lmc_lev: LMC Test for Leverage in SV(p) Models

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

LMC Test for Leverage in SV(p) Models

Description

Performs a Local Monte Carlo (LMC) test of the null hypothesis H_0: \rho = \rho_0 (typically \rho_0 = 0, i.e., no leverage) using a GMM likelihood-ratio type statistic.

Usage

lmc_lev(
  y,
  p = 1,
  J = 10,
  N = 99,
  rho_null = 0,
  burnin = 500,
  rho_type = "pearson",
  del = 1e-10,
  trunc_lev = TRUE,
  wDecay = FALSE,
  Bartlett = FALSE,
  Amat = NULL,
  errorType = "Gaussian",
  logNu = FALSE,
  sigvMethod = "factored",
  winsorize_eps = 0
)

Arguments

y	Numeric vector. Observed returns.
p	Integer. Order of the volatility process. Default 1.
J	Integer. Winsorizing parameter. Default 10.
N	Integer. Number of Monte Carlo replications. Default 99.
rho_null	Numeric. Value of \rho under the null. Default 0.
burnin	Integer. Burn-in for simulation. Default 500.
rho_type	Character. Correlation type. Default "pearson".
del	Numeric. Small constant for log transformation. Default 1e-10.
trunc_lev	Logical. Truncate leverage correlation estimate to [-0.999, 0.999]. Default TRUE.
wDecay	Logical. Use decaying weights. Default FALSE.
Bartlett	Logical. If TRUE, use Bartlett kernel HAC weighting matrix. If FALSE, use identity matrix. Default FALSE.
Amat	Weighting matrix specification. NULL (default) for identity weighting, "Weighted" for data-driven HAC, or a numeric matrix of dimension (p+3)x(p+3) (Gaussian) or (p+4)x(p+4) (heavy-tail). Takes precedence over Bartlett.
errorType	Character. Error distribution: "Gaussian" (default), "Student-t", or "GED".
logNu	Logical. Use log-space for nu estimation (Student-t only). Default FALSE.
sigvMethod	Method for sigma_v estimation: "factored" (default), "direct", or "hybrid".
winsorize_eps	Number of extreme autocovariance lags to winsorize (0 = none). Default 0.

Value

An object of class "svp_test", a list containing:

s0

Test statistic from observed data.

sN

Simulated null distribution (vector of length N).

pval

Monte Carlo p-value.

test_type

Character string identifying the test.

null_param

Name of the parameter tested.

null_value

Value under the null hypothesis.

call

The matched call.

Examples

y <- sim_svp(1000, phi = 0.95, sigy = 1, sigv = 0.2, leverage = TRUE, rho = -0.3)$y
test <- lmc_lev(y, p = 1, J = 10, N = 99)
print(test)

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