summary.MDSVboot: Summarize and print MDSV bootstrap forecasting

In Abdoulhaki/MDSV: Multifractal Discrete Stochastic Volatility

Summarize and print MDSV bootstrap forecasting

Description

Summary and print methods for the class MDSVboot as returned by the function MDSVboot.

Usage

## S3 method for class 'MDSVboot'
summary(object, ...)

## S3 method for class 'summary.MDSVboot'
print(x, ...)

## S3 method for class 'MDSVboot'
print(x, ...)

Arguments

object	An object of class MDSVboot, output of the function MDSVboot.
...	Further arguments passed to or from other methods.
x	An object of class summary.MDSVboot, output of the function summary.MDSVboot or class MDSVboot of the function MDSVboot.

Value

A list consisting of:

• ModelType : type of model to be fitted.

• LEVIER : wheter the fit take the leverage effect into account or not.

• N : number of components for the MDSV process.

• K : number of states of each MDSV process component.

• estimates : estimated parameters.

• LogLikelihood : log-likelihood of the model on the data.

• AIC : Akaike Information Criteria of the model on the data.

• BIC : Bayesian Information Criteria of the model on the data.

• data : data use for the fitting.

• dates : vector or names of data designing the dates.

• n.ahead : integer designing the forecast horizon.

• n.bootpred : integer designing the number of simulation based re-fits used to generate the parameter distribution.

• rt_sim : matrix of log-returns forecast simulated where the row stand for the simulations and the columns for the horizon.

• rt2 : vector of mean by column of the square of rt_sim.

• rvt_sim : matrix of realized variances forecast simulated where the row stand for the simulations and the columns for the horizon.

• rvt : vector of mean by column of rvt_sim.

See Also

For fitting MDSVfit, filtering MDSVfilter, bootstrap forecasting MDSVboot and rolling estimation and forecast MDSVroll.

Abdoulhaki/MDSV documentation built on July 6, 2024, 4:03 p.m.