustrate the proposed test.
    Date: 2013
  4. By: Mardi Dungey; Jan P.A.M. Jacobs; Jing Tian; Simon van Norden
    Abstract: A well-documented property of the Beveridge-Nelson trend-cycle decomposition is the perfect negative correlation between trend and cycle innovations. We show how this may be consistent with a structural model where trend shocks enter the cycle, or cyclic shocks enter the trend and that identification restrictions are necessary to make this structural distinction. A reduced-form unrestricted version such as that of Morley, Nelson and Zivot (2003) is compatible with either option, but cannot distinguish which is relevant. We discuss economic interpretations and implications using US real GDP data.
    Date: 2013
  5. By: Maican, Florin G. (Department of Economics, School of Business, Economics and Law, Göteborg University); Sweeney, Richard J. (Georgetown University, Washington, D.C.)
    Abstract: If the researcher tests each model in a battery at the a % significance level, the probability that at least one test rejects is generally larger than a %. For five unit-root models, this paper uses Monte Carlo simulation and the inclusion-exclusion principle to show for a %=5% for each test, the probability that at least one test rejects is 16.2% rather than the upper-bound of 25% from the Bonferroni inequality. It also gives estimated probabilities that any combination two, three, four or five models all reject.<p>
    Keywords: Real Exchange Rates; Unit root; Monte Carlo; Break models
    JEL: C15 C22 C32 C33 E31 F31
    Date: 2013–06–03
  6. By: Helmut Lütkepohl; Anna Staszewska-Bystrova; Peter Winker;
    Abstract: In vector autoregressive analysis confidence intervals for individual impulse responses are typically reported to indicate the sampling uncertainty in the estimation results. A range of methods are reviewed and a new proposal is made for constructing joint confidence bands, given a prespecifed coverage level, for the impulse responses at all horizons considered simultaneously. The methods are compared in a simulation experiment and recommendations for empirical work are provided.
    Keywords: Vector autoregressive process, impulse responses, bootstrap, confidence band
    JEL: C32
    Date: 2013–06
  7. By: Heejoon Han; Dennis Kristensen (Institute for Fiscal Studies and University College London)
    Abstract: This paper investigates the asymptotic properties of the Gaussian quasi-maximum-likelihood estimators (QMLE's) of the GARCH model augmented by including an additional explanatory variable- the so-called GARCH-X model. The additional covariate is allowed to exhibit any degree of persistence as captured by its long-memory parameter dx; in particular, we allow for both stationary and non-stationary covariates. We show that the QMLE's of the parameters entereing the volatility equation are consistent and mixed-normally distributed in large samples. The convergence rates and limiting distributions of the QMLE's depend on whether the regressor is stationary or not. However, standard inferential tools for the parameters are robust to the level of persistence of the regressor with t-statistics following standard Normal distributions in large sample irrespective of whether the regressor is stationary or not.
    Date: 2013–05
  8. By: David Hendry; Grayham E. Mizon
    Abstract: Unpredictability arises from intrinsic stochastic variation, unexpected instances of outliers, and unanticipated extrinsic shifts of distributions.  We analyze their properties, relationships, and different effects on the three arenas in the title, which suggests considering three associated information sets.  The implications of unanticipated shifts for forecasting, economic analyses of efficient markets, conditional expectations, and inter-temporal derivations are described.  The potential success of general-to-specific model selection in tackling location shifts by impulse-indicator saturation is contrasted with the major difficulties confronting forecasting.
    Keywords: Unpredictability, 'Black Swans', distributional shifts, forecast failure, model selection, conditional expectations
    JEL: C51 C22
    Date: 2013–03–14

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