1danjordan/mmr

Measuring Market Risk in R

mmr's Issues

roll on data frame

Currently roll is unpredictable or breaks if passed anything other than a vector

passing functions and arguments to compute_es

Trying to work out an elegant interface for turning VaR functions into expected shortfall measures. At the moment it seems reasonable to use as_function to pass a VaR function with further arguments in ....

Would like something like

# Compute ES by averaging tail VaRs
compute_es(some_var_measure, arg1, arg2, conf = 0.9, n = 1000)

Then ES functions could inherit the same parameters as the corresponding VaR measure and be simplified to

some_es_measure <- function(inherited_var_args, conf, n) {
    compute_es(some_var_measure, inherited_var_args, conf, n)
}

Could be more suitable to use partial though?