tegarchLogl: Auxiliary functions

Description

tegarchLogl, tegarchLogl2, tegarchRecursion and tegarchRecursion2 are auxiliary functions called by tegarch, and which are not intended to be used for the average user. Henceforth they are thusonly scarcely documented, but most should either be self-explanatory (for the non-average user!) or more or less documented in relation with the tegarch and tegarchSim functions.

Usage

##the '2' relates to the 2-component specification:
tegarchLogl(y, pars, lower = -Inf, upper = Inf, lambda.initial = NULL,
  logl.penalty = -1e+100, c.code = TRUE, aux = NULL)
tegarchLogl2(y, pars, lower = -Inf, upper = Inf, lambda.initial = NULL,
  logl.penalty = -1e+101, c.code = TRUE, aux = NULL)
tegarchRecursion(y, omega = 0.1, phi1 = 0.4, kappa1 = 0.2, kappastar = 0.1,
  df = 10, skew = 0.6, lambda.initial = NULL, c.code = TRUE, verbose = FALSE,
  aux = NULL)
tegarchRecursion2(y, omega = 0.1, phi1 = 0.4, phi2 = 0.2, kappa1 = 0.05,
  kappa2 = 0.1, kappastar = 0.02, df = 10, skew = 0.6, lambda.initial = NULL,
  c.code = TRUE, verbose = FALSE, aux = NULL)

Value

tegarchLogl:: The log-likelihood value (i.e. a numeric) of a 1-component specification
tegarchLogl2:: The log-likelihood value (i.e. a numeric) of a 2-component specification
tegarchRecursion:: A numeric vector containing the lambda values if verbose=FALSE (default). If verbose=TRUE then a matrix then a matrix with y and the fitted values of sigma, the log-scale (lambda), the conditional standard deviation (stdev), u, epsilon and the standardised residuals (residstd) are returned
tegarchRecursion2:: A numeric vector containing the lambda values if verbose=FALSE (default). If verbose=TRUE, then a matrix then a matrix with y and the fitted values of sigma, the log-scale (lambda), the conditional standard deviation (stdev), u, epsilon and the standardised residuals (residstd) are returned

Arguments

y: numeric vector, typically a financial return series
omega: numeric
phi1: numeric, must be less than 1 in absolute value
phi2: numeric, must be less than 1 in absolute value
kappa1: numeric
kappa2: numeric
kappastar: numeric
df: numeric, the value of df (degrees of freedom)
skew: numeric (positive), the value of skew (skewness parameter)
verbose: logical. If FALSE (default) then only lambda is returned. If TRUE then a matrix with y and the fitted values of, amongst other, sigma, the log-scale (lambda), the conditional standard deviation (stdev), u, epsilon and the standardised residuals (residstd) are returned
pars: numeric vector, the parameter values
lower: numeric vector, the lower bounds used during estimation
upper: numeric vector, the upper bounds used during estimation
lambda.initial: NULL (default) or initial value(s) of the recursion for lambda. If NULL, then the values are chosen automatically
logl.penalty: numeric value
c.code: logical. TRUE (default) is faster since it makes use of compiled C-code
aux: NULL (default) or a list, se tegarch code

Author

Genaro Sucarrat, http://www.sucarrat.net/

Details

tegarchLogl and tegarchLogl2 return the value of the log-likelihood for a 1-component and 2-component model, respectively.

References

C. Fernandez and M. Steel (1998), 'On Bayesian Modeling of Fat Tails and Skewness', Journal of the American Statistical Association 93, pp. 359-371, tools:::Rd_expr_doi("https://doi.org/10.1080/01621459.1998.10474117")

A. Harvey and G. Sucarrat (2014), 'EGARCH models with fat tails, skewness and leverage'. Computational Statistics and Data Analysis 76, pp. 320-338, tools:::Rd_expr_doi("https://doi.org/10.1016/j.csda.2013.09.022")

G. Sucarrat (2013), 'betategarch: Simulation, Estimation and Forecasting of First-Order Beta-Skew-t-EGARCH models'. The R Journal (Volume 5/2), pp. 137-147, ,tools:::Rd_expr_doi("https://doi.org/10.32614/RJ-2013-034")