This paper illustrates the usage of the betategarch package, a package for the simulation, estimation and forecasting of Beta-Skew-t-EGARCH models. The Beta-Skew-t-EGARCH model is a dynamic model of the scale or volatility of financial returns. The model is characterised by its robustness to jumps or outliers, and by its exponential specification of volatility. The latter enables richer dynamics, since parameters need not be restricted to be positive to ensure positivity of volatility. In addition, the model also allows for heavy tails and skewness in the conditional return (i.e. scaled return), and for leverage and a time-varying long-term component in the volatility specification. More generally, the model can be viewed as a model of the scale of the error in a dynamic regression.
tseries, fGarch, rugarch, AutoSEARCH, zoo
Finance, TimeSeries, Econometrics, Environmetrics
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For attribution, please cite this work as
Sucarrat, "The R Journal: betategarch: Simulation, Estimation and Forecasting of Beta-Skew-t-EGARCH Models", The R Journal, 2013
BibTeX citation
@article{RJ-2013-034, author = {Sucarrat, Genaro}, title = {The R Journal: betategarch: Simulation, Estimation and Forecasting of Beta-Skew-t-EGARCH Models}, journal = {The R Journal}, year = {2013}, note = {https://doi.org/10.32614/RJ-2013-034}, doi = {10.32614/RJ-2013-034}, volume = {5}, issue = {2}, issn = {2073-4859}, pages = {137-147} }