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On the Continuous Limit of GARCH [PDF]
, 2004 GARCH processes constitute the major area of time series variance analysis, hence the limit of these processes is of considerable interest for continuous time volatility modelling. The continuous time limit of the GARCH(1,1) model is fundamental for limits of other GARCH processes, yet it has been the point of much debate between econometricians.
Carol Alexander, Emese Lazar
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Journal of Financial Econometrics, 2006
This article develops the dynamic asymmetric GARCH (or DAGARCH) model that generalizes asymmetric GARCH models such as that of Glosten, Jagannathan, and Runkle (GJR), introduces multiple thresholds, and makes the asymmetric effect time dependent. We provide the stationarity conditions for the DAGARCH model and show how GJR can be obtained as a special ...
CAPORIN, MASSIMILIANO, M. MCALEER
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This article develops the dynamic asymmetric GARCH (or DAGARCH) model that generalizes asymmetric GARCH models such as that of Glosten, Jagannathan, and Runkle (GJR), introduces multiple thresholds, and makes the asymmetric effect time dependent. We provide the stationarity conditions for the DAGARCH model and show how GJR can be obtained as a special ...
CAPORIN, MASSIMILIANO, M. MCALEER
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The Effects of Structural Breaks in Arch and GARCH Parameters on Persistence of GARCH Models
Communications in Statistics - Simulation and Computation, 2004We show that persistence of conditional volatility in large samples could be exaggerated by the existence of structural breaks in the ARCH and GARCH parameters. Our results suggest that extreme persistence frequently observed in index volatility does not necessarily indicate the same level of persistence over the sample period.
Soosung Hwang, Pedro L. Valls Pereira
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GO‐GARCH: a multivariate generalized orthogonal GARCH model
Journal of Applied Econometrics, 2002AbstractMultivariate 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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Comparison of BEKK GARCH and DCC GARCH Models: An Empirical Study
2010Modeling 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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SSRN Electronic Journal, 2008
The literature on modeling and forecasting time-varying volatility is ripe with acronyms and abbreviations used to describe the many different parametric models that have been put forth since the original linear ARCH model introduced in the seminal Nobel Prize winning paper by Engle (1982).
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The literature on modeling and forecasting time-varying volatility is ripe with acronyms and abbreviations used to describe the many different parametric models that have been put forth since the original linear ARCH model introduced in the seminal Nobel Prize winning paper by Engle (1982).
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GARCH, Outliers, and Forecasting Volatility
2011The issue of detecting and handling outliers in GARCH processes has received considerable attention recently. In this chapter, we put forwardan iterative outlier detection procedure, which is appropriate given that in practice both the number of outliers as well as their timing is unknown. Our procedure aims to test for the presence of a single outlier
Franses, Philip Hans, van Dijk, Dick
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ON MIXTURE MEMORY GARCH MODELS
Journal of Time Series Analysis, 2013We propose a new volatility model, which is called the mixture memory generalized autoregressive conditional heteroskedasticity (MM‐GARCH) model. The MM‐GARCH model has two mixture components, of which one is a short‐memory GARCH and the other is the long‐memory fractionally integrated GARCH.
Li, M, Li, WK, Li, G
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A multivariate skew-garch model
2005Empirical 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 +2 more
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Journal of Empirical Finance, 2019
There is strong empirical evidence that the GARCH estimates obtained from panels of financial time series cluster. In order to capture this empirical regularity, this paper introduces the Hierarchical GARCH (HG) model. The HG is a nonlinear panel specification in which the coefficients of each series are modeled as a function of observed series ...
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There is strong empirical evidence that the GARCH estimates obtained from panels of financial time series cluster. In order to capture this empirical regularity, this paper introduces the Hierarchical GARCH (HG) model. The HG is a nonlinear panel specification in which the coefficients of each series are modeled as a function of observed series ...
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