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on Econometric Time Series |
| By: | Trenkler, Carsten; Weber, Enzo |
| Abstract: | We introduce the idea of common serial correlation features among non-stationary, cointegrated variables. That is, the time series do not only trend together in the long run, but adjustment restores equilibrium immediately in the period following a deviation. Allowing for delayed re-equilibration, we extend the framework to codependence. The restrictions derived for VECMs exhibiting the common feature are checked by LR and GMM-type tests. Alongside, we provide corrected maximum codependence orders and discuss identification. The concept is applied to US and European interest rate data, examining the capability of the Fed and ECB to control overnight money market rates. |
| Keywords: | VAR; serial correlation common features; codependence; cointegration |
| JEL: | C32 E52 |
| Date: | 2009–10–21 |
| URL: | http://d.repec.org/n?u=RePEc:bay:rdwiwi:9852&r=ets |
| By: | Weber, Enzo |
| Abstract: | This paper disentangles direct spillovers and common factors as sources of correlations in simultaneous heteroscedastic systems. While these different components are not identifiable by standard means without restrictions, it is shown that they can be pinned down by specifying the variances of the latent idiosyncratic and common shocks as ARCH-type processes. Applying an adapted Kalman filter estimation method to Dow and Nasdaq stock returns, predominant spillovers from the Dow and substantial rising factor exposure are found. While the latter is shown to prevail in the recent global financial crisis, volatility in the dot-com bubble period was driven by Nasdaq shocks. |
| Keywords: | Simultaneous System; Latent Factor; Identification; Spillover; EGARCH |
| Date: | 2010–03–16 |
| URL: | http://d.repec.org/n?u=RePEc:bay:rdwiwi:13581&r=ets |
| By: | Weber, Enzo |
| Abstract: | This paper proposes a new approach to modelling financial transmission effects. In simultaneous systems of stock returns, fundamental shocks are identified through heteroscedasticity. The size of contemporaneous spillovers is determined in the fashion of smooth transition regression by the innovations' variances and (negative) signs, both representing typical crisis-related magnitudes. Thereby, contagion describes higher inward transmission in times of foreign crisis, whereas vulnerability is defined as increased susceptibility to foreign shocks in times of domestic turmoil. The application to major American stock indices confirms US dominance and demonstrates that volatility and sign of the equity returns significantly govern spillover size. |
| Keywords: | Contagion; Vulnerability; Identification; Smooth Transition Regression |
| JEL: | C32 G15 |
| Date: | 2009–07–10 |
| URL: | http://d.repec.org/n?u=RePEc:bay:rdwiwi:8573&r=ets |
| By: | Vitali Alexeev (School of Economics and Finance, University of Tasmania, Australia); Alex Maynard (Department of Economics, University of Guelph, Canada.) |
| Abstract: | We propose a modified version of the nonparametric level crossing random walk test, in which the crossing level is determined locally. This modification results in a test that is robust to unknown multiple structural breaks in the level and slope of the trend function under both the null and alternative hypothesis. No knowledge regarding the number or timing of the breaks is required. An algorithm is proposed to select the degree of localization in order to maximize bootstrapped power in a proximate model. A computational procedure is then developed to adjust the critical values for the effect of this selection procedure by replicating it under the null hypothesis. The test is applied to Canadian nominal inflation and nominal interest rate series with implications for the Fisher hypothesis. |
| Keywords: | Level crossing; random walk; structural breaks; unit root; robustness |
| JEL: | C12 C14 C22 |
| Date: | 2010 |
| URL: | http://d.repec.org/n?u=RePEc:gue:guelph:2010-01.&r=ets |
| By: | Xin Jin; John M Maheu |
| Abstract: | This paper proposes new dynamic component models of realized covariance (RCOV) matrices based on recent work in time-varying Wishart distributions. The specifications are linked to returns for a joint multivariate model of returns and covariance dynamics that is both easy to estimate and forecast. Realized covariance matrices are constructed for 5 stocks using high-frequency intraday prices based on positive semi-definite realized kernel estimates. The models are compared based on a term-structure of density forecasts of returns for multiple forecast horizons. Relative to multivariate GARCH models that use only daily returns, the joint RCOV and return models provide significant improvements in density forecasts from forecast horizons of 1 day to 3 months ahead. Global minimum variance portfolio selection is improved for forecast horizons up to 3 weeks out. |
| Keywords: | eigenvalues, dynamic conditional correlation, predictive likelihoods, MCMC |
| JEL: | C11 C32 C53 |
| Date: | 2010–07–16 |
| URL: | http://d.repec.org/n?u=RePEc:tor:tecipa:tecipa-408&r=ets |
| By: | Xiaohong Chen (Cowles Foundation, Yale University); Lars P. Hansen (Dept. of Economics and Statistics, University of Chicago); Marine Carrasco (Dept. of Economics, University of Montreal) |
| Abstract: | Nonlinearities in the drift and diffusion coefficients influence temporal dependence in diffusion models. We study this link using three measures of temporal dependence: rho-mixing, beta-mixing and alpha-mixing. Stationary diffusions that are rho-mixing have mixing coefficients that decay exponentially to zero. When they fail to be rho-mixing, they are still beta-mixing and alpha-mixing; but coefficient decay is slower than exponential. For such processes we find transformations of the Markov states that have finite variances but infinite spectral densities at frequency zero. The resulting spectral densities behave like those of stochastic processes with long memory. Finally we show how state-dependent, Poisson sampling alters the temporal dependence. |
| Keywords: | Diffusion, Strong dependence, Long memory, Poisson sampling, Quadratic forms |
| JEL: | C12 C13 C22 C50 |
| Date: | 2009–10 |
| URL: | http://d.repec.org/n?u=RePEc:cwl:cwldpp:1652r&r=ets |
| By: | R. Vilela Mendes; Maria Jo\~ao Oliveira |
| Abstract: | Based on a criterium of mathematical simplicity and consistency with empirical market data, a stochastic volatility model has been obtained with the volatility process driven by fractional noise. Depending on whether the stochasticity generators of log-price and volatility are independent or are the same, two versions of the model are obtained with different leverage behavior. Here, the no-arbitrage and incompleteness properties of the model are studied. Some risk measures are also discussed in this framework. |
| Date: | 2010–07 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1007.2817&r=ets |