R: Fitting Hidden Markov Models to Financial Data

# Fitting Hidden Markov Models to Financial Data

## Documentation for package ‘fHMM’ version 1.1.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## 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