Run Monte Carlo Study for DCC(1,1) Estimation

Performs a Monte Carlo simulation study to assess the accuracy of DCC parameter estimation. Computes bias, RMSE, and coverage probabilities.

Usage

run_dcc_monte_carlo(
  n_sim = 100,
  n_obs = 500,
  k = 2,
  true_alpha = 0.05,
  true_beta = 0.9,
  omega = NULL,
  alpha_garch = NULL,
  beta_garch = NULL,
  confidence_level = 0.95,
  verbose = TRUE,
  seed = 12345
)

Arguments

n_sim

Number of simulation replications

n_obs

Number of observations per replication

k

Number of series (default 2)

true_alpha

True DCC alpha parameter

true_beta

True DCC beta parameter

omega

Vector of GARCH omega parameters (default: rep(0.05, k))

alpha_garch

Vector of GARCH alpha parameters (default: rep(0.10, k))

beta_garch

Vector of GARCH beta parameters (default: rep(0.85, k))

confidence_level

Confidence level for coverage (default 0.95)

verbose

Print progress

seed

Base seed for reproducibility

Value

List with:

estimates

Matrix of estimates (n_sim x 2)

std_errors

Matrix of standard errors (n_sim x 2)

bias

Bias for each parameter

rmse

RMSE for each parameter

coverage

Coverage probability for each parameter

summary

Summary data frame