mmc_ar: MMC Test for AR Order in SV(p) Models

In wARMASVp: Winsorized ARMA Estimation for Higher-Order Stochastic Volatility Models

MMC Test for AR Order in SV(p) Models

Description

Performs a Maximized Monte Carlo (MMC) test of H_0: \phi_{p_0+1} = \cdots = \phi_p = 0 by maximizing the MC p-value over nuisance parameters (\phi_1, \ldots, \phi_{p_0}, \sigma_y, \sigma_v).

Usage

mmc_ar(
  y,
  p_null,
  p_alt,
  J = 10,
  N = 99,
  burnin = 500,
  eps = NULL,
  threshold = 1,
  method = "pso",
  maxit = NULL,
  del = 1e-10,
  wDecay = FALSE,
  Bartlett = FALSE,
  Amat = NULL,
  errorType = "Gaussian",
  sigvMethod = "factored",
  logNu = TRUE,
  winsorize_eps = 0
)

Arguments

y	Numeric vector. Observed returns.
p_null	Integer. Order under the null hypothesis.
p_alt	Integer. Order under the alternative (p_alt > p_null).
J	Integer. Winsorizing parameter. Default 10.
N	Integer. Number of Monte Carlo replications. Default 99.
burnin	Integer. Burn-in for simulation. Default 500.
eps	Numeric vector. Half-width of search region around estimated nuisance parameters. Default rep(0.3, p_null+2).
threshold	Numeric. Target p-value. Default 1.
method	Character. Optimization method: "pso" or "GenSA". Default "pso".
maxit	Integer. Maximum iterations/evaluations. Default depends on method.
del	Numeric. Small constant for log transformation. Default 1e-10.
wDecay	Logical. Use decaying weights. Default FALSE.
Bartlett	Logical. If TRUE, use Bartlett kernel HAC weighting matrix for a GMM-LRT-type test statistic. If FALSE (default), use the sum of squared extra AR coefficients.
Amat	Weighting matrix specification. NULL (default) for identity weighting, or "Weighted" for data-driven HAC. Takes precedence over Bartlett. User-supplied matrices are not supported for AR order tests.
errorType	Character. Error distribution of the return innovations: "Gaussian" (default), "Student-t", or "GED". Heavy-tail options reuse the same moment-based GMM-LRT machinery as lmc_t/ lmc_ged; \nu is held at the null MLE during the simulation (it is not a varied nuisance for the AR-order test).
sigvMethod	Character. Method for \sigma_v estimation: "factored" (default), "hybrid", or "direct".
logNu	Logical. Use log-space for \nu estimation (Student-t/GED only). Default TRUE.
winsorize_eps	Number of extreme autocovariance lags to winsorize (heavy-tail only). Default 0.

Value

A list with optimization output including value (maximized p-value) and par (nuisance parameters at the maximum).

Examples

y <- sim_svp(1000, phi = 0.95, sigy = 1, sigv = 0.2)$y
mmc <- mmc_ar(y, p_null = 1, p_alt = 2, J = 10, N = 19,
              method = "pso", maxit = 10)
mmc$value

wARMASVp documentation built on May 15, 2026, 5:07 p.m.