sar: Standardized abnormal returns (SAR) in long-horizon event...

In crseEventStudy: A Robust and Powerful Test of Abnormal Stock Returns in Long-Horizon Event Studies

Standardized abnormal returns (SAR) in long-horizon event studies

Description

sar implements the calculation of standardized abnormal returns.

Standardized abnormal returns are defined as the excess event-return relative to a specific return of a matching control firm, and the remaining result subsequently divided by the standard variation of this excess return series: SAR_{it} = \frac{r_{event} - r_{control}}{sd_{event-control}}, with log-returns r_{event} and r_{control}. The matching control-return should be a single firm return-series and not portfolio-returns.

Usage

sar(event, control, logret="FALSE")

Arguments

event	a vector or time series of returns.
control	a vector or time series of returns.
logret	An object of class "logical": If logret is FALSE, then both return-series 'event' and 'control' will be converted into log-returns before calculating standardized abnormal returns. Set logret to TRUE, if both return-series are already log-returns.

Value

sar returns a vector of class "numeric":

SAR	Vector containing standardized abnormal returns.

References

Dutta, A., Knif, J., Kolari, J.W., Pynnonen, S. (2018): A robust and powerful test of abnormal stock returns in long-horizon event studies. Journal of Empirical Finance, 47, p. 1-24. doi: 10.1016/j.jempfin.2018.02.004.

Examples

## load demo_returns
## calculate mean of daily standardized abnormal returns from 2015-01-01 to 2017-12-31
## with E.ON AG as event firm and RWE AG as control firm.
data(demo_returns)
SAR <- sar(event=demo_returns$EON, control=demo_returns$RWE, logret=FALSE)
mean(SAR)

crseEventStudy documentation built on March 18, 2022, 7:20 p.m.