dax_model_3t: DAX 3-state HMM with t-distributions

In fHMM: Fitting Hidden Markov Models to Financial Data

DAX 3-state HMM with t-distributions

Description

A pre-computed HMM on closing prices of the DAX from 2000 to 2022 with three hidden states and state-dependent t-distributions for demonstration purpose.

Usage

data("dax_model_3t")

Format

An object of class fHMM_model.

Details

The model was estimated via:

controls <- set_controls(
  states = 3,
  sdds   = "t",
  data   = list(
    file        = dax,
    date_column = "Date",
    data_column = "Close",
    logreturns  = TRUE,
    from        = "2000-01-03",
    to          = "2022-12-31"
  ),
  fit    = list(
    runs        = 100, 
    iterlim     = 300,
    gradtol     = 1e-6,
    steptol     = 1e-6
  )
)
dax_data <- prepare_data(controls)
dax_model_3t <- fit_model(dax_data, seed = 1, ncluster = 10)
dax_model_3t <- decode_states(dax_model_3t)
dax_model_3t <- compute_residuals(dax_model_3t)
summary(dax_model_3t)

fHMM documentation built on April 3, 2025, 5:49 p.m.