A test for constant correlations in a multivariate GARCH model

By Y. Tse. 2000

441 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/5b0a6080fc2e86222d3a5788b5167d9e154791e9

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Citations in the corpus

Exchange return co-movements and volatility spillovers before and after the introduction of euro (2012, result): “In the pre-euro period the value of the Tse (2000) and Engle and Sheppard (2001) tests were 73.88 and 69.23 with p-values of [0.00] and [0.00], respectively, whilst 76.35 and 123.36 with [0.00] and [0.00] p-values, respectively, in the post-euro period.”
Out-of-Sample Predictions of Bond Excess Returns and Forward Rates: An Asset Allocation Perspective (2010, positive): “Then we carried out the LM test of conditional correlation by Tse (2000) on the multivariate GARCH model estimated assuming a constant conditional correlation.”
The intertemporal capital asset pricing model with dynamic conditional correlations (2010, neutral): “…work on time-varying covariances in large dimensions was carried out by Bollerslev (1990) in his constant correlation model, where the volatilities of each asset were allowed to vary through time but the correlations were time invariant (see Tse (2000) and Engle (2009a) for a review of this topic).”
Are Correlations Constant? Empirical and Theoretical Results on Popular Correlation Models in Finance (2017, neutral): “However, when applied to empirical data, most studies fail to detect linear dependence (Bollerslev, 1990; Tang, 1995; Tse, 2000).”
New Weighted Portmanteau Statistics for Time Series Goodness of Fit Testing (2012, methodology): “The statistic can be calculated using the recursive method in Tse ( 2000 ).”
U.S. and Latin American Stock Market Linkages (2011, background): “For asset return volatility, it is observed that large (small) changes in returns in one period tend to be followed by large (small) changes in subsequent periods.”
Modeling multivariate autoregressive conditional heteroskedasticity with the double smooth transition conditional correlation GARCH Model (2009, positive): “Tse (2000) derives a Lagrange multiplier (LM) test where the alternative model imposes ARCH-type dynamics on the conditional correlations.”
Modeling the conditional covariance between stock and bond returns : A multivariate GARCH approach (2004, neutral): “This is in line with Tse (2000), who rejects for various countries that conditional correlations are constant over time.”
A Multivariate Generalized Autoregressive Conditional Heteroscedasticity Model With Time-Varying Correlations (2002, methodology): “LMC is the Lagrange multiplier test statistic for constant correlation due to Tse (2000).”
Fitting Vast Dimensional Time-Varying Covariance Models (2020, background): “by, for example, Tse (2000) and Tsui and Yu (1999).”
Multivariate Autoregressive Conditional Heteroskedasticity with Smooth Transitions in Conditional Correlations (2005, methodology): “Tse (2000), Bera and Kim (2002), and Engle and Sheppard (2001) already proposed tests for this purpose.”
Simple Tests for Models of Dependence between Multiple Financial Time Series, with Applications to U.S. Equity Returns and Exchange Rates (2004, background): “Some authors, see Tse (2000) and Engle (2002) amongst others, have reported that the conditional correlation between equity returns is not constant, and so analyzing the unconditional copula of asset returns or standardized asset returns is of less interest than analyzing the conditional copula.”
Comovement in International Equity Markets: A Sectoral View (2005, methodology): “Following Tse (2000), we assume that within a neighborhood of = 0, the optimal properties of the LM test hold under some regularity conditions as provided by, among others, Godfrey (1988). If we plug the above Taylor approximation into the TVC-GARCH model, we obtain after some algebraic manipulation”