Investor Reactions to Crypto Token Regulation

Figures & data

Table 1. Event and sample selection

Panel A: Event selection
		N
All items		1009
– Non-news items		−589
– Non-regulation news items		−204
= All regulation news items		216
– Regulation news items from countries without a top 100 crypto-exchange		−54
– Non-transparency regulation news items		−128
– Non-securities regulation news items		−19
= Transparency regulation news events		15
Panel B: Sample selection
	Tokens	N
All cryptocurrencies on Coinmarketcap, Apr. 28, 2013–Sep. 1, 2018	1886	849,152
– No market data on any event date (keep only event days)	−100	−831,827
– No market cap., market cap. < US $10,000, and/or price < US $0.001	−393	−4028
– Extreme CAR due to data error	−0	−2
– No ICOBench data, not a utility token	−938	−9594
= ‘Market Reaction’ sample (Table 2)	455	3701
– No Expert Rating data	−140	−1283
= ‘Role of Rating’ sample (Tables 6 and 7)	315	2418
‘Role of Rating’ sample	315	2418
– No disclosure data (any of the variables missing)	−63	−671
= ‘Role of Disclosure’ sample (Table 8)	252	1747
‘Role of Rating’ sample	315	2418
– No exchange data (any of the variables missing)	−86	−647
= ‘Role of Exchanges’ sample (Table 9)	229	1771

Note: This Table presents an overview of the events and sample selection procedures. Panel A reconciles the number of all regulatory news items identified on Cointelegraph with those included in our event study. We exclude news items that do not represent news, are unrelated to securities regulation focused on enhancing transparency, or are news items from countries that are minor players in the cryptocurrency market (based on the existence of a large cryptocurrency exchange). Panel B shows how the four different test samples reconcile with all listed cryptocurrencies on Coinmarketcap. We present the sample selection in number of unique crypto tokens (‘Tokens’) and crypto token trading date observations (‘N’).

Table 2. Overview of news events and market reactions

				Market reaction
Event	Date	Event headline	Country	# Tokens	CAR	t-stat.
1	Jun. 13, 2017	‘SEC is Still Eyeing to Regulate the ICO Market’	US	40	−0.074${}^{\ast \ast \ast }$	−3.80
2	Jul. 25, 2017	‘SEC Deals Blow To ICOs: DAO Tokens Are Securities, Subject to Securities Laws’	US	71	−0.154${}^{\ast \ast \ast }$	−13.00
3	Aug. 1, 2017	‘Singapore Clarifies ICO Token Regulation, Follows US’	Singapore	73	0.041${}^{\ast \ast \ast }$	2.52
4	Aug. 24, 2017	‘Canada Looking To Classify Digital Currencies As Securities’	Canada	88	0.029	1.41
5	Sep. 7, 2017	‘Digital Currencies, ICO-Based Tokens Are Securities, Says Kiwi Finance Regulator’	New Zealand	93	−0.096${}^{\ast \ast \ast }$	−7.05
6	Feb. 11, 2018	‘Gibraltar To Introduce “World's First” ICO Regulations’	Gibraltar	246	−0.007	−0.58
7	Feb. 14, 2018	‘Canadian Stock Exchange Launches “Fully-Regulated” Token Platform, “Unlike” ICOs’	Canada	249	0.116${}^{\ast \ast \ast }$	10.90
8	Feb. 19, 2018	‘US: Republican, Democrat Officials Calling For Crypto Regulation In Rare Show Of Unity’	US	255	−0.057${}^{\ast \ast \ast }$	−5.45
9	Mar. 7, 2018	‘US: Cryptocurrency Trading Platforms Must Be Registered With SEC’	US	284	−0.187${}^{\ast \ast \ast }$	−21.77
10	Mar. 13, 2018	‘Thailand's SEC To Release Crypto Market Regulatory Framework In March’	Thailand	295	−0.125${}^{\ast \ast \ast }$	−12.74
11	May 14, 2018	‘Thailand: Legal Framework For Cryptocurrencies Comes Into Force’	Thailand	361	−0.020${}^{\ast \ast \ast }$	−2.56
12	May 21, 2018	‘Thai SEC Holds Focus Group to Clarify New Crypto, ICO Regulations’	Thailand	371	−0.087${}^{\ast \ast \ast }$	−11.73
13	Jul. 5, 2018	‘Thai Regulator Confirms July Start Date for Regulated ICOs’	Thailand	409	0.002	0.36
14	Jul. 20, 2018	‘Ukrainian Financial Stability Council Supports Regulatory Concept for Cryptocurrencies’	Ukraine	421	−0.035${}^{\ast \ast \ast }$	−5.32
15	Aug. 10, 2018	‘ICOs Can “Prove Their Legitimacy” Under New Crowdfunding Rules, Says EU Lawmaker’	Global	445	−0.104${}^{\ast \ast \ast }$	−10.31
		Mean market reaction		3701	−0.052${}^{\ast \ast \ast }$	−2.56

Note: This Table presents an overview of the 15 transparency regulation news events between January 1st, 2017 and December 31st, 2018, which are the focus of this study, and the market reaction to each event and on average across all events. For the market tests, we cluster standard errors at the event- and crypto token-level. ${}^{\ast }$, ${}^{\ast \ast }$, and ${}^{\ast \ast \ast }$ denote statistical significance at the two-tailed 10, 5, and 1% level, respectively.

Table 3. Robustness of market reaction tests

Panel A: Univariate results using different samples
		Exchange-country sample			Traditional media covered sample
Event	Date	# Tokens	CAR	t-stat.	# Tokens	CAR	t-stat.
1	Jun. 13, 2017	32	−0.067${}^{\ast \ast \ast }$	−2.95	40	−0.074${}^{\ast \ast \ast }$	−3.80
2	Jul. 25, 2017	59	−0.155${}^{\ast \ast \ast }$	−11.22	71	−0.154${}^{\ast \ast \ast }$	−13.00
3	Aug. 1, 2017	27	0.046${}^{\ast \ast \ast }$	3.08	73	0.041${}^{\ast \ast \ast }$	2.52
4	Aug. 24, 2017	12	0.029	1.33
5	Sep. 7, 2017				93	−0.096${}^{\ast \ast \ast }$	−7.05
6	Feb. 11, 2018				246	−0.007	−0.58
7	Feb. 14, 2018	17	0.124${}^{\ast \ast \ast }$	4.12	249	0.116${}^{\ast \ast \ast }$	10.90
8	Feb. 19, 2018	207	−0.054${}^{\ast \ast \ast }$	−4.43
9	Mar. 7, 2018	235	−0.185${}^{\ast \ast \ast }$	−19.91	284	−0.187${}^{\ast \ast \ast }$	−21.77
10	Mar. 13, 2018	13	−0.132${}^{\ast \ast \ast }$	−9.11	295	−0.125${}^{\ast \ast \ast }$	−12.74
11	May 14, 2018	15	−0.029	−1.33	361	−0.020${}^{\ast \ast \ast }$	−2.56
12	May 21, 2018	15	−0.141${}^{\ast \ast \ast }$	−13.22	371	−0.087${}^{\ast \ast \ast }$	−11.73
13	Jul. 5, 2018	15	0.006	0.40	409	0.002	0.36
14	Jul. 20, 2018				421	−0.035${}^{\ast \ast \ast }$	−5.32
15	Aug. 10, 2018	367	−0.105${}^{\ast \ast \ast }$	−9.10
	Mean market reaction	1014	−0.103${}^{\ast \ast \ast }$	−4.39	2752	−0.059${}^{\ast \ast \ast }$	−2.79
Panel B: Regression results
		Daily return
		(1)	(2)
	Constant (Average Daily Return)	0.007${}^{\ast \ast \ast }$	0.007${}^{\ast \ast \ast }$
		(90.08)	(91.14)
	Event	−0.025${}^{\ast \ast \ast }$
		(−15.02)
Event Number	Date
1	Jun. 13, 2017		0.070${}^{\ast \ast \ast }$
			(3.34)
2	Jul. 25, 2017		−0.137${}^{\ast \ast \ast }$
			(−10.95)
3	Aug. 1, 2017		0.046${}^{\ast \ast \ast }$
			(3.69)
4	Aug. 24, 2017		0.027${}^{\ast \ast }$
			(2.11)
5	Sep. 7, 2017		0.006
			(0.43)
6	Feb. 11, 2018		−0.064${}^{\ast \ast \ast }$
			(−11.15)
7	Feb. 14, 2018		0.097${}^{\ast \ast \ast }$
			(13.95)
8	Feb. 19, 2018		0.029${}^{\ast \ast \ast }$
			(5.13)
9	Mar. 7, 2018		−0.108${}^{\ast \ast \ast }$
			(−18.75)
10	Mar. 13, 2018		−0.011${}^{\ast \ast }$
			(−2.19)
11	May 14, 2018		−0.010${}^{\ast \ast }$
			(−2.02)
12	May 21, 2018		−0.027${}^{\ast \ast \ast }$
			(−5.96)
13	Jul. 5, 2018		−0.013${}^{\ast \ast \ast }$
			(−2.90)
14	Jul. 20, 2018		−0.056${}^{\ast \ast \ast }$
			(−11.24)
15	Aug. 10, 2018		−0.077${}^{\ast \ast \ast }$
			(−15.04)
	N	80,839	80,839
	No. of Crypto Tokens	455	455
	${\mathrm{R}}^2$	0.016	0.016
	Crypto Token FE	Yes	Yes

Note: This Table presents the robustness results of the market reaction tests. Panel A presents the market reaction to each event and on average across all events using two different samples. The ‘Exchange-Country Sample’ limits the sample of crypto tokens per news event to those that are traded on an exchange in the specific country of the regulation news event. The ‘Traditional Media Covered Sample’ limits the sample to those events that are also covered by traditional, international media outlets covered by LexisNexis (e.g., Bloomberg, Reuters) Panel B regresses the daily crypto token return for the entire sample period on an event dummy equal to one if the date corresponds to a transparency regulation event, and zero otherwise, and on an indicator for each date. For the market tests, we cluster standard errors at the event- and crypto token-level. For the regression, we include crypto token fixed effects and cluster standard errors at the crypto token-level. ${}^{\ast }$, ${}^{\ast \ast }$, and ${}^{\ast \ast \ast }$ denote statistical significance at the two-tailed 10, 5, and 1% level, respectively.

Table 4. Descriptive statistics

Variable	N	Mean	S.D.	Min.	Q1	Med.	Q3	Max.
CAR	2418	−0.052	0.177	−0.790	−0.142	−0.064	0.008	2.284
Size	2418	16.563	1.877	11.595	15.365	16.587	17.783	21.317
Supply	2418	18.182	2.138	11.528	16.856	18.383	19.674	23.627
Total Rating	2418	3.242	0.772	0.800	2.900	3.400	3.800	4.700
Benchy Rating	2418	3.053	0.743	0.700	2.800	3.200	3.500	4.800
Expert Rating	2418	3.630	1.054	1.000	3.167	3.933	4.367	5.000
Benchy rating components
Team Score	2418	0.445	0.240	0.000	0.500	0.500	0.500	1.000
ICO Info. Score	2418	0.951	0.116	0.170	1.000	1.000	1.000	1.000
Product Info. Score	2418	0.673	0.213	0.000	0.600	0.800	0.800	1.000
Social Media Score	2418	0.522	0.206	0.000	0.380	0.530	0.690	0.940
Expert rating components
Team Rating	2418	3.635	1.154	1.000	3.000	4.000	4.400	5.000
Vision Rating	2418	3.765	1.090	1.000	3.200	4.000	4.500	5.000
Product Rating	2418	3.489	1.108	1.000	3.000	3.700	4.200	5.000
Disclosure Variables
Website Size (unlogged)	1747	183,136	387,068	1655	44,302	100,642	203,160	8,098,158
Website Size	1747	11.376	1.292	7.631	10.764	11.584	12.236	14.340
GitHub	1747	0.652	0.476	0.000	0.000	1.000	1.000	1.000
Total GitHub Changes	1747	5.117	5.050	0.000	0.000	4.942	9.650	14.474
Total Tweets	1747	5.744	1.183	0.693	5.252	5.814	6.540	7.875
Total Replies	1747	4.177	1.484	0.000	3.466	4.357	5.124	6.917
Exchange variables
Exchange Volume	1771	20.999	2.409	14.041	20.955	21.810	22.375	23.987
Exchange Liquidity	1771	5.937	0.671	1.099	5.916	6.055	6.236	6.488
Exchange Visits	1771	13.556	1.611	7.563	12.647	13.722	14.647	16.595
Exchange #Cryptos	1771	5.528	0.731	2.303	5.388	5.614	5.943	6.721

Note: This Table presents the descriptive statistics for the variables used in the cross-sectional analyzes. The variables are defined in the Appendix A1.

Table 5. Correlation matrix

		1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	19	20	21	22
1	CAR		−0.04	−0.07${}^{\ast }$	0.06${}^{\ast }$	0.08${}^{\ast }$	−0.01	0.04	0.02	0.05${}^{\ast }$	0.06${}^{\ast }$	0.01	−0.02	−0.01	−0.03	−0.01	−0.02	0.01	0.05	0.03	−0.03	0.01	0.00
2	Size	−0.06${}^{\ast }$		0.33${}^{\ast }$	0.11${}^{\ast }$	0.03	0.37${}^{\ast }$	−0.12${}^{\ast }$	0.01	−0.15${}^{\ast }$	0.22${}^{\ast }$	0.36${}^{\ast }$	0.35${}^{\ast }$	0.29${}^{\ast }$	0.47${}^{\ast }$	0.18${}^{\ast }$	0.52${}^{\ast }$	−0.07${}^{\ast }$	−0.05	0.06${}^{\ast }$	0.12${}^{\ast }$	0.15${}^{\ast }$	0.30${}^{\ast }$
3	Supply	−0.07${}^{\ast }$	0.42${}^{\ast }$		0.10${}^{\ast }$	0.09${}^{\ast }$	0.06${}^{\ast }$	0.05	−0.07${}^{\ast }$	0.08${}^{\ast }$	0.08${}^{\ast }$	0.09${}^{\ast }$	0.00	0.06${}^{\ast }$	0.19${}^{\ast }$	0.18${}^{\ast }$	0.19${}^{\ast }$	0.09${}^{\ast }$	0.17${}^{\ast }$	0.11${}^{\ast }$	0.11${}^{\ast }$	0.04	0.11${}^{\ast }$
4	Total Rating	0.01	0.16${}^{\ast }$	0.27${}^{\ast }$		0.77${}^{\ast }$	0.43${}^{\ast }$	0.49${}^{\ast }$	0.31${}^{\ast }$	0.52${}^{\ast }$	0.61${}^{\ast }$	0.42${}^{\ast }$	0.35${}^{\ast }$	0.39${}^{\ast }$	0.16${}^{\ast }$	0.05	0.14${}^{\ast }$	0.21${}^{\ast }$	0.19${}^{\ast }$	0.31${}^{\ast }$	0.01	0.12${}^{\ast }$	0.04
5	Benchy Rating	0.01	0.11${}^{\ast }$	0.21${}^{\ast }$	0.91${}^{\ast }$		0.03	0.63${}^{\ast }$	0.35${}^{\ast }$	0.61${}^{\ast }$	0.79${}^{\ast }$	0.07${}^{\ast }$	0.00	0.01	0.05	0.00	0.02	0.13${}^{\ast }$	0.17${}^{\ast }$	0.37${}^{\ast }$	−0.08${}^{\ast }$	0.13${}^{\ast }$	0.00
6	Expert Rating	0.00	0.42${}^{\ast }$	0.33${}^{\ast }$	0.73${}^{\ast }$	0.48${}^{\ast }$		0.05	0.03	−0.05	0.10${}^{\ast }$	0.91${}^{\ast }$	0.91${}^{\ast }$	0.93${}^{\ast }$	0.35${}^{\ast }$	0.15${}^{\ast }$	0.36${}^{\ast }$	0.18${}^{\ast }$	0.04	−0.06${}^{\ast }$	0.14${}^{\ast }$	0.05	0.13${}^{\ast }$
7	Team Score	−0.02	0.07${}^{\ast }$	0.13${}^{\ast }$	0.59${}^{\ast }$	0.67${}^{\ast }$	0.32${}^{\ast }$		0.10${}^{\ast }$	0.39${}^{\ast }$	0.26${}^{\ast }$	0.09${}^{\ast }$	0.07${}^{\ast }$	0.00	−0.06${}^{\ast }$	−0.06${}^{\ast }$	−0.05${}^{\ast }$	0.07${}^{\ast }$	0.11${}^{\ast }$	0.14${}^{\ast }$	−0.01	0.01	−0.12${}^{\ast }$
8	ICO Info. Score	0.01	−0.23${}^{\ast }$	−0.07${}^{\ast }$	0.32${}^{\ast }$	0.31${}^{\ast }$	0.11${}^{\ast }$	0.06${}^{\ast }$		0.21${}^{\ast }$	0.18${}^{\ast }$	−0.03	0.02	0.05	−0.05	0.02	−0.11${}^{\ast }$	0.07${}^{\ast }$	0.10${}^{\ast }$	0.09${}^{\ast }$	−0.12${}^{\ast }$	−0.02	−0.09${}^{\ast }$
9	Product Info. Score	0.00	−0.04${}^{\ast }$	0.16${}^{\ast }$	0.64${}^{\ast }$	0.69${}^{\ast }$	0.37${}^{\ast }$	0.35${}^{\ast }$	0.14${}^{\ast }$		0.30${}^{\ast }$	0.02	−0.11${}^{\ast }$	−0.07${}^{\ast }$	−0.04	−0.02	−0.08${}^{\ast }$	0.13${}^{\ast }$	0.20${}^{\ast }$	0.18${}^{\ast }$	−0.08${}^{\ast }$	−0.02	−0.16${}^{\ast }$
10	Social Media Score	0.02	0.25${}^{\ast }$	0.21${}^{\ast }$	0.71${}^{\ast }$	0.78${}^{\ast }$	0.40${}^{\ast }$	0.30${}^{\ast }$	0.07${}^{\ast }$	0.33${}^{\ast }$		0.12${}^{\ast }$	0.07${}^{\ast }$	0.10${}^{\ast }$	0.16${}^{\ast }$	0.04	0.15${}^{\ast }$	0.10${}^{\ast }$	0.11${}^{\ast }$	0.36${}^{\ast }$	0.02	0.19${}^{\ast }$	0.13${}^{\ast }$
11	Team Rating	0.00	0.38${}^{\ast }$	0.32${}^{\ast }$	0.73${}^{\ast }$	0.51${}^{\ast }$	0.94${}^{\ast }$	0.34${}^{\ast }$	0.14${}^{\ast }$	0.39${}^{\ast }$	0.41${}^{\ast }$		0.78${}^{\ast }$	0.74${}^{\ast }$	0.42${}^{\ast }$	0.23${}^{\ast }$	0.40${}^{\ast }$	0.21${}^{\ast }$	0.06${}^{\ast }$	−0.02	0.13${}^{\ast }$	0.07${}^{\ast }$	0.12${}^{\ast }$
12	Vision Rating	−0.01	0.41${}^{\ast }$	0.32${}^{\ast }$	0.70${}^{\ast }$	0.46${}^{\ast }$	0.95${}^{\ast }$	0.32${}^{\ast }$	0.05${}^{\ast }$	0.35${}^{\ast }$	0.38${}^{\ast }$	0.84${}^{\ast }$		0.79${}^{\ast }$	0.27${}^{\ast }$	0.09${}^{\ast }$	0.31${}^{\ast }$	0.11${}^{\ast }$	0.00	−0.05	0.14${}^{\ast }$	0.05	0.13${}^{\ast }$
13	Product Rating	0.00	0.38${}^{\ast }$	0.30${}^{\ast }$	0.65${}^{\ast }$	0.39${}^{\ast }$	0.94${}^{\ast }$	0.24${}^{\ast }$	0.12${}^{\ast }$	0.29${}^{\ast }$	0.34${}^{\ast }$	0.81${}^{\ast }$	0.85${}^{\ast }$		0.28${}^{\ast }$	0.09${}^{\ast }$	0.28${}^{\ast }$	0.14${}^{\ast }$	0.04	−0.09${}^{\ast }$	0.13${}^{\ast }$	0.03	0.12${}^{\ast }$
14	Exchange Volume	−0.07${}^{\ast }$	0.47${}^{\ast }$	0.25${}^{\ast }$	0.20${}^{\ast }$	0.16${}^{\ast }$	0.27${}^{\ast }$	0.03	−0.04${}^{\ast }$	0.07${}^{\ast }$	0.23${}^{\ast }$	0.33${}^{\ast }$	0.20${}^{\ast }$	0.23${}^{\ast }$		0.69${}^{\ast }$	0.83${}^{\ast }$	0.39${}^{\ast }$	0.00	0.10${}^{\ast }$	0.10${}^{\ast }$	0.16${}^{\ast }$	0.22${}^{\ast }$
15	Exchange Liquidity	0.02	0.20${}^{\ast }$	0.14${}^{\ast }$	0.07${}^{\ast }$	0.00	0.17${}^{\ast }$	−0.06${}^{\ast }$	−0.08${}^{\ast }$	−0.02	0.07${}^{\ast }$	0.18${}^{\ast }$	0.14${}^{\ast }$	0.17${}^{\ast }$	0.46${}^{\ast }$		0.54${}^{\ast }$	0.51${}^{\ast }$	−0.02	−0.02	0.10${}^{\ast }$	0.14${}^{\ast }$	0.15${}^{\ast }$
16	Exchange Visits	−0.03	0.44${}^{\ast }$	0.26${}^{\ast }$	0.12${}^{\ast }$	0.05${}^{\ast }$	0.27${}^{\ast }$	0.00	−0.12${}^{\ast }$	−0.04${}^{\ast }$	0.16${}^{\ast }$	0.31${}^{\ast }$	0.22${}^{\ast }$	0.22${}^{\ast }$	0.66${}^{\ast }$	0.46${}^{\ast }$		0.34${}^{\ast }$	−0.02	0.08${}^{\ast }$	0.13${}^{\ast }$	0.18${}^{\ast }$	0.23${}^{\ast }$
17	Exchange #Cryptos	−0.03	0.11${}^{\ast }$	0.14${}^{\ast }$	0.20${}^{\ast }$	0.18${}^{\ast }$	0.17${}^{\ast }$	0.11${}^{\ast }$	0.05${}^{\ast }$	0.16${}^{\ast }$	0.13${}^{\ast }$	0.25${}^{\ast }$	0.07${}^{\ast }$	0.16${}^{\ast }$	0.55${}^{\ast }$	0.45${}^{\ast }$	0.57${}^{\ast }$		0.03	0.15${}^{\ast }$	−0.02	0.06${}^{\ast }$	0.04
18	Website Size	0.04	0.03	0.15${}^{\ast }$	0.23${}^{\ast }$	0.20${}^{\ast }$	0.09${}^{\ast }$	0.12${}^{\ast }$	0.08${}^{\ast }$	0.24${}^{\ast }$	0.12${}^{\ast }$	0.10${}^{\ast }$	0.11${}^{\ast }$	0.06${}^{\ast }$	0.00	0.08${}^{\ast }$	0.06${}^{\ast }$	0.06${}^{\ast }$		0.04	0.02	0.09${}^{\ast }$	0.02
19	GitHub	0.01	0.07${}^{\ast }$	0.09${}^{\ast }$	0.38${}^{\ast }$	0.40${}^{\ast }$	0.11${}^{\ast }$	0.17${}^{\ast }$	0.07${}^{\ast }$	0.21${}^{\ast }$	0.45${}^{\ast }$	0.13${}^{\ast }$	0.14${}^{\ast }$	0.05${}^{\ast }$	0.15${}^{\ast }$	0.01	0.17${}^{\ast }$	0.12${}^{\ast }$	0.04		0.00	0.04	0.01
20	Total GitHub Changes	−0.02	0.16${}^{\ast }$	0.13${}^{\ast }$	0.07${}^{\ast }$	0.01	0.21${}^{\ast }$	0.04${}^{\ast }$	−0.14${}^{\ast }$	−0.02	0.06${}^{\ast }$	0.21${}^{\ast }$	0.21${}^{\ast }$	0.17${}^{\ast }$	0.09${}^{\ast }$	−0.05${}^{\ast }$	0.13${}^{\ast }$	−0.05${}^{\ast }$	0.03	0.09${}^{\ast }$		0.01	−0.02
21	Total Tweets	0.01	0.24${}^{\ast }$	0.19${}^{\ast }$	0.21${}^{\ast }$	0.22${}^{\ast }$	0.22${}^{\ast }$	0.15${}^{\ast }$	0.02	0.02	0.27${}^{\ast }$	0.23${}^{\ast }$	0.20${}^{\ast }$	0.19${}^{\ast }$	0.09${}^{\ast }$	0.11${}^{\ast }$	0.05${}^{\ast }$	−0.01	0.12${}^{\ast }$	0.02	0.01		0.75${}^{\ast }$
22	Total Replies	−0.01	0.30${}^{\ast }$	0.22${}^{\ast }$	0.10${}^{\ast }$	0.10${}^{\ast }$	0.18${}^{\ast }$	0.09${}^{\ast }$	0.01	−0.07${}^{\ast }$	0.16${}^{\ast }$	0.19${}^{\ast }$	0.14${}^{\ast }$	0.18${}^{\ast }$	0.15${}^{\ast }$	0.14${}^{\ast }$	0.15${}^{\ast }$	0.06${}^{\ast }$	0.03	−0.02	0.00	0.79${}^{\ast }$

Note: This Table presents the correlation matrix for the variables used in the cross-sectional analyzes. Pearson (Spearman) correlations are below (above) the diagonal. The variables are defined in the Appendix A1. ${}^{\ast }$ denotes statistical significance at the two-tailed 5% level.

Table 6. Role of Total Rating and Benchy Rating

		CAR
	Prediction	(1)	(2)	(3)
Total Rating	+	0.017${}^{\ast \ast }$
		(2.28)
Benchy Rating	+		0.012${}^{\ast \ast }$
			(2.24)
Team Info. Score	+			0.004
				(0.36)
ICO Info. Score	+			−0.008
				(−0.23)
Product Info. Score	+			−0.008
				(−0.24)
Social Media Score	+			0.061${}^{\ast \ast \ast }$
				(4.47)
Size	?	−0.012${}^{\ast \ast \ast }$	−0.011${}^{\ast \ast \ast }$	−0.011${}^{\ast \ast \ast }$
		(−4.14)	(−3.32)	(−3.53)
Supply	?	−0.003	−0.002	−0.003
		(−1.74)	(−1.46)	(−1.63)
N		2418	2418	2418
No. of Crypto Tokens		315	315	315
No. of Events		15	15	15
${\mathrm{R}}^2$		0.191	0.190	0.191
Platform FE		Yes	Yes	Yes
Event FE		Yes	Yes	Yes

Note: This Table presents the coefficients (t-statistics in parentheses) for the analyzes of the effect of Total Rating and Benchy Rating on market reactions to transparency regulation news events. The variables are defined in the Appendix A1. We cluster standard errors at the event- and crypto token-level and include crypto token platform- and event fixed effects. ${}^{\ast }$, ${}^{\ast \ast }$, and ${}^{\ast \ast \ast }$ denote statistical significance at the two-tailed 10, 5, and 1% level, respectively.

Table 7. Role of Expert Rating

		CAR
	Prediction	(1)	(2)	(3)	(4)	(5)
Expert Rating	+	0.013${}^{\ast \ast \ast }$				0.010${}^{\ast \ast \ast }$
		(2.64)				(2.28)
Team Rating	+		0.012${}^{\ast \ast \ast }$
			(3.28)
Vision Rating	+			0.009${}^{\ast }$
				(1.92)
Product Rating	+				0.010${}^{\ast \ast \ast }$
					(2.47)
Social Media Score	+					0.047${}^{\ast \ast \ast }$
						(3.70)
Size	?	−0.013${}^{\ast \ast \ast }$	−0.012${}^{\ast \ast \ast }$	−0.012${}^{\ast \ast \ast }$	−0.012${}^{\ast \ast \ast }$	−0.013${}^{\ast \ast \ast }$
		(−4.32)	(−4.12)	(−4.21)	(−3.78)	(−4.75)
Supply	?	−0.002	−0.002	−0.002	−0.002	−0.003
		(−1.39)	(−1.40)	(−1.27)	(−1.38)	(−1.75)
N		2418	2418	2418	2418	2418
No. of Crypto Tokens		315	315	315	315	315
No. of Events		15	15	15	15	15
${\mathrm{R}}^2$		0.191	0.192	0.190	0.191	0.193
Platform FE		Yes	Yes	Yes	Yes	Yes
Event FE		Yes	Yes	Yes	Yes	Yes

Note: This Table presents the coefficients (t-statistics in parentheses) for the analyzes of the effect of Expert Rating on market reactions to transparency regulation news events. The variables are defined in the Appendix A1. We cluster standard errors at the event- and crypto token-level and include crypto token platform- and event fixed effects. ${}^{\ast }$, ${}^{\ast \ast }$, and ${}^{\ast \ast \ast }$ denote statistical significance at the two-tailed 10, 5, and 1% level, respectively.

Table 8. Role of disclosure

		CAR
	Prediction	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)	(10)	(11)
Website Size	+		0.009${}^{\ast }$	0.008${}^{\ast }$							0.009${}^{\ast }$	0.008${}^{\ast }$
			(1.99)	(1.87)							(2.08)	(1.93)
GitHub	+				0.013	0.007					0.014	0.008
					(1.55)	(0.69)					(1.64)	(0.82)
Total GitHub Changes	+				−0.000	−0.000					−0.000	−0.000
					(−0.21)	(−0.33)					(−0.20)	(−0.34)
Total Tweets	+						0.000	−0.002			−0.002	−0.005
							(0.06)	(−0.32)			(−0.22)	(−0.57)
Total Replies	+								0.000	−0.000	0.001	0.003
									(0.12)	(−0.04)	(0.24)	(0.52)
Expert Rating	+	0.005		0.005		0.006		0.005		0.005		0.006
		(1.07)		(1.01)		(1.13)		(1.11)		(1.07)		(1.27)
Social Media Score	+	0.060${}^{\ast \ast \ast }$		0.057${}^{\ast \ast \ast }$		0.053${}^{\ast \ast }$		0.061${}^{\ast \ast \ast }$		0.060${}^{\ast \ast \ast }$		0.052${}^{\ast \ast }$
		(3.07)		(3.21)		(2.17)		(3.45)		(3.09)		(2.57)
Size	?	−0.009${}^{\ast \ast \ast }$	−0.005	−0.009${}^{\ast \ast \ast }$	−0.005	−0.008${}^{\ast \ast }$	−0.005	−0.009${}^{\ast \ast \ast }$	−0.005	−0.009${}^{\ast \ast \ast }$	−0.005	−0.008${}^{\ast \ast }$
		(−3.16)	(−1.41)	(−3.26)	(−1.12)	(−2.72)	(−1.48)	(−3.24)	(−1.35)	(−3.19)	(−1.26)	(−2.76)
Supply	?	−0.004${}^{\ast }$	−0.004${}^{\ast }$	−0.004${}^{\ast \ast }$	−0.004${}^{\ast }$	−0.004${}^{\ast \ast }$	−0.003	−0.004${}^{\ast }$	−0.003	−0.004${}^{\ast }$	−0.004${}^{\ast \ast }$	−0.004${}^{\ast \ast }$
		(−2.05)	(−2.03)	(−2.33)	(−2.04)	(−2.20)	(−1.72)	(−2.03)	(−1.75)	(−2.07)	(−2.40)	(−2.54)
N		1747	1747	1747	1747	1747	1747	1747	1747	1747	1747	1747
No. of Crypto Tokens		252	252	252	252	252	252	252	252	252	252	252
No. of Events		15	15	15	15	15	15	15	15	15	15	15
${\mathrm{R}}^2$		0.227	0.226	0.230	0.224	0.227	0.222	0.227	0.222	0.227	0.227	0.230
Platform FE		Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Event FE		Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes

Note: This Table presents the coefficients (t-statistics in parentheses) for the analyzes to the effect of cross-sectional differences in crypto token firm disclosure on market reactions to transparency regulation news events. The variables are defined in the Appendix A1. We cluster standard errors at the event- and crypto token-level and include crypto token platform- and event fixed effects. ${}^{\ast }$, ${}^{\ast \ast }$, and ${}^{\ast \ast \ast }$ denote statistical significance at the two-tailed 10, 5, and 1% level, respectively.

Table 9. Role of crypto exchanges

		CAR
	Prediction	(1)	(2)
Exchange Liquidity	+	0.014${}^{\ast \ast }$	0.013${}^{\ast \ast }$
		(2.20)	(2.87)
Exchange Volume	?	−0.005	−0.005${}^{\ast }$
		(−1.75)	(−1.92)
Exchange Visits	?	0.008${}^{\ast }$	0.008${}^{\ast }$
		(2.04)	(2.06)
Exchange #Cryptos	?	−0.012	−0.013
		(−0.84)	(−0.89)
Expert Rating	+		0.007${}^{\ast }$
			(1.85)
Social Media Score	+		0.038${}^{\ast \ast }$
			(2.35)
Size	?	−0.012${}^{\ast \ast }$	−0.014${}^{\ast \ast \ast }$
		(−2.97)	(−3.82)
Supply	?	−0.003${}^{\ast }$	−0.003${}^{\ast }$
		(−1.88)	(−1.96)
N		1771	1771
No. of Crypto Tokens		229	229
No. of Events		15	15
${\mathrm{R}}^2$		0.232	0.235
Platform FE		Yes	Yes
Event FE		Yes	Yes

Note: This Table presents the coefficients (t-statistics in parentheses) for the analyzes to the effect of cross-sectional differences in characteristics of exchanges on which tokens are listed on market reactions to transparency regulation news events. The variables are defined in the Appendix A1. We cluster standard errors at the event- and crypto token-level and include crypto token platform- and event fixed effects. ${}^{\ast }$, ${}^{\ast \ast }$, and ${}^{\ast \ast \ast }$ denote statistical significance at the two-tailed 10, 5, and 1% level, respectively.

Table B1. Definition of variables

Variable	Source	Description
CAR	Coinmarketcap	Sum of mean-adjusted return over $[0;+1]$ where t = 0 is the event date. For mean adjustment we use the average return over the 80 calendar days around t = 0, excluding other event-dates.
Size	Coinmarketcap	Natural logarithm of total market capitalization of a crypto token.
Supply	Coinmarketcap	Natural logarithm of total market capitalization divided by closing price of a crypto token.
Total Rating	ICOBench	Weighted average rating of Benchy Rating and Expert Rating, provided by ICOBench.
Benchy Rating	ICOBench	Rating of ICO information provided by ICO Analyzer Bot ‘Benchy,’ as the weighted average of the following four subcomponents: (1) Team Info. Score, (2) ICO Info. Score, (3) Product Info. Score, and (4) Social Media Score. ICOBench transforms the percentage ratings of individual subcomponents (see below) to a score between 0 and 5 prior to averaging.
Expert Rating	ICOBench	Weighted average of cryptocurrency/blockchain expert ratings, based on the following subcomponents: (1) Team Rating, (2) Vision Rating and (3) Product Rating.
Team Score	ICOBench	Score (in %) for total information available about team behind ICO, provided by ICO Analyzer Bot ‘Benchy’ on ICOBench.
ICO Info. Score	ICOBench	Score (in %) for total information available about ICO provided by ICO Analyzer Bot ‘Benchy’ on ICOBench.
Product Info. Score	ICOBench	Score (in %) for the total information available about product, provided by ICO Analyzer Bot ‘Benchy’ on ICOBench.
Social Media Score	ICOBench	Score (in %) for presence on social media, both in terms of total number of platforms and in activity on those platforms, provided by ICO Analyzer Bot ‘Benchy’ on ICOBench.
Team Rating	ICOBench	Rating (out of 5) of team behind the ICO provided by experts on ICOBench.
Vision Rating	ICOBench	Rating (out of 5) of the vision and/or plans outlaid in the ICO provided by experts on ICOBench.
Product Rating	ICOBench	Rating (out of 5) of the actual product or service offered by the company doing an ICO provided by experts on ICOBench.
Exchange Volume	Coinmarketcap	Natural log of the per crypto token average total dollar trading volume of all exchanges on which a crypto token is listed. The dollar trading volume is measured from December 7th till December 8th, 2021.
Exchange Liquidity	Coinmarketcap	Natural log of the per crypto token liquidity score of all exchanges on which a crypto token is listed. The liquidity score ranges from 0 to 1000 and is based on the slippage incurred by various order sizes, and is calculated by Coinmarketcap between December 7th and December 8th, 2021.
Exchange Visits	Coinmarketcap	Natural log of the per crypto token average of total number of unique visitors on the exchanges on which a crypto token is listed. The number of visitors are measured from December 7th till December 8th, 2021.
Exchange #Cryptos	Coinmarketcap	Natural log of the per crypto token average of the total number of cryptocurrencies on the exchanges on which a crypto token is listed. The number of cryptocurrencies is measured from December 7th till December 8th, 2021.
Website Size	WebArchive	Natural log of the size in bytes of the website of the crypto token company, following Boulland et al. (2021). We take the snapshot from the Internet Wayback Machine of the WebArchive at the date closest prior to the event.
GitHub	ICOBench	Indicator variable that is equal to ‘one’ if the crypto token company shares a link to a GitHub code repository on the ICO page on ICOBench.
Total GitHub Changes	CoinGecko	Natural log of the sum of additions and deletions in the code shared by the crypto token company in the GitHub code repository, up until the date of an event.
Total Tweets	Twitter	Natural log of one plus the number of tweets sent by the crypto token company up until the date of an event.
Total Replies	Twitter	Natural log of one plus the number of reply tweets sent by the crypto token company, i.e., replies to their own or others' tweets up until the date of an event.

Note: This Table gives an overview of the variables used in the analyzes, their sources, and their descriptions.

Table B2. Overview of the top 100 cryptocurrency exchanges

Country	No. of top 100 cryptocurrency exchanges	Exchanges
Australia	1	TOPBTC
Canada	2	BCEX, Coinsquare
Cayman Islands	1	BitMart
China	9	Binance, ZB.COM, DOBI trade, OEX, IDCM, Fatbtc, C2CX, Allcoin, LakeBTC
Cyprus	2	Coindeal, Cryptology
Dubai	1	RightBTC
Estonia	4	Bibox, CoinsBank, P2PB2B, CryptalDash
Gibraltar	1	GBX Digital Assets
Hong Kong	7	OKEx, HitBTC, LBank, Bitfinex, Bit-Z, Coinsuper, CHAOEX
India	1	UEX
Indonesia	2	Exrates, Indodax
Ireland	1	Bitsane
Japan	2	Bitbank, BTCBOX
Luxembourg	1	Bitstamp
Mongolia	1	IDAX
New Zealand	1	Cryptopia
Panama	1	IDEX
Peru	1	Bitinka
Poland	2	Coinroom, Coinbe
Russia	3	Simex, B2BX, YoBit
Singapore	10	Huobi, DigiFinex, CoinBene, DragonEX, CoinTiger, LATOKEN, Kucoin, MBAex, HADAX, Coinut
South Korea	6	Upbit, Allbit, CPDAX, Coinone, Korbit, GOPAX
Switzerland	1	Rfinex
Taiwan	1	Bitrue
Thailand	1	TDAX
Turkey	5	Sistemkoin, Vebitcoin, BtcTurk, Paribu, Ovis
UK	11	Cryptonex, CoinEgg, Bitlish, Exmo, Livecoin, CEX.IO, Mercatox, Bilaxy, BTC-Alpha, DSX, Luno
Ukraine	1	Liqui
Unknown	10	BitBay, Hotbit, InfinityCoin, Trade by Trade, BtcTrade.im, BiteBTC, Coinhub, Ethfinex, Liquid, Waves
US	10	Kraken, Coinbase Pro, Kryptono, Bittrex, Gate.io, Gemini, itBit, bitFlyer, Poloniex, Tidex

Note: This Table presents the total number and the names of top 100 cryptocurrency exchanges per country. If the country of registration could not be determined, the country of registration is ‘Unknown.’ Data is per November 2018.

Boulland, R., Bourveau, T., & Breuer, M. (2021). Corporate websites: A new measure of voluntary disclosure. https://ssrn.com/abstract=3816623

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