gLog.ep: Adjust for zero values and compute log(abs(e)^p)
Description
Adjusts a series called e - typically a series of residuals or
financial returns - for zero values, so that the logarithm can be
applied on the absolute pth. exponentiated values. Next,
log(abs(e)^p) is computed
Usage
gLog.ep(e, zero.adj=0.1, p=2, na.replace=NA)
Arguments
e
numeric vector, time series or zoo object
zero.adj
numeric value between 0 and 1. The quantile adjustment for zero values.
The default 0.1 means that the zero residuals are replaced by means of
the 10 percent quantile of abs(e) before taking the
logarithm
p
numeric value greater than zero. The power of the log-volatility
specification.
na.replace
the value to replace NA values with. Default: na.replace=NA
Value
log(abs(e)^p), where the e values have been zero adjusted
References
Genaro Sucarrat and Alvaro Escribano (2012): 'Automated Financial
Model Selection: General-to-Specific Modelling of the Mean and
Volatility Specifications', Oxford Bulletin of Economics and
Statistics 74, Issue no. 5 (October), pp. 716-735