Announcement effects in the cryptocurrency market

Joo, Mohammad Hashemi; Nishikawa, Yuka; Dandapani, Krishnan

doi:10.1080/00036846.2020.1745747

Cited by 31 publications

(11 citation statements)

References 37 publications

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“…Comparing the magnitudes of CARs for negative and positive events, we can state that the market reacts stronger to negative surprises than to positive ones, especially within the first and the second sub-periods. The asymmetric behavior of this emerging asset is in line with the findings of [ 49 , 51 , 53 ]. However, the empirical evidence presented within Tables 4 – 7 suggests that the fluctuation of returns registered after the arrival of an unexpected event shows a decrease in magnitude over time.…”

Section: Resultssupporting

confidence: 87%

“…In addition, the authors found that investors overreacted during days of sharp declines in the Bitcoin price and weeks of market rallies. Also, the same asymmetrical overreaction of the investor on this crypto market was found by [ 51 – 53 ]. Briefly, the authors emphasized that the market reaction to negative events is stronger than to positive events; that is to say, the cryptocurrency market is inefficient.…”

Section: Introductionsupporting

confidence: 80%

“…To examine the reactions of investors to the arrival of unexpected information in the Bitcoin market, we first identified the date of the arrival of unexpected information. Contrary to previous studies [ 37 , 53 ], we did not use economic and political news as surprises; rather, we employed a strictly quantitative approach to identify the market surprises. Specifically, following [ 67 ], we identified the market events by estimating GARCH(1,1) model for the data and defined thresholds for standardized residuals as 2.5 quantiles (as in [ 56 ]) of unexpected unfavorable information and, respectively, unexpected favorable information.…”

Section: Methodsmentioning

confidence: 99%

“…First, we built a set of daily abnormal returns (AR t ) of each day included in the 5-day post-information window. Following [ 53 ] and because the applicability of asset pricing models for cryptocurrency is still puzzling [ 60 ], we calculated the AR in a simple manner, as the difference between actual daily return and the expected return of each period–computed as the mean of non-event days. More specifically: where AR t is the abnormal return for Bitcoin on day t following the arrival of unexpected information; t = 1,2,….5; R t is the return of Bitcoin on day t in the 5-day-window; and R non is the mean return for Bitcoin over the non-event days.…”

Section: Methodsmentioning

confidence: 99%

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An analysis of investors’ behavior in Bitcoin market

2022

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As an emerging digital asset, Bitcoin has been traded for more than a decade, reaching an impressively high market capitalization and continuing to expand its volume of trading at a rapid pace. Many countries have legalized or are considering legalizing a trading platform for this asset, and a set of companies worldwide accept it as a medium of exchange. As a result of this expansion, many studies in finance literature have focused on studying the efficiency of this cryptocurrency. In line with this literature, this paper investigates, using the abnormal returns and abnormal trading volumes methodologies, the dynamics of investors’ reaction to the arrival of unexpected favorable and unfavorable information regarding the Bitcoin market in the context of the three famous hypotheses: the overreaction, the uncertain information, and the efficient market hypotheses. Overall, we find evidence confirming that the Bitcoin market tends to mature over time. More precisely, over the entire analyzed period, investors behave in accordance with the predictions of the uncertain information hypothesis when positive and negative events occur. However, splitting the timespan into sub-periods provides interesting insights. Remarkably in this respect is the fact that starting with the second sub-period, the response of investors in the Bitcoin market supports, in a moderate manner, the postulate of the efficient market hypothesis when favorable events are addressed. Moreover, our findings reveal that during the pandemic period, the efficiency of Bitcoin has increased, thus turning this stressful period into an advantage for this cryptocurrency. This improved market efficiency is also supported by the abnormal trading volume analysis.

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Section: Resultssupporting

confidence: 87%

Section: Introductionsupporting

confidence: 80%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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An analysis of investors’ behavior in Bitcoin market

2022

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“…MacKinlay (1997) fixed the length of the estimation window at 60. Following previous works on event study in the cryptocurrency market (Hashemi Joo et al, 2020;Ante and Fiedler, 2020), we employ the mean-adjusted-return model and an estimation window of 365 days to calculate the expected return. We also use a smaller estimation window of 60 days to check the robustness of our results.…”

Section: Methodsmentioning

confidence: 99%

Cryptocurrency bubble risk and the FOMC announcements during COVID-19 black swan event

Jarboui¹,

Mnif

2021

JOIC

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Purpose After the COVID-19 outbreak, the Federal Reserve has undertaken several monetary policies to alleviate the pandemic consequences on the markets. This paper aims to evaluate the effects of the Federal Reserve monetary policy on the cryptocurrency dynamics during the COVID19 pandemic. Design/methodology/approach We examine the response and feedback effects via an event study methodology. For this purpose, abnormal returns (AR) and cumulative abnormal returns (CARs) around the first FOMC (Federal Open Market Committee) announcement related to the COVID-19 pandemic for the top five cryptocurrencies are explored. We, further investigate the effect of the eight FOMC statement announcements during the COVID19 pandemic on these cryptocurrencies (Bitcoin, Ethereum, Tether, Litecoin, and Ripple). In the above-mentioned crypto-currency markets, we investigate the presence of bubbles by using the PSY test. We then examine the concordance of the dates of these bubbles with the dates of the FOMC announcements. Findings The empirical results show that the first FOMC event has a negative significant effect after 4 days of the announcement date for all studied cryptocurrencies except Tether. The results also indicate that cumulative abnormal returns are significant during the event windows of (−3,8), (−3,9), and (−3,10). Besides, we find that Bitcoin, Ethereum and, Litecoin lived short bubbles lasting for a few days. However, Ripple and Tether markets present no bubbles and no explosive periods. Research limitations/implications This paper presents trained proof that FOMC announcements have a positive effect on volatility's predictive capacity. This work therefore promotes the study of the data quality of volatility in future research as well. Practical implications The justified effect of the FOMC announcements on cryptocurrency as a speculative asset has practical implications for investors in building their trading strategies in anticipation of the next FOMC announcement. Therefore, this study implies that the FOMC announcements contain very relevant information for investors in the cryptocurrency market. This research may not only encourage a better understanding of the evolution of the expectations of policymakers, but also facilitate a better understanding of how these expectations are developed. Originality/value The COVID-19 pandemic has disturbed the stability of financial markets, inciting the Fed to take some monetary regulations. To the best of our knowledge, this study is the first one that analyses the response of five major cryptocurrencies to FOMC announcements during COVID 19 pandemic and associates these dates with bubble occurrences.

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The effects of hacking events on bitcoin

Pham

Thanh

Ramiah

et al. 2021

Journal of Public Affairs

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We examine the short-term and long-term effects of hacking events on bitcoin return. Additionally, we attempt to find out if investors can benefit from these events by adopting and modifying the models proposed by Baur et al. (2018) [Journal of International Financial Markets, Institutions & Money, 54, 177-189] who compare the performance of bitcoin against FX returns and the S&P500. The results show that hacking events present an opportunity for investors to make a profit if they invest in bitcoin, stocks and currencies. Such an opportunity, however, does not last for long.

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Announcement effects in the cryptocurrency market

Cited by 31 publications

References 37 publications

An analysis of investors’ behavior in Bitcoin market

An analysis of investors’ behavior in Bitcoin market

Cryptocurrency bubble risk and the FOMC announcements during COVID-19 black swan event

The effects of hacking events on bitcoin

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