Fitting Hidden Markov Models to Financial Data

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Documentation for package ‘fHMM’ version 1.1.0

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

coef.fHMM_model	Model coefficients
compare_models	Compare multiple models
compute_residuals	Compute (pseudo-) residuals
dax	Deutscher Aktienindex (DAX) index data
dax_model_2n	DAX 2-state HMM with normal distributions
dax_model_3t	DAX 3-state HMM with t-distributions
dax_vw_model	DAX/VW hierarchical HMM with t-distributions
decode_states	Decode the underlying hidden state sequence
download_data	Download financial data from Yahoo Finance
fHMM_data	Constructor of an 'fHMM_data' object
fHMM_events	Checking events
fHMM_model	Constructor of a model object
fHMM_parameters	Set and check model parameters
fit_model	Model fitting
npar	Number of model parameters
npar.fHMM_model	Number of model parameters
plot.fHMM_data	Plot method for an object of class 'fHMM_data'
plot.fHMM_model	Plot method for an object of class 'fHMM_model'
predict.fHMM_model	Prediction
prepare_data	Prepare data
print.fHMM_controls	Set and validate controls
print.fHMM_data	Constructor of an 'fHMM_data' object
print.fHMM_events	Checking events
print.fHMM_model	Model fitting
print.fHMM_parameters	Set and check model parameters
reorder_states	Reorder estimated states
residuals.fHMM_model	Residuals
set_controls	Set and validate controls
sim_model_2gamma	Simulated 2-state HMM with gamma distributions
sim_model_4lnorm	Simulated 4-state HMM with log-normal distributions
spx	Standard & Poor’s 500 (S&P 500) index data
summary.fHMM_data	Constructor of an 'fHMM_data' object
unemp	Unemployment rate data USA
unemp_spx_model_3_2	Unemployment rate and S&P 500 hierarchical HMM
vw	Volkswagen AG (VW) stock data