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Have EST-ARC results been validated?

Written by EST Admin
Updated 1 week ago

Good question and surely something you should have in mind when choosing a solution that produces the empirical results for your research paper.

We are certain that our ARC's results are correct. Why? For two reasons: First, our algorithms and the inherent test statistics are coded by a renowned statistics professor. Second, we validate our results by benchmarking them against alternative software solutions and published research papers.

Which EST-ARC results have been validated successfully?

For different variables/results (e.g., individual test statistics), there are different pieces of evidence - from differing sources. For example, the abnormal returns at AR- and CAR-levels can be verified against an Excel calculation, whereas the test statistics can only be compared against alternative event study software solutions and published research papers. We constantly expand our validation and search for papers (incl. data) or alternative software that contain or produce benchmark values for the few variables/results that have not been able to validate yet. 

Fortunately, we have been able to benchmark most of our statistical results as of today already. The tables below provide an overview of the current state of validation of EventStudyTools' (EST) outputs.

Validation of expected return models

Test statistics can only match their benchmark values if also the underlying abnormal returns match. We thus first compared whether our algorithms produce AR-. CAR-. AAR-. and CAAR-values that are identical to those benchmarks that are created by alternative software solutions or are available in published research papers. 

The below table shows the validation status of the EST expected return models:

Expected return model Model validated?
Market Model Yes, EST results match benchmark(s)
Market Adjusted Yes, EST results match benchmark(s)
Comparison Period Mean Adjusted Yes, EST results match benchmark(s)
CAPM Yes, EST results match benchmark(s)
Fama-French 3 Factor Model No benchmark has been found yet
Fama-French-Momentum 4 Factor Model No benchmark has been found yet
Fama-French 5 Factor Model No benchmark has been found yet

Validation of test statistics and their p-values

The algorithms of the individual test statistics apply across the different expected factor-based return models. This means for the benchmarking that the algorithms can be considered as correctly designed once their outputs were found to match the benchmark(s) in one of the expected return models. To be sure, however, we programmed an internal service that compared all EST test statistics results per each model (except for the Fama French models) with the corresponding benchmark(s). 

The below table shows the validation status of our test statistics (incl. p-values):

Level(s) EST variable  Variable calculation validated?
AR T-Value No benchmark has been found yet, but this is a simple t-value calculation with little room for error
CAR T-Value No benchmark has been found yet, but this is a simple t-value calculation with little room for error
AAR, CAAR Cross-Sectional T Yes, EST results match benchmark(s)
AAR, CAAR CDA T Yes, EST results match benchmark(s)
AAR, CAAR Patell Z Yes, EST results match benchmark(s)
AAR, CAAR Adjusted Patell Z Yes, EST results match benchmark(s)
AAR, CAAR Stand. Cross-Section. T Yes, EST results match benchmark(s)
AAR, CAAR Adj. StdCSect T Yes, EST results match benchmark(s)
AAR, CAAR Skewness Corrected T Yes, EST results match benchmark(s)
AAR, CAAR Rank Z Yes, EST results match benchmark(s)
AAR, CAAR Generalized Rank Z Yes, EST results match benchmark(s)
AAR, CAAR Generalized Rank T Yes, EST results match benchmark(s)
AAR, CAAR Sign Z Yes, EST results match benchmark(s)
AAR Wilcoxon Yes, EST results match benchmark(s)

Please further note:

  • All validation was performed through a 1:1 comparison of results that were produced by EventStudyTools and the benchmark source. In case we compared against an alternative software, we used the EST ARC example dataset as a source for both the EST algorithms and the alternative software benchmark.
  • We will update this page as we progress in our search for benchmarks on the variables or expected return models that are not yet covered
  • In case you have questions on the benchmarking or want the data of a certain variable and its benchmark(s), please reach out to us.
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