CalendarTimePortfolioTest: Calendar-Time Portfolio Test

In EventStudy: Event Study Analysis

Calendar-Time Portfolio Test

Description

Aggregates event-firm returns into calendar-time portfolios and tests whether the portfolio intercept (alpha) is significantly different from zero, using the Brown and Warner (1980, 1985) crude-dependence-adjustment: the standard deviation of the ESTIMATION-window cross-event average abnormal return (AAR) series is used as the (calendar-)time-series standard deviation, so the denominator is independent of the event window and of any event-window shock magnitude.

For each relative event day, the test forms an equal-weighted portfolio of all event firms' abnormal returns and computes caltime_t = AAR_t / sd(AAR_{estimation}), with degrees of freedom n_estimation_days - 1 (the number of finite estimation-window AAR observations), exposed as attr(result, "caltime_df").

Super class

TestStatisticBase -> CalendarTimePortfolioTest

Public fields

name

Short code of the test statistic.

Methods

Public methods

• CalendarTimePortfolioTest$compute()

• CalendarTimePortfolioTest$clone()

Inherited methods

• TestStatisticBase$initialize()

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CalendarTimePortfolioTest$compute()

Computes the calendar-time portfolio test.

Usage

CalendarTimePortfolioTest$compute(data_tbl, model)

Arguments

data_tbl

The data for multiple events with calculated abnormal returns.

model

The fitted models (unused directly).

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CalendarTimePortfolioTest$clone()

The objects of this class are cloneable with this method.

Usage

CalendarTimePortfolioTest$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

References

Brown, S. J. and Warner, J. B. (1980). Measuring security price performance. Journal of Financial Economics, 8(3), 205–258.

Brown, S. J. and Warner, J. B. (1985). Using daily stock returns: The case of event studies. Journal of Financial Economics, 14(1), 3–31.

See Also

Other eventstudy-statistics: ARTTest, BHARTTest, BMPTest, CARTTest, CSectTTest, GeneralizedSignTest, KolariPynnonenTest, MultiEventStatisticsSet, PatellZTest, RankTest, SignTest, SingleEventStatisticsSet, StatisticsSetBase, TestStatisticBase, adjust_p_values(), bootstrap_test(), car_by_group(), car_quantiles(), cross_sectional_regression(), model_diagnostics(), pretrend_test(), simulate_event_study(), validate_task()

EventStudy documentation built on Oct. 31, 2026, 1:07 a.m.