dax_vw_model {fHMM}

DAX/VW hierarchical HMM with t-distributions

Description

A pre-computed HHMM with monthly averaged closing prices of the DAX from 2010 to 2022 on the coarse scale, Volkswagen AG stock data on the fine scale, two hidden fine-scale and coarse-scale states, respectively, and state-dependent t-distributions for demonstration purpose.

Usage

data("dax_vw_model")

Format

An object of class fHMM_model.

Details

The model was estimated via:

controls <- set_controls(
  hierarchy = TRUE,
  states    = c(2, 2),
  sdds      = c("t", "t"),
  period    = "m",
  data      = list(
    file       = list(dax, vw),
    from       = "2010-01-01",
    to         = "2022-12-31",
    logreturns = c(TRUE, TRUE)
  ),
  fit       = list(
    runs       = 200, 
    iterlim    = 300,
    gradtol    = 1e-6,
    steptol    = 1e-6
  )
)
dax_vw_data <- prepare_data(controls)
dax_vw_model <- fit_model(dax_vw_data, seed = 1, ncluster = 10)
dax_vw_model <- decode_states(dax_vw_model)
dax_vw_model <- compute_residuals(dax_vw_model)
summary(dax_vw_model)