Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 368

The DOI matches its Crossref record; 25 of the 25 references it cites were found in a registry or an index.

Crypto-currency bubbles: an application of the Phillips–Shi–Yu (2013) methodology on Mt. Gox bitcoin prices

Cheung, Adrian (Wai-Kong), Roca, Eduardo, Su, Jen-Je·2015·Applied Economics

Abstract

The creation of bitcoin heralded the arrival of digital or crypto-currency and has been regarded as a phenomenon. Since its introduction, it has experienced a meteoric rise in price and rapid growth accompanied by huge volatility swings, and also attracted plenty of controversies which even involved law enforcement agencies. Hence, claims abound that bitcoin has been characterized by bubbles ready to burst any time (e.g. the recent collapse of bitcoin’s biggest exchange, Mt Gox). This has earned plenty of coverage in the media but surprisingly not in the academic literature. We therefore fill this knowledge gap. We conduct an econometric investigation of the existence of bubbles in the bitcoin market based on a recently developed technique that is robust in detecting bubbles – that of Phillips et al. (2013a). Over the period 2010–2014, we detected a number of short-lived bubbles; most importantly, we found three huge bubbles in the latter part of the period 2011–2013 lasting from 66 to 106 days, with the last and biggest one being the one that ‘broke the camel’s back’ – the demise of the Mt Gox exchange.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1080/00036846.2015.1005827

Cites

25 of 25 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 25 references

Cited by

See all 368

Metadata

Authors
Cheung, A. (.-K., Roca, E., & Su, J.-J.
Venue
Applied Economics
Published
2015-02-04
Volume
47
Issue
23
Pages
2348-2358
ISSN
  • 0003-6846 (ISSN-L)
  • 1466-4283
OpenAlex
W2041854950
Cited by
368
References
25
FWCI
46.69
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Crypto-currency bubbles: an application of the Phillips–Shi–Yu (2013) methodology on Mt. Gox bitcoin prices. https://app.cochat.ai/papers/10.1080/00036846.2015.1005827
The paper
Cheung, A. (.-K., Roca, E., & Su, J.-J. (2015). Crypto-currency bubbles: an application of the Phillips–Shi–Yu (2013) methodology on Mt. Gox bitcoin prices. Applied Economics. https://doi.org/10.1080/00036846.2015.1005827

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.