mmc_t: MMC Test for Student-t Tail Parameter

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

MMC Test for Student-t Tail Parameter

Description

Performs a Maximized Monte Carlo (MMC) test of H_0: \nu = \nu_0 by maximizing the MC p-value over nuisance parameters (phi, sigma_y, sigma_v).

Usage

mmc_t(
  y,
  p = 1,
  J = 10,
  N = 99,
  nu_null,
  burnin = 500,
  eps = NULL,
  threshold = 1,
  method = "pso",
  maxit = NULL,
  del = 1e-10,
  wDecay = FALSE,
  Bartlett = FALSE,
  Amat = NULL,
  logNu = TRUE,
  direction = c("two-sided", "less", "greater"),
  sigvMethod = "factored",
  winsorize_eps = 0
)

Arguments

y	Numeric vector. Observed returns.
p	Integer. AR order of the volatility process. Default 1.
J	Integer. Winsorizing parameter. Default 10.
N	Integer. Number of Monte Carlo replications. Default 99.
nu_null	Numeric. Value of \nu under the null hypothesis.
burnin	Integer. Burn-in for simulation. Default 500.
eps	Numeric vector. Half-width of search region around estimated nuisance parameters. Must have length p+2 (one entry per nuisance parameter: \phi_1,\ldots,\phi_p, \sigma_y, \sigma_v). Default rep(0.3, p+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. Use Bartlett kernel HAC for weighting matrix. Default FALSE.
Amat	Weighting matrix specification. NULL (default) for identity weighting, "Weighted" for data-driven HAC, or a (p+3)x(p+3) matrix. Takes precedence over Bartlett.
logNu	Logical. Use log-space for nu estimation. Default TRUE.
direction	Character. Test direction: "two-sided" (default), "less" (H1: nu < nu_null), or "greater" (H1: nu > nu_null). Uses signed root of the LR statistic for one-sided tests.
sigvMethod	Character. Method for \sigma_v estimation: "factored" (default), "hybrid", or "direct".
winsorize_eps	Numeric. Winsorization threshold for moment conditions. Default 0 (no winsorization).

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, errorType = "Student-t", nu = 5)$y
mmc <- mmc_t(y, p = 1, J = 10, N = 19, nu_null = 5, method = "pso", maxit = 10)
mmc$value

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