I am conducting an Event study at the moment. I have like over and over again the same steps for the last parts of my study, therefore I would like to insert these steps into a function that I can just apply. The outputs should be presented in a table.

Here is a MRE of my data:

```
df = data.frame(
Date_ = 1:15,
ISIN = rep(c('CH00','CH00', 'GB00'),length.out=15,each=5),
Return = c(0.0175, -0.0734, -0.0734, 0.0457, 0.0208,-0.0780496, 0.0688210, -0.0064685, -0.0997418, -0.0203781, 0.0056672, 0.0028146, 0.0366418, 0.0745412, 0.1555046),
Rating_Change = c(0,0,0,1.9,0,0,0,-0.90, 0, 0, 0, 0, 3.66, 0, 0),
Rating = c('A','A','A','A','A','A','A','A','A', 'A', 'B+','B+','B+','B+','B+'),
event = c(0,1,1,1,1,2,2,2,2,2,1,1,1,1,1)
)
df
```

Then I apply the following function to filter for events, that are non-zero - in this example greater than zero.

For "s" I can define the number of the rating change.

For "w" I can define the window for the events.

```
event_up <- function(df, s, w) {
data_filtered_up <- data.frame()
for (i in 1:nrow(df)) {
if (df[i, 4]>s) {
data_filtered_up[i+w, 1:6] <- filter(df[i+w, 1:6])
data_filtered_up <- na.omit(data_filtered_up)
}
}
return(data_filtered_up)
}
```

Now I have these steps to conduct (over and over again for different rating changes and different event windows):

```
TR_event_u_m3 <- event_up(df, 0, -3:-1) #0 defines that the rating change is greater than 0, "-3:-1" defines the pre-event window (3 to 1 month before event)
TR_CAR_u_m3 <- aggregate(.~TR_event_u_m3$ISIN, data=TR_event_u_m3, mean) #aggregating the ISINs to calculate cumulative abnormal returns
TR_CAR_u_m3 <- TR_CAR_u_m3[,-2][,-2] #deleting non-necessary columns
TR_CAAR_u_m3 <- mean(TR_CAR_u_m3$AR) #calculate the mean of all cumulative average abnormal returns (CAAR) pre event window
TR_CAAR_u_m3_t <- t.test(TR_CAR_u_m3$AR) #make t-test for the CAAR
TR_CAAR_table[1,1] <- TR_CAAR_u_m3 #put CAAR value in table
TR_CAAR_table[2,1] <- TR_CAAR_u_m3_t$statistic #put t-test for CAAR value in table
```

The output shall be in a specific table, where the rownames describe the event windows with always following the corresponding t-test:

```
TR_CAAR_table <- matrix(NA, 8, 8)
colnames(TR_CAAR_table) <- c("GSE_U", "E_U", "S_U", "G_U", "GSE_D", "E_D", "S_D", "G_D")
rownames(TR_CAAR_table) <- c("t= -3:-1","t-test -3:-1","t= -1:+1","t-test -1:+1","t= 0:+1","t-test 0:+1","t= +1:+3","t-test +1:+3")
```

Is there a way to integrate the above steps (aggregation, the deleting of the non-necessary columns, the mean, t-test results and the correct placement in the table) into the above mentioned function(event_up), so that I only have to apply the function and not type the steps over and over again for each event window/rating change?

I tried several attempts but there were always errors occurring and I really don't know why. So any help and support is very much appreciated!!

Thank you so much in advance, Antonia