% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/merton_fit.R
\name{fitMerton}
\alias{fitMerton}
\title{Fit Merton Jump-Diffusion Model via MLE}
\usage{
fitMerton(
  log_returns,
  start = c(mu = 0.05, sigma = 0.2, lambda = 1, mu_j = -0.1, sigma_j = 0.15),
  dt = 1/252,
  N_max = 50L,
  verbose = FALSE
)
}
\arguments{
\item{log_returns}{Numeric vector of observed log asset returns.}

\item{start}{Named numeric vector of starting values.
Defaults to \code{c(mu=0.05, sigma=0.20, lambda=1,
  mu_j=-0.10, sigma_j=0.15)}.}

\item{dt}{Numeric. Time step length (default 1/252).}

\item{N_max}{Integer. Mixture truncation (default 50).}

\item{verbose}{Logical. Print progress? (default FALSE).}
}
\value{
A \linkS4class{JDFitResult} object.
}
\description{
Maximises the log-likelihood of the Merton (1976) model using
L-BFGS-B optimisation. Returns a \linkS4class{JDFitResult} object
containing parameter estimates, standard errors, and convergence info.
}
\examples{
\donttest{
ret <- jdSampleData("merton", n = 500, seed = 42)
fit <- fitMerton(ret, verbose = TRUE)
print(fit)
confint(fit)
}

}
