Quantifying endogeneity of cryptocurrency markets

Mark, Michael L.; Sila, Jan; Weber, Thomas A.

doi:10.1080/1351847x.2020.1791925

Cited by 12 publications

(12 citation statements)

References 50 publications

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“…on sub-samples of the jump times t i ) and rolling them forward in time to trace out a time-variant estimate of the parameters (e.g. Filimonov and Sornette 2012, Hardiman et al 2013, Filimonov et al 2014, Mark et al 2020. This approach of rectangular windowing brings several practical difficulties, like the selection of window size in a way that does not neglect relevant memory, or treatment of edge and truncation effects, which when neglected can bias parameter estimates.…”

Section: Calibration To Mid-price Data-the Hawkes(p Q) Modelmentioning

confidence: 99%

“…On randomized timestamps, the optimal model is a Hawkes(19,5) ¶ and reveals that the branching ratio is constantly above 0.8 and visits the critical regime twice before the occurrence of the crash, whereas it is only around 0.85 at the actual time of the price drop. To gauge how the overall level of self-excitation on the day of the crash compares to 'typical' dynamics of cryptocurrencies, we can look at the recent study of Mark et al (2020), done for the Bitcoin market. They estimate a standard Hawkes on mid-price changes that were induced by market orders.…”

Section: The Ether Crash In June 2017mentioning

confidence: 99%

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Classification of flash crashes using the Hawkes(p,q)framework

Wehrli

Sornette

2021

Quantitative Finance

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We introduce a novel modeling framework-the Hawkes(p, q) process-which allows us to parsimoniously disentangle and quantify the time-varying share of high frequency financial price changes that are due to endogenous feedback processes and not exogenous impulses. We show how both flexible exogenous arrival intensities, as well as a time-dependent feedback parameter can be estimated in a structural manner using an Expectation Maximization algorithm. We use this approach to investigate potential characteristic signatures of anomalous market regimes in the vicinity of 'flash crashes'-events where prices exhibit highly irregular and cascading dynamics. Our study covers some of the most liquid electronic financial markets, in particular equity and bond futures, foreign exchange and cryptocurrencies. Systematically balancing the degrees of freedom of both exogenously driving processes and endogenous feedback variation using information criteria, we show that the dynamics around such events are not universal, highlighting the usefulness of our approach: (i) post-mortem, for developing remedies and better future processes-e.g. improving circuit breakers or latency floor designs-and potentially (ii) ex-ante, for short-term forecasts in the case of endogenously driven events. Finally, we test our proposed model against a process with refined treatment of exogenous clustering dynamics in the spirit of the recently proposed autoregressive moving-average (ARMA) point process.

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Section: Calibration To Mid-price Data-the Hawkes(p Q) Modelmentioning

confidence: 99%

Section: The Ether Crash In June 2017mentioning

confidence: 99%

Classification of flash crashes using the Hawkes(p,q)framework

Wehrli

Sornette

2021

Quantitative Finance

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“…Both reach a plateau after three days. The decreasing and increasing pattern of

and n can be explained as follows: (1) The first fundraising day usually cannot span over an entire day, resulting in a calibrating window of less than 24 h. As pointed out by Mark et al [ 24 ], the branching ratio n can be underestimated in narrow windows. (2) The spreading process of the crowdfunding project is in an initial state on the first fundraising day.…”

Section: Resultsmentioning

confidence: 99%

“…Usually, the background intensity

in the Hawkes process is assumed to be a constant and the memory kernel function

takes the form of both an exponential function [ 5 , 19 , 24 ] and power-law function [ 16 , 20 , 24 ]. The exponential kernel indicates that the influence of the history donation exponentially decays with respect to the time elapsed since it occurred [ 25 ].…”

Section: Modelmentioning

confidence: 99%

“…Our results complement the analysis of the donating events by means of the recurrence interval analysis [ 15 ]. Second, differing from the studies on uncovering the endogeneity in price changes in financial markets [ 5 , 18 , 19 , 22 , 23 ] and in digital currency markets [ 24 ], our work focuses on the endogeneity in the donations of online crowdfunding projects, which still experiences a lack of investigation. Our data set contains 210,907 projects, spanning over a period from October 2015 to June 2020, which allows us to reveal the dominating driving force in online donations.…”

Section: Introductionmentioning

confidence: 99%

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Quantifying the Endogeneity in Online Donations

Wang

YinJie

et al. 2021

Entropy

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Charitable crowdfunding provides a new channel for people and families suffering from unforeseen events, such as accidents, severe illness, and so on, to seek help from the public. Thus, finding the key determinants which drive the fundraising process of crowdfunding campaigns is of great importance, especially for those suffering. With a unique data set containing 210,907 crowdfunding projects covering a period from October 2015 to June 2020, from a famous charitable crowdfunding platform, specifically Qingsong Chou, we will reveal how many online donations are due to endogeneity, referring to the positive feedback process of attracting more people to donate through broadcasting campaigns in social networks by donors. For this aim, we calibrate three different Hawkes processes to the event data of online donations for each crowdfunding campaign on each day, which allows us to estimate the branching ratio, a measure of endogeneity. It is found that the online fundraising process works in a sub-critical state and nearly 70–90% of the online donations are endogenous. Furthermore, even though the fundraising amount, number of donations, and number of donors decrease rapidly after the crowdfunding project is created, the measure of endogeneity remains stable during the entire lifetime of crowdfunding projects. Our results not only deepen our understanding of online fundraising dynamics but also provide a quantitative framework to disentangle the endogenous and exogenous dynamics in complex systems.

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Cryptocurrency market microstructure: a systematic literature review

Almeida,

Gonçalves

2023

Ann Oper Res

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This study contributes to the unconsolidated cryptocurrency literature, with a systematic literature review focused on cryptocurrency market microstructure. We searched Web of Science database and focused only on journals listed on 2021 ABS list. Our final sample comprises 138 research papers. We employed a quantitative and an integrative analysis, and revealed complex network associations, and a detailed research trending analysis. Our study provides a robust and systematic contribution to cryptocurrency literature by making use of a powerful and accurate methodology—the bibliographic coupling, also by only considering ABS academic journals, using a wider keyword scope, and not enforcing any restrictions regarding areas of knowledge, thus enhancing the contribution of extant literature by allowing the insights of more high-quality peripheral studies on the subject. The conclusions of this study are of extreme importance for researchers, investors, regulators, and the academic community in general. Our study provides high structured networking and clear information for research outlets and literature strands, for future studies on cryptocurrency investment, it also presents valuable insights to better understand the cryptocurrency market microstructure and deliver helpful information for regulators to effectively regulate cryptocurrencies.

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Quantifying endogeneity of cryptocurrency markets

Cited by 12 publications

References 50 publications

Classification of flash crashes using the Hawkes(p,q)framework

Classification of flash crashes using the Hawkes(p,q)framework

Quantifying the Endogeneity in Online Donations

Cryptocurrency market microstructure: a systematic literature review

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