The Bitcoin market, characterized by its high volatility, consistently attracts the attention of investors and researchers. However, two primary challenges persist within this market: assessing its efficiency and identifying periods of price bubbles. These bubbles can lead to erroneous financial decisions. Despite extensive research, ambiguities surrounding non-random behavior and the formation of price bubbles in Bitcoin remain. This study investigates the efficiency of the Bitcoin market and identifies potential bubbles using the DS LPPLS (Discrete Singularity Log-Periodic Power Law Singularity) model, alongside confidence and sentiment indices. Daily closing prices of Bitcoin from the beginning of 2025 to the end of 2024 were utilized for this analysis. Through the examination of price charts and relevant indicators, it was determined that the Bitcoin market generally does not exhibit weak-form efficiency, and its behavior does not fully align with a purely random walk model. The confidence and sentiment indices, which reflect investor emotions towards the market, experienced significant fluctuations and showed a high correlation with price changes. Sudden and simultaneous increases in positive sentiment indicators and price suggest the formation of price bubbles during certain periods. The findings of this research indicate that the DS LPPLS model, in conjunction with confidence and sentiment indices, serves as a robust tool for analyzing Bitcoin market behavior and detecting price bubbles. Nevertheless, for more precise results, further in-depth investigation into factors influencing the market and the application of more complex models are warranted.
heydari,M , Shahiki Tash,M N and Ghasemi,M R . (2025). Decoding Bitcoin's Volatility: A Random Walk Analysis and Bubble Detection Using the DS LPPLS Model. (e47078). Monetary & Financial Economics, (), e47078 doi: 10.22067/mfe.2025.91430.1488
MLA
heydari,M , , Shahiki Tash,M N , and Ghasemi,M R . "Decoding Bitcoin's Volatility: A Random Walk Analysis and Bubble Detection Using the DS LPPLS Model" .e47078 , Monetary & Financial Economics, , , 2025, e47078. doi: 10.22067/mfe.2025.91430.1488
HARVARD
heydari M, Shahiki Tash M N, Ghasemi M R. (2025). 'Decoding Bitcoin's Volatility: A Random Walk Analysis and Bubble Detection Using the DS LPPLS Model', Monetary & Financial Economics, (), e47078. doi: 10.22067/mfe.2025.91430.1488
CHICAGO
M heydari, M N Shahiki Tash and M R Ghasemi, "Decoding Bitcoin's Volatility: A Random Walk Analysis and Bubble Detection Using the DS LPPLS Model," Monetary & Financial Economics, (2025): e47078, doi: 10.22067/mfe.2025.91430.1488
VANCOUVER
heydari M, Shahiki Tash M N, Ghasemi M R. Decoding Bitcoin's Volatility: A Random Walk Analysis and Bubble Detection Using the DS LPPLS Model. Monetary & Financial Economics. 2025;():e47078 (In Persian). doi: 10.22067/mfe.2025.91430.1488