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arXiv · 2609.32611

Crypto Price Similarity: An Investigation Using Pearson Correlation and Dynamic Time Warping

Onur Batin Doğan·Fatma Sevinç Kurnaz
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Abstract

The cryptocurrency market's volatility and complex price dynamics challenge portfolio diversification and risk management. This study examines price similarity across 347 cryptocurrencies from March 2020 to April 2024 using daily OHLCV data from the Binance API. Daily dynamics are summarized via a signed, capped intraday price-range metric, and pair similarity is assessed using the Pearson cross-correlation coefficient, capturing linear co-movement at a given lag, and Dynamic Time Warping (DTW) distance, capturing shape similarity independent of lag. Data are segmented into three market phases: an uptrend, a decline, and a subsequent uptrend. For each period, the 10 pairs with highest cross-correlation and lowest DTW distance are identified. BNB-CAKE, XLM-XRP, and MANA-SAND show the strongest cross correlations across the three periods, with coefficients of 0.78 or higher and maximum correlations at lag 0, indicating synchronized movements. Three to four of the ten lowest-DTW pairs coincide with the cross-correlation top 10 per period, showing the measures are related but not interchangeable. Two same-platform fan tokens rank among the most DTW-similar pairs despite weak cross-correlation, while a euro pegged asset and gold-backed token show the lowest DTW distance, driven by low volatility rather than shared dynamics. Results demonstrate substantial, measure dependent interconnectedness with implications for diversification strategies.

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Onur Batin Doğan, Fatma Sevinç Kurnaz. 2026-09-26. Crypto Price Similarity: An Investigation Using Pearson Correlation and Dynamic Time Warping. https://arxiv.org/abs/2609.32611

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