Results 221 to 230 of about 3,114 (262)

GARCH-type factor model

Journal of Multivariate Analysis, 2022
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Yuanbo Li, Chi Tim Ng, Chun Yip Yau
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A tobit model with garch errors [PDF]

Econometric Reviews, 1998
In the context of time series regression, we extend the standard Tobit model to allow for the possibility of conditional heteroskedastic error processes of the GARCH type. We discuss the likelihood function of the Tobit model in the presence of conditionally heteroskedastic errors.
CALZOLARI, GIORGIO, FIORENTINI, GABRIELE
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A multivariate skew-garch model

2005
Empirical research on European stock markets has shown that they behave differently according to the performance of the leading financial market identified as the US market. A positive sign is viewed as good news in the international financial markets, a negative sign means, conversely, bad news.
DE LUCA, GIOVANNI, LOPERFIDO N, GENTON M.   +2 more
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EMPIRICAL LIKELIHOOD FOR GARCH MODELS

Econometric Theory, 2006
Summary: This paper develops an empirical likelihood approach for regular generalized autoregressive conditional heteroskedasticity (GARCH) models and GARCH models with unit roots. For regular GARCH models, it is shown that the log empirical likelihood ratio statistic asymptotically follows a \(\chi^2\) distribution.
Chan, NH, Ling, SQ
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GO‐GARCH: a multivariate generalized orthogonal GARCH model

Journal of Applied Econometrics, 2002
AbstractMultivariate GARCH specifications are typically determined by means of practical considerations such as the ease of estimation, which often results in a serious loss of generality. A new type of multivariate GARCH model is proposed, in which potentially large covariance matrices can be parameterized with a fairly large degree of freedom while ...
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Adaptive Filtering for GARCH Models

2002
The volatility of a speculative asset is a fundamental ingredient of many financial pricing algorithms, therefore, accurate forecasts of volatility are essential to financial practioners. Autoregressive Conditional Heteroscekdastic models and their generalisations (GARCH) have been shown to provide reasonable forecasts of volatility with relatively few
Paul E. Lynch, Nigel M. Allinson
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Varying Coefficient GARCH Models

2009
This paper offers a new method for estimation and forecasting of the volatility of financial time series when the stationarity assumption is violated. We consider varying–coefficient parametric models, such as ARCH and GARCH, whose coefficients may arbitrarily vary with time.
Cizek, P., Spokoiny, V.
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Dynamic Factor Multivariate GARCH Model

SSRN Electronic Journal, 2012
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André Alves Portela Santos, Guilherme V. Moura   +1 more
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THE GARCH OPTION PRICING MODEL

Mathematical Finance, 1995
This article develops an option pricing model and its corresponding delta formula in the context of the generalized autoregressive conditional heteroskedastic (GARCH) asset return process. the development utilizes the locally risk‐neutral valuation relationship (LRNVR).
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Comparison of BEKK GARCH and DCC GARCH Models: An Empirical Study

2010
Modeling volatility and co-volatility of a few zero-coupon bonds is a fundamental element in the field of fix-income risk evaluation. Multivariate GARCH model (MGARCH), an extension of the well-known univariate GARCH, is one of the most useful tools in modeling the co-movement of multivariate time series with time-varying covariance matrix. Grounded on
Yiyu Huang, Wenjing Su, Xiang Li 0033
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