A pre-computed HMM on closing prices of the DAX from 2000 to 2022 with two hidden states and normal state-dependent distributions for demonstration purpose.
Usage
data("dax_model_2n")Format
An object of class fHMM_model.
Details
The model was estimated via:
controls <- set_controls(
states = 2,
sdds = "normal",
data = list(
file = dax,
date_column = "Date",
data_column = "Close",
logreturns = TRUE,
from = "2000-01-03",
to = "2022-12-31"
),
fit = list("runs" = 10, "gradtol" = 1e-6, "steptol" = 1e-6)
)
dax_data <- prepare_data(controls)
dax_model_2n <- fit_model(dax_data, seed = 1)
dax_model_2n <- decode_states(dax_model_2n)
dax_model_2n <- compute_residuals(dax_model_2n)
summary(dax_model_2n)