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Showing papers in "Journal of Econometrics in 2011"


Journal ArticleDOI
TL;DR: In this paper, the authors propose several connectedness measures built from pieces of variance decomposition positions, and argue that they provide natural and insightful measures of connectedness among nancial asset returns and volatilities.

1,912 citations


Journal ArticleDOI
TL;DR: In this article, the authors derive necessary and sufficient conditions on the functional form of the loss function for the ranking of competing volatility forecasts to be robust to the presence of noise in the volatility proxy, and derive some useful special cases of this class of robust loss functions.

892 citations


Journal ArticleDOI
TL;DR: In this article, the authors examined the important case where the unobserved common factors follow unit root processes and could be cointegrated and found that the presence of unit roots does not affect most theoretical results which continue to hold irrespective of the integration and the cointegration properties of the unob-served factors.

801 citations


Journal ArticleDOI
TL;DR: In this paper, the authors consider the statistical analysis of large panel data sets where even after condi- tioning on common observed eects the cross section units might remain dependently distrib- uted.

618 citations


Journal ArticleDOI
TL;DR: In this paper, the authors show consistency of a two-step estimation of the factors in a dynamic approximate factor model when the panel of time series is large (n large), in the first step, the parameters of the model are estimated from an OLS on principal components.

457 citations


Journal ArticleDOI
TL;DR: In this article, a multivariate realised kernel is proposed to estimate the ex-post covariation of log-prices, which is guaranteed to be positive semi-definite and robust to measurement noise of certain types.

441 citations


Journal ArticleDOI
TL;DR: In this article, the authors consider the properties of weighted linear combinations of n prediction models, or linear pools, evaluated using the conventional log predictive scoring rule, and derive several interesting formal results: for example, a prediction model with positive weight in a pool may have zero weight if some other models are deleted from that pool.

382 citations


Journal ArticleDOI
TL;DR: In this paper, a quantile regression dynamic panel model with fixed effects is proposed to reduce the dynamic bias of fixed effects estimators in the presence of lagged dependent variables as regressors.

299 citations


Journal ArticleDOI
TL;DR: In this paper, the impact of time series dependence in market microstructure noise on the properties of estimators of the integrated volatility of an asset price based on data sampled at frequencies high enough for that noise to be a dominant consideration is analyzed.

284 citations


Journal ArticleDOI
TL;DR: In this article, the authors extend the analytical results for reduced form realized volatility based forecasting in Andersen, Bollerslev and Meddahi (2004) to allow for market microstructure frictions and deviations from the basic semi-martingale assumption in the observed high-frequency returns underlying the realized measures.

258 citations


Journal ArticleDOI
TL;DR: In this article, a new heteroscedastic model called Contextual Utility (CUI) is proposed to explain and predict risk aversion in the context of discrete choice under risk, which explains as well as or better than other stochastic models.

Journal ArticleDOI
TL;DR: In this paper, the authors introduce a novel approach for dealing with the "curse of dimensionality" in the case of large linear dynamic systems, where restrictions on the coe¢ cients of an unrestricted VAR are proposed that are binding only in a limit as the number of endogenous variables tends to in…nity.

Journal ArticleDOI
TL;DR: In this paper, a cluster covariance matrix estimator (CCE) is used to construct the t and Wald statistics for dependent data in time series, spatial, and panel data applications.

Journal ArticleDOI
TL;DR: In this article, a nonparametric test for nonlinear causality up to the K th conditional moment was proposed, where the conditional mean of a series is not the only variable, but also the dependence between series may be nonlinear, and/or not only through conditional mean.

Journal ArticleDOI
TL;DR: In this article, the forecasting of future realized volatility in the foreign exchange, stock, and bond markets from variables in our information set, including implied volatility backed out from option prices, is studied.

Journal ArticleDOI
TL;DR: In this article, the Epps effect and the effect of microstructure noise are analyzed and a two-scale covariance estimator is provided which simultaneously cancels (to first order) the Eppes effect and other sources of stochastic error terms, including nonsynchronous trading, non-synchronized trading, and time discretization.

Journal ArticleDOI
TL;DR: In this paper, the authors investigate the consequences of structural breaks in the factor loadings for the specification and estimation of factor models based on principal components and suggest procedures for testing for structural breaks.

Journal ArticleDOI
TL;DR: In this paper, the authors propose a model of dynamic correlations with a short and long-run component specification, by extending the idea of component models for volatility, called this class of models DCC-MIDAS.

Journal ArticleDOI
TL;DR: In this article, the authors examined the impact of time aggregation on price change estimates for 19 supermarket item categories using scanner data and found that time aggregation choices lead to a difference in price change estimate for chained indexes which ranged from 0.28% to 29.73% for a superlative index and an incredible 14.88% to 46,463.71% for non-superlative indexes.

Journal ArticleDOI
TL;DR: In this paper, a new matrix-logarithm model of the realized covariance matrix of stock returns is presented, which uses latent factors which are functions of lagged volatility, lagged returns and other forecasting variables.

Journal ArticleDOI
TL;DR: The authors decompose the total daily return variability into the continuous sample path variance, the variation arising from discontinuous jumps that occur during the trading day, as well as the overnight return variance, and discuss how the resulting reduced form model structure for each of the three components may be used in the construction of out-of-sample forecasts for the total return volatility.

Journal ArticleDOI
TL;DR: This article found evidence of multiple breaks in return prediction models based on the dividend yield or a short interest rate, which can lead to a negative slope in the relationship between the investment horizon and the proportion of wealth that investors allocate to stocks.

Journal ArticleDOI
TL;DR: The authors generalize the standard regression-discontinuity approach to include multiple assignment variables simultaneously and show that fitting this general, flexible regression-deconfiguration model enables them to estimate several treatment effects of interest.

Journal ArticleDOI
TL;DR: In this paper, the relative merits of the two main approaches to estimation and inference, namely, the cross-sectional average and principal component estimators, are compared for factor-augmented regressions.

Journal ArticleDOI
TL;DR: In this article, a simple numerical version of the Deaton and Laroque (1992, 1995, 1996) model is presented to explain the degree of serial correlation observed in the prices of twelve major commodities, including coffee, copper, jute, maize, palm oil, sugar and tin.

Journal ArticleDOI
TL;DR: This article proposed new scoring rules based on conditional and censored likelihood for assessing the predictive accuracy of competing density forecasts over a specific region of interest, such as the left tail in financial risk management.

Journal ArticleDOI
TL;DR: In this paper, the authors propose methods of taking into account all forms of heterogeneity, concentrating particularly on using a Mixture Model to capture the heterogeneity of preference functionals for choice under risk from the choice behaviour of individuals.

Journal ArticleDOI
TL;DR: In this article, the authors examined the effect of variable selection in linear regression modeling, where there is a potentially large amount of possible covariates and economic theory offers insufficient guidance on how to select the appropriate subset.

Journal ArticleDOI
TL;DR: In this article, a state-space model for modeling data revisions is proposed, which allows for more realistic data revision properties and allows the use of standard methods for optimal real-time estimation of trends and cycles.

Journal ArticleDOI
TL;DR: In this paper, a method is introduced for approximating the likelihood for the unknown parameters of a state space model, and the approximation converges to the true likelihood as the simulation size goes to infinity.