Showing 1 - 10 of 77
This is a simulation-based warning note for practitioners who use the MGLS unit root tests in the context of structural change using different selection lag length criteria. With T=100 , we find severe oversize problems when using some criteria, while other criteria produce an undersizing...
Persistent link: https://www.econbiz.de/10011755373
This paper develops residual-based monitoring procedures for cointegrating polynomial regressions (CPRs), i.e., regression models including deterministic variables and integrated processes, as well as integer powers, of integrated processes as regressors. The regressors are allowed to be...
Persistent link: https://www.econbiz.de/10012696317
One of the most popular univariate asymmetric conditional volatility models is the exponential GARCH (or EGARCH) specification. In addition to asymmetry, which captures the different effects on conditional volatility of positive and negative effects of equal magnitude, EGARCH can also...
Persistent link: https://www.econbiz.de/10010362978
Of the two most widely estimated univariate asymmetric conditional volatility models, the exponential GARCH (or EGARCH) specification can capture asymmetry, which refers to the different effects on conditional volatility of positive and negative effects of equal magnitude, and leverage, which...
Persistent link: https://www.econbiz.de/10010384390
The three most popular univariate conditional volatility models are the generalized autoregressive conditional heteroskedasticity (GARCH) model of Engle (1982) and Bollerslev (1986), the GJR (or threshold GARCH) model of Glosten, Jagannathan and Runkle (1992), and the exponential GARCH (or...
Persistent link: https://www.econbiz.de/10010405194
Of the two most widely estimated univariate asymmetric conditional volatility models, the exponential GARCH (or EGARCH) specification can capture asymmetry, which refers to the different effects on conditional volatility of positive and negative effects of equal magnitude, and leverage, which...
Persistent link: https://www.econbiz.de/10010477092
In this paper we test for (Generalized) AutoRegressive Conditional Heteroskedasticity [(G)ARCH] in daily data on 22 exchange rates and 13 stock market indices using the standard Lagrange Multiplier [LM] test for GARCH and a LM test that is resistant to patches of additive outliers. The data span...
Persistent link: https://www.econbiz.de/10011284080
Tests for structural stability with unknown breakpoint are derived for and applied tothe efficient method of moments. Three types of tests are discerned: Wald type tests,Predictive tests and Hansen type tests. The Hansen type test for structural stabilitywith unknown breakpoint is a novelty for...
Persistent link: https://www.econbiz.de/10011284082
The asymmetric moving average model (asMA) is extended to allow forasymmetric quadratic conditional heteroskedasticity (asQGARCH). Theasymmetric parametrization of the conditional variance encompassesthe quadratic GARCH model of Sentana (1995). We introduce a framework fortesting asymmetries in...
Persistent link: https://www.econbiz.de/10011303289
In the class of univariate conditional volatility models, the three most popular are the generalized autoregressive conditional heteroskedasticity (GARCH) model of Engle (1982) and Bollerslev (1986), the GJR (or threshold GARCH) model of Glosten, Jagannathan and Runkle (1992), and the...
Persistent link: https://www.econbiz.de/10011688332