Simulate Event Study for Power Analysis — simulate_event

Runs Monte Carlo simulations to estimate the statistical power (rejection rate) of an event study design. Each simulation generates synthetic data from a user-specified DGP, runs the full event study pipeline, and records whether the null hypothesis is rejected.

Usage

simulate_event_study(
  n_events = 20,
  event_window = c(-5, 5),
  estimation_window_length = 120,
  abnormal_return = 0,
  return_model = MarketModel$new(),
  test_statistic = "CSectT",
  alpha = 0.05,
  n_simulations = 1000,
  dgp_params = list(),
  seed = NULL
)

Arguments

n_events: Number of events (firms) per simulation. Default 20.
event_window: Event window as c(start, end). Default c(-5, 5).
estimation_window_length: Length of the estimation window. Default 120.
abnormal_return: Injected abnormal return on the event day (day 0). Set to 0 for size analysis, positive for power analysis. Default 0.
return_model: An initialized return model object. Default MarketModel$new().
test_statistic: Name of the multi-event test statistic to evaluate. Default "CSectT".
alpha: Significance level. Default 0.05.
n_simulations: Number of Monte Carlo replications. Default 1000.
dgp_params: List of DGP parameters: alpha (drift), beta (market exposure), sigma_firm (idiosyncratic volatility), sigma_market (market volatility).
seed: Optional seed for reproducibility.

Value

An S3 object of class es_simulation with components:

power: Rejection rate at the event day
rejection_by_day: Tibble of rejection rates for each event-window day
test_stats: Vector of test statistics at the event day from each sim
params: List of simulation parameters