- Via San Felice, 5
27100 Pavia
Italy
Eduardo Rossi
University of Pavia, Economics and Management, Faculty Member
- University of Pavia, Economia Politica E Metodi Quantitativi, Faculty Memberadd
- Financial Econometrics, Time series Econometrics, Financial Economics, Financial Derivatives, Asset and investment valuation, Finance, and 13 moreBanking, Forecasting, Time series analysis, Time Series, Asset Pricing, Time-Series Analysis, Bayesian Models, Vector Autoregression, Impulse response, ARCH models, Nonlinear state-space models, Fractional Cointegration, and Economicsedit
ABSTRACT Castagnetti et al. (2015) propose two max-type statistics to test for the presence of a factor structure in a large stationary panel data model. In this contribution, we study the use of Hausman-type statistics based on the CCE... more
ABSTRACT Castagnetti et al. (2015) propose two max-type statistics to test for the presence of a factor structure in a large stationary panel data model. In this contribution, we study the use of Hausman-type statistics based on the CCE estimator of Pesaran (2006) and the IE estimator developed by Bai (2009; see also Song, 2013). We show that tests based on either estimator cannot be employed directly, and either need further assumptions than those required for the simple purpose of estimation, or bias corrections, or cannot be used altogether.
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ABSTRACT This paper develops an estimation and testing framework for a stationary large panel model with observable regressors and unobservable common factors. We allow for slope heterogeneity and for correlation between the common... more
ABSTRACT This paper develops an estimation and testing framework for a stationary large panel model with observable regressors and unobservable common factors. We allow for slope heterogeneity and for correlation between the common factors and the regressors. We propose a two stage estimation procedure for the unobservable common factors and their loadings, based on Common Correlated Effects estimator and the Principal Component estimator. We also develop two tests for the null of no factor structure: one for the null that loadings are cross sectionally homogeneous, and one for the null that common factors are homogeneous over time. Our tests are based on using extremes of the estimated loadings and common factors. The test statistics have an asymptotic Gumbel distribution under the null, and have power versus alternatives where only one loading or common factor differs from the others. Monte Carlo evidence shows that the tests have the correct size and good power.
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Research Interests: Approximation Theory, Stochastic Process, Econometrics, Statistics, Data Analysis, and 17 morePrediction, Numerical Analysis, Random Walk, Maximum Likelihood, Sample Survey, Approximation, DSGE Model, Stochastic differential equation, Density Estimation, Importance Sampling, Differential equation, Integral Equation, Probability Density Function, Monte Carlo Method, Computational Statistics and Data Analysis, maximum likelihood estimate, and Posterior distribution
The paper presents some recent results on multivariate GARCH models, and proposes a parametrization which guarantees a positive definite conditional variance-covariance matrix of the disturbances. The properties of quasi-maximum... more
The paper presents some recent results on multivariate GARCH models, and proposes a parametrization which guarantees a positive definite conditional variance-covariance matrix of the disturbances. The properties of quasi-maximum likelihood estimators are showed. The ...
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Research Interests:
Research Interests: Finance, Approximation Theory, Stochastic Process, Econometrics, Statistics, and 12 moreData Analysis, Monte Carlo Simulation, Numerical Analysis, Multivariate Analysis, Probability Distribution & Applications, Density Estimation, Parameterization, Tagucghi Loss Function, Multivariate Normal Distribution, Monte Carlo Method, Covariance, and Computational Statistics and Data Analysis
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This paper deals with the estimation of optimal hedge ratios. Three alternative hedging strategies are considered: duration matching, least squares hedge estimator and asymmetric multivariate GARCH. Hedging performance comparisons, in... more
This paper deals with the estimation of optimal hedge ratios. Three alternative hedging strategies are considered: duration matching, least squares hedge estimator and asymmetric multivariate GARCH. Hedging performance comparisons, in terms of ex-post ...