Multivariate bubbles and antibubbles

In this paper we draw upon the close relationship between statistical physics and mathematical finance to develop a suite of models for financial bubbles and crashes. The derived models allow for a probabilistic and statistical formulation of econophysics models closely linked to mainstream financial models. Applications include monitoring the stability of financial systems and the subsequent policy implications. We emphasise the timeliness of our contribution with an application to the two largest cryptocurrency markets: Bitcoin and Ripple. Results shed new light on emerging debates over the nature of cryptocurrency markets and competition between rival digital currencies.

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“…Equation (33) shows that the shock reduces the level of return. The risk (variance) associated with equation ( 30) is…”

Section: Accepted M Manuscriptmentioning

confidence: 99%

Negative bubbles and shocks in cryptocurrency markets

Fry

Cheah

2016

International Review of Financial Analysis

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432

198

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“…Zhou et al, 2018), and oil (Cheng et al, 2018;Fantazzini, 2016;Sornette et al, 2009;Wątorek et al, 2016); (3) the Property Market: Real estate in the United States (Ardila et al, 2018;Brauers et al, 2014;W.-X. Zhou & Sornette, 2006b, the China (Zhi et al, 2019;, the United Kingdom (Fry, 2014), the Hong Kong and Seoul (Xiao, 2010), and the Switzerland (Ardila et al, 2018(Ardila et al, , 2021; (4) the Bond Market: Corporate bond yield (Clark, 2004), government bond CDS spread (Wosnitza & Denz, 2013), and financial institutions' CDS spread (Wosnitza & Leker, 2014b;Wosnitza & Sornette, 2015); (5) the Cryptocurrency Market (Gerlach et al, 2019;Geuder et al, 2019;Shu et al, 2021a;Shu & Zhu, 2020b;Wheatley et al, 2019); and (6) others: Foreign capital inflow and world population growth (Johansen & Sornette, 2001b).…”

Section: Literature Reviewmentioning

confidence: 99%

Detection of financial bubbles using a log‐periodic power law singularity (LPPLS) model

Shu,

Song

2024

WIREs Computational Stats

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This article provides a systematic review of the theoretical and empirical academic literature on the development and extension of the log‐periodic power law singularity (LPPLS) model, which is also known as the Johansen–Ledoit–Sornette (JLS) model or log‐periodic power law (LPPL) model. Developed at the interface of financial economics, behavioral finance and statistical physics, the LPPLS model provides a flexible and quantitative framework for detecting financial bubbles and crashes by capturing two salient empirical characteristics of price trajectories in speculative bubble regimes: the faster‐than‐exponential growth of price leading to unsustainable growth ending with a finite crash‐time and the accelerating log‐periodic oscillations. We also demonstrate the LPPLS model by detecting the recent bubble status of the S&P 500 index between April 2020 and December 2022, during which the S&P 500 index reaches its all‐time peak at the end of 2021. We find that the strong corrections of the S&P 500 index starting from January 2022 stem from the increasingly systemic instability of the stock market itself, while the well‐known external shocks, such as the decades‐high inflation, aggressive monetary policy tightening by the Federal Reserve, and the impact of the Russia/Ukraine war, may serve as sparks.This article is categorized under: Applications of Computational Statistics > Computational Finance Algorithms and Computational Methods > Computational Complexity Statistical Models > Nonlinear Models

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Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin

2015

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This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. The cu rrent m arket valu e of the bitcoin m arket is cu rrently estim ated to be arou nd $3.3 billion  Bitcoins p rices contain a consid erable sp ecu lative com p onent  Bitcoin m arkets are su scep tible to bu bbles.  The fu nd am ental valu e of bitcoins is zero. Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of BitcoinEng-Tuck Cheah * John Fry † February 2015Abstract Amid its rapidly increasing usage and immense public interest the subject of Bitcoin has raised profound economic and societal issues. In this paper we undertake economic and econometric modelling of Bitcoin prices. As with many asset classes we show that Bitcoin exhibits speculative bubbles. Further, we find empirical evidence that the fundamental price of Bitcoin is zero.

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Multivariate bubbles and antibubbles

Cited by 5 publications

References 34 publications

Negative bubbles and shocks in cryptocurrency markets

Negative bubbles and shocks in cryptocurrency markets

Detection of financial bubbles using a log‐periodic power law singularity (LPPLS) model

Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin

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