Event Group | Event Window | CAAR | Test |
|---|
t-test | CDA | Patell | PatellADJ | Corrado- Cowan | GenSign | Wilcox |
|---|
High Exposure (N = 12) | AAR[0] | 3.632 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.01 | 0.04 |
[− 1;1] | 7.966 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.06 | 0.02 |
[− 2;2] | 5.327 | 0.02 | 0.00 | 0.00 | 0.00 | 0.37 | 0.45 | 0.55 |
[− 5;5] | 4.958 | 0.14 | 0.08 | 0.00 | 0.00 | 0.24 | 0.18 | 0.65 |
[0;1] | 5.091 | 0.00 | 0.00 | 0.00 | 0.00 | 0.02 | 0.45 | 0.09 |
[0;3] | 4.825 | 0.02 | 0.00 | 0.00 | 0.00 | 0.16 | 0.45 | 0.37 |
Medium Exposure (N = 13) | AAR[0] | − 1.547 | 0.13 | 0.10 | 0.09 | 0.08 | 0.04 | 0.41 | 0.10 |
[− 1;1] | − 0.1 | 0.95 | 0.95 | 0.94 | 0.94 | 0.90 | 0.41 | 0.82 |
[− 2;2] | − 0.74 | 0.74 | 0.72 | 0.47 | 0.45 | 1.00 | 0.40 | 0.96 |
[− 5;5] | 0.009 | 1.00 | 1.00 | 0.43 | 0.41 | 0.60 | 0.78 | 0.53 |
[0;1] | − 0.236 | 0.87 | 0.86 | 0.47 | 0.45 | 0.72 | 0.41 | 0.97 |
[0;3] | − 1.358 | 0.50 | 0.47 | 0.22 | 0.20 | 0.41 | 0.41 | 0.53 |
Low Exposure (N = 10) | AAR[0] | − 1.567 | 0.48 | 0.47 | 0.57 | 0.57 | 0.21 | 0.58 | 0.14 |
[− 1;1] | − 5.151 | 0.18 | 0.17 | 0.00 | 0.00 | 0.06 | 0.23 | 0.07 |
[− 2;2] | − 4.136 | 0.41 | 0.39 | 0.02 | 0.02 | 0.18 | 0.07 | 0.29 |
[− 5;5] | − 5.12 | 0.49 | 0.47 | 0.16 | 0.16 | 0.25 | 0.58 | 0.28 |
[0;1] | − 2.378 | 0.45 | 0.44 | 0.35 | 0.35 | 0.18 | 0.23 | 0.14 |
[0;3] | − 2.599 | 0.56 | 0.55 | 0.19 | 0.19 | 0.23 | 0.58 | 0.33 |
- This table shows the p-values of each hypothesis test – t-test, Crude Dependence Adjustment test (CDA), Patell test, Adjusted Pattel test, Corrado rank test, Generalized Sign test, and Wilcoxon signed-ranks test for different groups of cryptocurrency exposure. We highlight in bold the p values lower or equal to 0.10. The degree of cryptocurrency exposure is assessed using data from regulatory fillings (e.g., 10-Q, 8-K), firms' announcements, and media posts. For cryptocurrency direct acquisitions (BTC or ETH), we assign high (low) exposure to events at the top (bottom) tercile of the ratio between the USD value of cryptocurrency acquisitions and the USD value of total assets. For indirect acquisitions/investments and acceptance as means of payment, we qualitatively analyze the information content of each event and use the following sorting criteria. Plans to accept cryptocurrency (not actual acceptance) and indirect acceptance of crypto as means of payment (e.g., only through gift cards) are classified as low cryptocurrency exposure events. Conversely, effective acceptance of cryptocurrency by a firm pioneer in its industry and worldwide, economically relevant M&A or partnerships are classified as high exposure. Finally, we categorize medium exposure as the effective acceptance of crypto by a non-pioneer firm in its industry and M&A or partnerships not worldwide noticed
