NNS (version 0.8.5)

NNS.nowcast: NNS Nowcast

Description

Wrapper function for NNS nowcasting method using NNS.VAR as detailed in Viole (2020), https://www.ssrn.com/abstract=3586658.

Usage

NNS.nowcast(
  h = 12,
  additional.regressors = NULL,
  start.date = "2000-01-03",
  Quandl.key = NULL,
  status = TRUE,
  ncores = NULL
)

Arguments

h

integer; (h = 12) (default) Number of periods to forecast. (h = 0) will return just the interpolated and extrapolated values.

additional.regressors

character; NULL (default) add more regressors to the base model. The format must utilize the Quandl exchange format as described in https://docs.data.nasdaq.com/docs/data-organization. For example, the 10-year US Treasury yield using the St. Louis Federal Reserve data is "FRED/DGS10".

start.date

character; "2000-01-03" (default) Starting date for all data series download.

Quandl.key

character; NULL (default) User provided Quandl API key WITH QUOTES. If previously entered in the current environment via Quandl::Quandl.api_key, no further action required.

status

logical; TRUE (default) Prints status update message in console.

ncores

integer; value specifying the number of cores to be used in the parallelized subroutine NNS.ARMA.optim. If NULL (default), the number of cores to be used is equal to the number of cores of the machine - 1.

Value

Returns the following matrices of forecasted variables:

• "interpolated_and_extrapolated" Returns a data.frame of the linear interpolated and NNS.ARMA extrapolated values to replace NA values in the original variables argument. This is required for working with variables containing different frequencies, e.g. where NA would be reported for intra-quarterly data when indexed with monthly periods.

• "relevant_variables" Returns the relevant variables from the dimension reduction step.

• "univariate" Returns the univariate NNS.ARMA forecasts.

• "multivariate" Returns the multi-variate NNS.reg forecasts.

• "ensemble" Returns the ensemble of both "univariate" and "multivariate" forecasts.

References

Viole, F. and Nawrocki, D. (2013) "Nonlinear Nonparametric Statistics: Using Partial Moments" https://www.amazon.com/dp/1490523995/ref=cm_sw_su_dp

Viole, F. (2019) "Multi-variate Time-Series Forecasting: Nonparametric Vector Autoregression Using NNS" https://www.ssrn.com/abstract=3489550

Viole, F. (2020) "NOWCASTING with NNS" https://www.ssrn.com/abstract=3586658

Examples

# NOT RUN {
 
# }
# NOT RUN {
 NNS.nowcast(h = 12)
 
# }
# NOT RUN {
# }