Package index • fHMM

Data preparation

Use these functions to prepare or simulate financial data.

set_controls() validate_controls() print(<fHMM_controls>) summary(<fHMM_controls>): Define and validate model specifications

download_data(): Download financial data from Yahoo Finance

simulate_hmm(): Simulate data

prepare_data(): Prepare data

fHMM_data() print(<fHMM_data>) summary(<fHMM_data>): Constructor of an fHMM_data object

plot(<fHMM_data>): Plot method for an object of class fHMM_data

Model parameters

Use these functions to define and transform model parameters.

fHMM_parameters() print(<fHMM_parameters>): Set and check model parameters

par2parUncon() parUncon2parCon() parCon2par() par2parCon() parCon2parUncon() parUncon2par() muCon2muUncon() muUncon2muCon() sigmaCon2sigmaUncon() sigmaUncon2sigmaCon() dfCon2dfUncon() dfUncon2dfCon() Gamma2gammasCon() Gamma2gammasUncon() gammasCon2Gamma() gammasCon2gammasUncon() gammasUncon2Gamma() gammasUncon2gammasCon(): Parameter transformations

Model estimation

Use these function for model estimation and state decoding.

ll_hmm(): Log-likelihood function of an (H)HMM

fit_model(): Model fitting

fHMM_model() print(<fHMM_model>) residuals(<fHMM_model>) summary(<fHMM_model>) coef(<fHMM_model>) AIC(<fHMM_model>) BIC(<fHMM_model>) nobs(<fHMM_model>) logLik(<fHMM_model>) npar() predict(<fHMM_model>): Constructor of a model object

decode_states() viterbi(): Decode the underlying hidden state sequence

reorder_states(): Reorder estimated states

Model evaluation

Use these functions to evaluate a fitted model.

fHMM_model() print(<fHMM_model>) residuals(<fHMM_model>) summary(<fHMM_model>) coef(<fHMM_model>) AIC(<fHMM_model>) BIC(<fHMM_model>) nobs(<fHMM_model>) logLik(<fHMM_model>) npar() predict(<fHMM_model>): Constructor of a model object

compare_models(): Compare multiple models

compute_residuals(): Compute (pseudo-) residuals

plot(<fHMM_model>): Plot method for an object of class fHMM_model

fHMM_colors(): Set color scheme for visualizations

fHMM_events() print(<fHMM_events>): Checking events

Data

The following data sets are included in the package.

dax: Deutscher Aktienindex (DAX) index data

spx: Standard & Poor’s 500 (S&P 500) index data

unemp: Unemployment rate data USA

vw: Volkswagen AG (VW) stock data

Models

The following pre-computed models are included in the package.

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

sim_model_2gamma: Simulated 2-state HMM with gamma distributions

unemp_spx_model_3_2: Unemployment rate and S&P 500 hierarchical HMM