Marcin Wątorek, Marija Bezbradica, Martin Crane, Jarosław Kwapień, Stanisław Drożdż
arXiv 23 Sep 2025 · Finance — Statistical Finance · publishedPhysical review. E (2025) · 1 citations (OpenAlex)
arXiv:2509.18820 · PDF · DOI · OpenAlex · Extracted main text
Based on the cryptocurrency market dynamics, this study presents a general methodology for analyzing evolving correlation structures in complex systems using the $q$-dependent detrended cross-correlation coefficient \rho(q,s). By extending traditional metrics, this approach captures correlations at varying fluctuation amplitudes and time scales. The method employs $q$-dependent minimum spanning trees ($q$MSTs) to visualize evolving network structures. Using minute-by-minute exchange rate data for 140 cryptocurrencies on Binance (Jan 2021-Oct 2024), a rolling window analysis reveals significant shifts in $q$MSTs, notably around April 2022 during the Terra/Luna crash. Initially centralized around Bitcoin (BTC), the network later decentralized, with Ethereum (ETH) and others gaining prominence. Spectral analysis confirms BTC's declining dominance and increased diversification among assets. A key finding is that medium-scale fluctuations exhibit stronger correlations than large-scale ones, with $q$MSTs based on the latter being more decentralized. Properly exploiting such facts may offer the possibility of a more flexible optimal portfolio construction. Distance metrics highlight that major disruptions amplify correlation differences, leading to fully decentralized structures during crashes. These results demonstrate $q$MSTs' effectiveness in uncovering fluctuation-dependent correlations, with potential applications beyond finance, including biology, social and other complex systems.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | author author J. Kwapień, author P. Oświecimka, author M. Forczek,\… (2017) ) NoStop | 0.874 | 7 | 2 | 100% |
| 2 | author author J. Kwapień, author P. Oświecimka,\ and\ author S. Droż… (2015) ) NoStop | 0.874 | 5 | 2 | 100% |
| 3 | author author J. Kwapień\ and\ author S. Drożdż,\ title title Physic… (2012) 01.007 journal journal Physics Reports\ volume 515,\ pages 115 ( year 2012) NoStop | 0.843 | 3 | 3 | 100% |
| 4 | @noop title CoinDesk DACSclassification,\ howpublished https://indic… | 0.737 | 3 | 3 | 67% |
| 5 | author author J. W.\ Kantelhardt, author S. A.\ Zschiegner, author E… (2002) ) NoStop | 0.737 | 3 | 2 | 100% |
| 6 | author author R. N.\ Mantegna,\ title title Hierarchical structure i… (1999) ) NoStop | 0.737 | 3 | 2 | 100% |
| 7 | author author P. Oświecimka, author S. Drożdż, author M. Forczek, au… (2014) ) NoStop | 0.737 | 3 | 2 | 100% |
| 8 | author author S. Drożdż\ and\ author P. Oświecimka,\ title title Det… (2015) ) NoStop | 0.644 | 2 | 2 | 100% |
| 9 | author author J. B.\ Kruskal,\ title title On the shortest spanning… (1956) ) NoStop | 0.644 | 2 | 2 | 100% |
| 10 | author author R. C.\ Prim,\ title title Shortest connection networks… (1957) ) NoStop | 0.644 | 2 | 2 | 100% |
Showing the top 10 of 114 scored citations.