tegarchSim: Simulate from a first order Beta-Skew-t-EGARCH model In betategarch: Simulation, Estimation and Forecasting of Beta-Skew-t-EGARCH Models

Description

Simulate the y series (typically interpreted as a financial return or the error in a regression) from a first order Beta-Skew-t-EGARCH model. Optionally, the conditional scale (sigma), log-scale (lambda), conditional standard deviation (stdev), dynamic components (lambdadagger in the 1-component specification, lambda1dagger and lambda2dagger in the 2-component specification), score (u) and centred innovations (epsilon) are also returned.

Usage

 1 2 tegarchSim(n, omega = 0, phi1 = 0.95, phi2 = 0, kappa1 = 0.01, kappa2 = 0, kappastar = 0, df = 10, skew = 1, lambda.initial = NULL, verbose = FALSE)

Arguments

 n integer, length of y (i.e. no of observations) omega numeric, the value of omega phi1 numeric, the value of phi1 phi2 numeric, the value of phi2 kappa1 numeric, the value of kappa1 kappa2 numeric, the value of kappa2 kappastar numeric, the value of kappastar df numeric, the value of df (degrees of freedom) skew numeric, the value of skew (skewness parameter lambda.initial NULL (default) or initial value(s) of the recursion for lambda or log-volatility. If NULL then the values are chosen automatically verbose logical, TRUE or FALSE (default). If TRUE then a matrix with n rows containing y, sigma, lambda, lambdadagger, u and epsilon is returned. If FALSE then only y is returned

Empty

Value

A zoo vector of length n or a zoo matrix with n rows, depending on the value of verbose.

Author(s)

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

References

Fernandez and Steel (1998), 'On Bayesian Modeling of Fat Tails and Skewness', Journal of the American Statistical Association 93, pp. 359-371.

Harvey and Sucarrat (2014), 'EGARCH models with fat tails, skewness and leverage'. Computational Statistics and Data Analysis 76, pp. 320-338.

Sucarrat (2013), 'betategarch: Simulation, Estimation and Forecasting of First-Order Beta-Skew-t-EGARCH models'. The R Journal (Volume 5/2), pp. 137-147.