Residual Trading Days Test

Usage

td_f(
  s,
  model = c("D1", "DY", "DYD1", "WN", "AIRLINE", "R011", "R100"),
  nyears = 0
)

Arguments

s: a ts object that corresponds to the input time series to test.
model: the model to use for the residuals. See details.
nyears: integer that corresponds to the length of the sub series, starting from the end of the series, to be used for the test: in number of periods (positive value) or years (negative values). By default (nyears = 0), the entire sample is used.

Value

a JD3_TEST object with value, p-value and information about the distribution

Details

The function performs a residual seasonality test that is a joint F-Test on the coefficients of trading days regressors. Several specifications can be used on the model:

model = "WN" the following model is used: $$ y_t - \bar y =\beta TD_t + \varepsilon_t $$
model = "D1" (the default) the following model is used: $$ \Delta y_t - \overline{\Delta y} =\beta \Delta TD_t + \varepsilon_t $$
model = "DY" the following model is used: $$ \Delta_s y_t - \overline{\Delta_s y} =\beta \Delta_s TD_t + \varepsilon_t $$
model = "DYD1" the following model is used: $$ \Delta_s\Delta y_t - \overline{\Delta_s \Delta y} =\beta \Delta_s \Delta TD_t + \varepsilon_t $$
model = "AIRLINE" the following model is used: $$ y_t =\beta TD_t + \varepsilon_t \text{ with }\varepsilon_t \sim ARIMA(0,1,1)(0,1,1) $$
model = "R011" the following model is used: $$ y_t =\beta TD_t + \varepsilon_t \text{ with }\varepsilon_t \sim ARIMA(0,1,1) $$
model = "R100" the following model is used: $$ y_t =\alpha_0 + \alpha_1 y_{t-1} + \beta TD_t + \varepsilon_t $$

Examples

td_f(ABS$X0.2.09.10.M)
#> Value: 0.5919107 
#> P-Value: 0.7369