bahibo_garch: Garch Analyse

In StephanBahibo/Bahibo: Prices and historical crypto data (Crypto Data)

Description

We check 336 Garch models. Garch(0-6,1-6) = 7*6 = 42 models for 8 different conditional distributions ("norm", "snorm", "ged", "sged", "std", "sstd" , "snig", "QMLE). For more details: library(fGarch) function garchFit()

Usage

  bahibo.garch(data="r",cond.dist = c("norm", "snorm", "ged", "sged", "std", "sstd","snig", "QMLE"))

Arguments

r	use the log returns from a data time series
cond.dist	cond.dist a character string naming the desired conditional distribution. Valid values are "dnorm", "dged", "dstd", "dsnorm", "dsged", "dsstd" and "QMLE". The default value is the normal distribution. See Details for more information.

Value

you get a data.frame with 13 colums.

AIC
BIC
SIC
HQIC
pval_Box_r_lag_10	p-value from Ljung Box Test for standardize Residuels lag 10. It´s a test of indepently. Compute the Ljung Box test statistic for examining the null hypothesis of independence in a given time series. These are sometimes known as "portmanteau" tests.
pval_Box_r_lag_15	p-value from Ljung Box Test for standardize Residuels lag 15.
pval_Box_r_lag_20	p-value from Ljung Box Test for standardize Residuels lag 15.
pval_Box_r2_lag_10	p-value from Ljung Box Test for standardize Residuels^2 lag 10.
pval_Box_r2_lag_15	p-value from Ljung Box Test for standardize Residuels^2 lag 15.
pval_Box_r2_lag_20	p-value from Ljung Box Test for standardize Residuels^2 lag 20.
pval_jarq	p-value jarqueberaTest - testing normality of financial return series
pval_shapiro	p-value Shapiro-Wilk's test for normality
llh	Log Likelihood

Author(s)

S.Baartz

Examples

  # load data I
  btc<-bahibo.hist(coin = "bitcoin",start = "2021-01-01",end = "2021-06-01",currency = "USD",quote = "Close")
  btc<-zoo(btc$Close,as.Date(rownames(btc)))
  r<-diff(log(btc))
  parameter_btc<-bahibo.garch(r)

  # load data IIlibrary(quantmod)
  library(quantmod)
  getSymbols('SPY')
  spy<-SPY$SPY.Close
  R<-diff(log(spy))
  R<-R[1:100]
  parameter_spy<-bahibo.garch(R)

  #analysce data
  str(parameter_spy)
  summary(parameter_spy)
  subset(parameter_spy,AIC<7)

StephanBahibo/Bahibo documentation built on Feb. 13, 2022, 9:13 a.m.