Instructions Event Study Calculators

Our advanced "Event Study Calculators (AXC)" simplify the use of event studies and the calculation of the associated test statistics. With return, volume, and volatility event studies, there are three types of event studies. We offer a matching set of three calculators: the Abnormal Return Calculator (ARC), the Abnormal Volume Calculator (AVC), and the Abnormal Volatility Calculator (AVyC). All calculators are self-service and function as illustrated in the below workflow picture, Figure 1. We also wrote an article about how to perform a Return Event Study with EventStudyTools - it is hosted on the Medium website, which will read the text aloud in case you prefer voice.

The event study calculators ask you to upload three files that contain all the data and information needed for your event study. Statistical analyses are then performed server-side and you receive the analysis results as attachments to an email. As for your input, you need to provide an 'analysis request file' that specifies your analysis parameters, a 'firm data file' which holds the firm financial data that is required for your analysis, and a 'market data file' that holds the respective capital market data. You should upload the files in CSV file format (standard, not UTF-8) or xls, xlsx. In case of large data, you may ZIP-compress your files. For creating the firm and market data files, you need financial data, which you can retrieve either from a financial data website (e.g., Yahoo!Finance) or from our firm and market data files compilation service (for ARC only).

Access to AXC calculators is provided for a period of one month. You get directed to the payment provider, Stripe, when trying to use ARC, AVC, or AVyC for the first time or can subscribe here. We whitelist your email, which then serves as your unlimited access pass to the AXC calculators (i.e., ARC, AVC, and AVyC). Just enter it for results delivery at any of the event study calculators to receive the analysis results. Our basic ARC is your free option for basic return event study without test statistics and p-values.

Figure 1: Event Study Workflow of EventStudyTools

Your three input files must comply with a certain internal structure so that our event study calculators can process these files. As per your planned event study type (i.e., return, volume, or volatility event study), this structure is different. Please find below tables that describe the required input file structures. Further, please find tables that describe the provided output files.

For the Abnormal Return Calculator (ARC), tables 1 and 2 describe the structures of the in- and output files. The following example ARC input files may help as templates when constructing your own input files. Variants for the CAPM and the Fama-French 3-, 4-, and 5-factor models.
For the Abnormal Volume Calculator (AVC), tables 3 and 4 describe the structures of the in- and output files. The following example AVC input files may help as templates when constructing your own input files.
For the Abnormal Volatility Calculator (AVyC), tables 5 and 6 describe the structures of the in- and output files. The following example AVyC input files may help as templates when constructing your own input files.

Table 1: Structure of Input Files to Trigger ARC
CSV	BENCHMARK MODEL	ITEMS TO BE INCLUDED (TO BE SEPARATED BY A SEMICOLON )
Request File	Same structure for all models	Event ID¹; Firm ID¹; Market ID¹; Event Date²; Grouping Variable³; Start Event Window⁴; End Event Window⁴; End of Estimation Window⁴; Estimation Window Length
Firm Data	Same structure for all models	Firm identifier; Date; Closing price
Market Data	All models but factor models (i.e., CAPM, Fama French 3, 4, and 5 Factor Models)	Market identifier; Date; Closing price
	Fama-French 3-Factor Model	Market identifier; Date; Closing price; Rf⁵; smb; hml
	Fama-French Momentum-4-Factor Model	Market identifier; Date; Closing price; Rf⁵; smb; hml; umd

¹Please use integer values for the event IDs; make sure each line in your request file holds a unique ID. There is no specific format you have to follow for firm and market IDs; just make sure that the identifiers you use in the firm and market data CSVs match the ones you use in the analysis request CSV.
²The dates you provide, however, need to be in a distinct date format. Please use either YYYY-MM-DD (default of Yahoo!Finance) or DD.MM.YYYY (Excel default in many countries). If you should use a date format different from these two, the ARC will prompt an error message in its report.
³For generating the 'average' values in your analysis (i.e., AAR and CAAR values as produced by aARC), you need to specify the 'grouping variable'. If you use only one value in the grouping variable, which is the default case, AXC will calculate the average values across all events in your request file; if you choose more than one value (e.g., 'acquisition' and 'divestiture' in a boundary choice study), AXC will produce average values across the events grouped by these values.
⁴These variables hold figures relative to the event date. ‘Start Event Window’ and ‘End Estimation Window’ are before the event date, therefore, must have a negative sign or be zero. Ranges of allowed values: ‘Start Event Window’: [-50, 0]; ‘End Event Window’: [0, 50]; ‘End Estimation Window’: [-unlimited, -1]; you may choose any (positive) length of the estimation window.
⁵When providing the risk-free return, make sure to give the per day value in decimal format as it applies in the market/country you study. See our page on data sources for guidance on where to retrieve this data.
A file size limit of approx. 5MB per input file applies.

Table 2: Structure of ARC Output Files
APP	OUTPUT FILE	ITEMS REPORTED* (SEPARATED BY A SEMICOLON)
ARC	AR Results	Event ID; ...; AR(-1); AR(0); AR(1); ...; t-value [AR(-1)]; t-value [AR(0)]; t-value [AR(1)]; ...
	AAR Results	Columns: Sub-Sample (as defined by grouping variable); Variables; Days Relative to Events (e.g., -10, -9, ..., 0, 1, ... 10 for a -10 to 10 event window) Lines: N(as number of ARs considered in average); Pos:Neg (as number of ARs that are positive/negative in sub-sample and corresponding day; Patell Z, Generalized Sign Z, Sign Z, Csect T, StdCSect T, Rank Z, Generalized Rank T, Generalized Rank Z, Adjusted Patell Z, Adjusted StdCSect T, Skewness Corrected T, CDA T
	CAR Results	Event ID; Window; CAR Value; CAR t-test
	CAAR Results	Grouping Variable; CAAR Type; CAAR Value; Precision Weighted CAAR Value; ABHAR; pos:neg CAR; Number of CARs considered; CAAR Pattell Z; CAAR t-test; CAAR GSIGN-Test; CAAR BMP; CAAR GRANK T; CAAR adjusted Patell; CAAR adjusted BMP; CAAR GRANK Z; CAAR skewness adjusted T; ABHAR T; ABHAR skewness adjusted T
	Analysis Report	Event ID; Firm; Reference Market; Event Date; Analysis Report; Estimation Window Length; End of Estimation Window; First Date Estimation Window; Last Date Estimation Window; Actual Stock Return; Actual Market Return; Alpha; Beta; Residual Standard Deviation; Expected Market Return

* test statistics are accompanied by corresponding p-values

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Table 3: AVC Input Files
CSV	ITEMS TO BE INCLUDED (SEPARATED BY A SEMICOLON )
Request File	Event ID; Firm ID; Market ID; Event Date; Grouping Variable²; Start Event Window³, End Event Window³, End of Estimation Window³, Estimation Window Length
Firm Data	Firm identifier; Date; number of shares traded; outstanding share of firm
Market Data	Market identifier; Date; mean of log percentage of trading volume of the index

Table 4: AVC Output Files
APP	OUTPUT FILE	ITEMS REPORTED (SEPARATED BY A SEMICOLON)
AVC	AV Results	Event ID; ...; AR(-1); AR(0); AR(1); ...; t-value [AR(-1)]; t-value [AR(0)]; t-value [AR(1)]; ...
	AAV Results	Grouping variable; ...; AAV(-1); AAV(0); AAV(1); ... N(Grouping variable, AAV(i)); ...; N(AAV(-1)); N(AAV(0)); N(AAV(1)); ... Pos:Neg(Grouping variable, AAV(i)); ... ; Pos:Neg(Grouping variable, AAV(-1)); Pos:Neg(Grouping variable, AAV(0)); Pos:Neg(Grouping variable, AAV(1)); ... + per AAV(i): Patell Z, Generalized Sign Z, Csect T, StdCSect Z, Rank Z, Generalized Rank T, Adjusted Patell Z, Adjusted StdCSect Z, Generalized Rank Z, Skewness Corrected T
	CAV Results	Event ID; Window; CAV Value; BHAV Value; CAV t-test
	CAAV Results	Grouping Variable; CAAV Type; CAAV Value; Precision Weighted CAAV Value; ABHAR; pos:neg CAV; Number of CAVs considered; Patell Z; Csect T; Generalized Sign Z; StdCSect Z; Rank Z; Generalized Rank T; Adjusted Patell Z; AdjustedÂ StdCSect Z; Generalized Rank T; Skewness Corrected T; ABHAR Csect T; ABHAR Skewness Corrected T
	Analysis Report	Event ID; Firm; Reference Market; Event Date; Analysis Report; Estimation Window Length; End of Estimation Window; First Date Estimation Window; Last Date Estimation Window; Actual Stock Volume; Actual Market volume; Alpha; Beta Residual Standard Deviation; Expected Market Return; First-order Autocorellation

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Table 5: AVyC Input Files
CSV	ITEMS TO BE INCLUDED (SEPARATED BY A SEMICOLON )
Request File	Event ID; Firm ID; Market ID; Event Date; Grouping Variable²; Start Event Window³, End Event Window³, End of Estimation Window³, Estimation Window Length
Firm Data	Firm identifier; Date; Closing price
Market Data	Market identifier; Date; Closing price

Table 6: AVyC Output Files
APP	OUTPUT FILE	ITEMS REPORTED (SEPARATED BY A SEMICOLON)
AVC	AVy Results
	AVy Results	Event ID; ...; AVy(-1); AVy(0); AVy(1); ...;
	AAVy Results	Grouping variable; ...; AAVy(-1); AAVy(0); AAVy(1); ... N(Grouping variable, AAV(i)); ...; N(AAV(-1)); N(AAV(0)); N(AAV(1)); ... Pos:Neg(Grouping variable, AAV(i)); ... ; Pos:Neg(Grouping variable, AAV(-1)); Pos:Neg(Grouping variable, AAV(0)); Pos:Neg(Grouping variable, AAV(1)); ... + per AAV(i): Cross-Sectional-Vy-t-Test, Cross-Sectional-Corrected-Vy-t-Test, Cross-Sectional-AR-t-Test, Cross-Sectional-Corrected-AR-t-Test
	Analysis Report	Event ID; Firm ID; Reference Market; Event Date; Analysis Report; Estimation Window Length; End of Estimation Window; First Date Estimation Window; Last Date Estimation Window; Alpha; p-value; Beta; p-value; Gamma; p-value; Delta; p-value; H_i; preLambda; postLambda; Abnormal Return on Event Day; Residual Standard Deviation; Expected Stock Return; Autocorellation

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