# 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.

`tegarch`, `zoo`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18``` ```##1-component specification: simulate series with 500 observations: set.seed(123) y <- tegarchSim(500, omega=0.01, phi1=0.9, kappa1=0.1, kappastar=0.05, df=10, skew=0.8) ##simulate the same series, but with more output (volatility, log-volatility or ##lambda, lambdadagger, u and epsilon) set.seed(123) y <- tegarchSim(500, omega=0.01, phi1=0.9, kappa1=0.1, kappastar=0.05, df=10, skew=0.8, verbose=TRUE) ##plot the simulated values: plot(y) ##2-component specification: simulate series with 500 observations: set.seed(123) y <- tegarchSim(500, omega=0.01, phi1=0.95, phi2=0.9, kappa1=0.01, kappa2=0.05, kappastar=0.03, df=10, skew=0.8) ```