Cryptocurrency Price Bubble Detection Using Log-Periodic Power Law Model and Wavelet Analysis

In this article, we establish a method to detect and formulate price bubbles in the cryptocurrency markets. This method identifies abnormal crashes through violations of the exponential decaying property. Confirmations of bubble bursts within these anomalies are obtained through wavelet analysis. By decomposing the cryptocurrency price into the high-frequency and low-frequency factors, we distinguish the price regimes versus the periods with bubbles and crashes in both time and frequency domains. In addition, we apply the log-periodic power law model to fit the bubble formation. In the analysis of eight cryptocurrencies—Bitcoin, Ethereum, Litecoin, Antshares, Ethereum Classic, Dash, Monero, and OmiseGO—from 15 May 2018 to 28 November 2022, we identify 24 bubbles. Some of them exhibit a significant and strong exponential growth pattern.

• Publication year

  2024

• Venue

  IEEE transactions on engineering management

• Publication date

  Unknown publication date

• Fields of study

  Business, Computer Science, Economics

• Identifiers
  DOI 10.1109/TEM.2024.3427647
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• On the Applications of Blockchain in FinTech: Advancements and Opportunities

  2024cited by this paper
• Trading patterns in the bitcoin market

  2023cited by this paper
• Examination of Bitcoin Exchange Through Agent-Based Modeling: Focusing on the Perceived Fundamental of Bitcoin

  2022cited by this paper
• A review on drawdown risk measures and their implications for risk management

  2022cited by this paper
• Financial time series forecasting using optimized multistage wavelet regression approach

  2022cited by this paper
• Log Periodic Power Analysis of Critical Crashes: Evidence from the Portuguese Stock Market

  2022cited by this paper
• Time-Varying Nexus between Investor Sentiment and Cryptocurrency Market: New Insights from a Wavelet Coherence Framework

  2021cited by this paper
• Bubble detection in Greek Stock Market: A DS-LPPLS model approach

  2021cited by this paper
• Does Sentiment Impact Cryptocurrency?

  2021cited by this paper
• Bitcoin price forecasting: A perspective of underlying blockchain transactions

  2021cited by this paper
• Are Cryptos Safe-Haven Assets during Covid-19? Evidence from Wavelet Coherence Analysis

  2021cited by this paper
• Cumulation, crash, coherency: A cryptocurrency bubble wavelet analysis

  2020cited by this paper
• How well the log periodic power law works in an emerging stock market?

  2020cited by this paper
• Dynamic interdependence of cryptocurrency markets: An analysis across time and frequency

  2020cited by this paper
• Time-frequency co-movement of cryptocurrency return and volatility: Evidence from wavelet coherence analysis

  2020cited by this paper
• Pricing Cryptocurrency Options

  2020cited by this paper
• Fractal dynamics and wavelet analysis: Deep volatility and return properties of Bitcoin, Ethereum and Ripple

  2020cited by this paper
• News sentiment in the cryptocurrency market: An empirical comparison with Forex

  2020cited by this paper
• A new method to verify Bitcoin bubbles: Based on the production cost

  2020cited by this paper
• Towards an Understanding of Cryptocurrency: A Comparative Analysis of Cryptocurrency, Foreign Exchange, and Stock

  2019cited by this paper
• Stochastic asset price dynamics and volatility using a symmetric supply and demand price equation

  2019cited by this paper
• Cryptocurrencies as financial bubbles: The case of Bitcoin

  2019cited by this paper
• Sentiment-Induced Bubbles in the Cryptocurrency Market

  2019cited by this paper
• Real-time prediction of Bitcoin bubble crashes

  2019cited by this paper
• Are Bitcoin bubbles predictable? Combining a generalized Metcalfe’s Law and the Log-Periodic Power Law Singularity model

  2019cited by this paper
• Detecting bubbles in Bitcoin price dynamics via market exuberance

  2019cited by this paper
• A Continuous Time Model for Bitcoin Price Dynamics

  2018cited by this paper
• Cryptocurrency price drivers: Wavelet coherence analysis revisited

  2018cited by this paper
• Dissection of Bitcoin’s multiscale bubble history from January 2012 to February 2018

  2018cited by this paper
• Datestamping the Bitcoin and Ethereum bubbles

  2017cited by this paper
• Predicting cryptocurrency price bubbles using social media data and epidemic modelling

  2017cited by this paper
• On the predictability of stock market bubbles: evidence from LPPLS confidence multi-scale indicators

  2017cited by this paper
• Birth or burst of financial bubbles: which one is easier to diagnose?

  2017cited by this paper
• LPPLS Bubble Indicators over Two Centuries of the S&P 500 Index

  2016cited by this paper
• Crypto-currency bubbles: an application of the Phillips–Shi–Yu (2013) methodology on Mt. Gox bitcoin prices

  2015cited by this paper
• Power Law Scaling and 'Dragon-Kings' in Distributions of Intraday Financial Drawdowns

  2014cited by this paper
• The digital traces of bubbles: feedback cycles between socio-economic signals in the Bitcoin economy

  2014cited by this paper
• What Are the Main Drivers of the Bitcoin Price? Evidence from Wavelet Coherence Analysis

  2014cited by this paper
• The volatility-confined LPPL model: A consistent model of ‘explosive’ financial bubbles with mean-reverting residuals

  2014cited by this paper
• The economics of BitCoin price formation

  2014cited by this paper
• Bitcoin - Asset or Currency? Revealing Users' Hidden Intentions

  2014cited by this paper
• Super-exponential bubbles in lab experiments: evidence for anchoring over-optimistic expectations on price

  2012cited by this paper
• A Stable and Robust Calibration Scheme of the Log-Periodic Power Law Model

  2011influential reference
• Everything you always wanted to know about log-periodic power laws for bubble modeling but were afraid to ask

  2011cited by this paper
• Shocks, Crashes and Bubbles in Financial Markets

  2010cited by this paper
• On the Analytic Wavelet Transform

  2007cited by this paper
• Characterization of large price variations in financial markets

  2002influential reference
• Significance of log-periodic precursors to financial crashes

  2001cited by this paper
• Large Stock Market Price Drawdowns Are Outliers

  2000influential reference
• Determining Local Singularity Strengths and their Spectra with the Wavelet Transform

  2000cited by this paper
• CRASHES AS CRITICAL POINTS

  1998cited by this paper
• Stock market crashes are outliers

  1997influential reference

• Novel symbolic detection for flight-to-safety in Bitcoin and investigation of information flow dynamics alongside multiple markets

  2025cites this paper
• A spatial analysis of the use of Bitcoin as a medium of exchange

  2025cites this paper
• Log-periodicity: Fact or fiction?

  2025cites this paper
• A Hybrid Wavelet-GNN-LSTM Framework for Cryptocurrency Forecasting

  2025influential citation
• Assessment of the Volatility of the Main Cryptocurrencies, the Euro and the Direct Exchange Rate of the Ruble

  2024cites this paper