sym.vg_fit: Fit Symmetric Variance Gamma Distribution to a vector of...

In StockDistFit: Fit Stock Price Distributions

Fit Symmetric Variance Gamma Distribution to a vector of returns/stock prices.

Description

This function fits the Symmetric Variance Gamma (sVG) distribution to a given data vector using the fit.VGuv function from the ghyp package. It returns the estimated parameters along with the AIC and BIC values for the fitted distribution.

Usage

sym.vg_fit(vec)

Arguments

vec	a numeric vector containing the data to be fitted.

Value

a list containing the following elements:

par

a numeric vector of length 4 containing the estimated values for the parameters of the fitted distribution: lambda (scale), mu (location), sigma (volatility), and gamma (skewness).

aic

the Akaike information criterion (AIC) value for the fitted distribution.

bic

the Bayesian information criterion (BIC) value for the fitted distribution.

See Also

norm_fit, t_fit, cauchy_fit, ghd_fit, hd_fit, sym.ghd_fit, sym.hd_fit, vg_fit, nig_fit, ged_fit, skew.t_fit, skew.normal_fit, skew.ged_fit

Examples

stock_prices <- c(10, 11, 12, 13, 14, 17, 18)
returns <- diff(log(stock_prices))
sym.vg_fit(returns)

StockDistFit documentation built on May 31, 2023, 8:59 p.m.