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Event Studies with Crypto-Asset Returns


Event Studies with Crypto-Asset Returns

Amsden, Ryan (2019) Event Studies with Crypto-Asset Returns. Masters thesis, Concordia University.

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This paper provides the first empirical evidence of how the unique properties of crypto-asset returns impact event-study test performance. Employing a simulation approach with actual price data from 1877 unique crypto-assets over the period of January 1st, 2015 to June 30th, 2018 reveals that both parametric procedures and non-parametric procedures often result in significant statistical errors. In the presence of event-day clustering, only the Generalized Rank T-Test is both powerful and well specified. To estimate abnormal returns, the market-model with a value-weighted index produces test statistics with distributions closest to expectation. The empirical evidence provided by the simulation then used in the first ever crypto-asset based event-study. Specifically, the event study investigated allegations of insider trading by the worlds largest crypto-asset exchange Binance.com. A total of 44 unique listing announcements during the period of September 2017 to June 2018. produce a statistically significant two day return of 13.6% (CAR(0,1)). However, the GRANK-T test fails to reject the null hypothesis of no insider trading during the three days preceding the announcements. Guidance and future applications of event-studies with crypto-asset returns are discussed.

Divisions:Concordia University > John Molson School of Business > Finance
Item Type:Thesis (Masters)
Authors:Amsden, Ryan
Institution:Concordia University
Degree Name:M. Sc.
Date:28 March 2019
Thesis Supervisor(s):Schweizer, Denis
ID Code:985163
Deposited By: RYAN AMSDEN
Deposited On:19 Dec 2019 14:44
Last Modified:01 Mar 2021 02:00
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