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The Predictability of High-Frequency Returns in the Cryptocurrency Markets and the Adaptive Market Hypothesis

Jacek Karasiński

Jacek Karasiński

University of Warsaw, Faculty of ManagementWarsaw, Poland
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Karasiński, Jacek
  
02 feb 2025
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Pubblicato online: 02 feb 2025
Pagine: 34 - 48
DOI: https://doi.org/10.2478/ceej-2025-0003
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© 2025 Jacek Karasiński, published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.

Figure 1.

The histograms of the percentage of efficient windowsNote: The headers of distributions refer to the intervals considered.
The histograms of the percentage of efficient windowsNote: The headers of distributions refer to the intervals considered.

Figure 2.

The histograms of the rate of changesNote: The headers of distributions refer to the intervals considered.
The histograms of the rate of changesNote: The headers of distributions refer to the intervals considered.

Figure 3.

The results of the MDH tests over consecutive months for a 30-minute intervalNote: ‘Portmonteau’ stands for the automatic Portmanteau test for serial correlation proposed by Escanciano and Lobato (2009). ‘AVR’ is an abbreviation for the wild bootstrapped automatic variance ratio test under conditional heteroskedasticity proposed by Kim (2009). ‘All tests’ refers to both tests together.
The results of the MDH tests over consecutive months for a 30-minute intervalNote: ‘Portmonteau’ stands for the automatic Portmanteau test for serial correlation proposed by Escanciano and Lobato (2009). ‘AVR’ is an abbreviation for the wild bootstrapped automatic variance ratio test under conditional heteroskedasticity proposed by Kim (2009). ‘All tests’ refers to both tests together.

Figure 4.

The results of the MDH tests over consecutive months for a 5-minute intervalNote: ‘Portmonteau’ stands for the automatic Portmanteau test for serial correlation proposed by Escanciano and Lobato (2009). ‘AVR’ is an abbreviation for the wild bootstrapped automatic variance ratio test under conditional heteroskedasticity proposed by Kim (2009). ‘All tests’ refers to both tests together.
The results of the MDH tests over consecutive months for a 5-minute intervalNote: ‘Portmonteau’ stands for the automatic Portmanteau test for serial correlation proposed by Escanciano and Lobato (2009). ‘AVR’ is an abbreviation for the wild bootstrapped automatic variance ratio test under conditional heteroskedasticity proposed by Kim (2009). ‘All tests’ refers to both tests together.

Figure 5.

The results of the MDH tests for the three most efficient and three least efficient cryptocurrencies over consecutive months for a 30-minute intervalNote: The numbers refer to the ranking of efficiency based on the results presented in Table 1. Codes refer to cryptocurrencies in the efficiency ranking: Bitcoin (BTC), Polygon (MATIC), Solana (SOL), Shiba Inu (SHIB), TRON (TRX), and Dogecoin (DOGE).
The results of the MDH tests for the three most efficient and three least efficient cryptocurrencies over consecutive months for a 30-minute intervalNote: The numbers refer to the ranking of efficiency based on the results presented in Table 1. Codes refer to cryptocurrencies in the efficiency ranking: Bitcoin (BTC), Polygon (MATIC), Solana (SOL), Shiba Inu (SHIB), TRON (TRX), and Dogecoin (DOGE).

Figure 6.

The results of the MDH tests for three most efficient and three least efficient cryptocurrencies over consecutive months for a 5-minute intervalNote: The numbers refer to the ranking of efficiency based on the results presented in Table 1. Codes refer to cryptocurrencies in the efficiency ranking: Chainlink (LINK), Solana (SOL), Avalanche (AVAX), BNB (BNB), XRP (XRP), and Dogecoin (DOGE).
The results of the MDH tests for three most efficient and three least efficient cryptocurrencies over consecutive months for a 5-minute intervalNote: The numbers refer to the ranking of efficiency based on the results presented in Table 1. Codes refer to cryptocurrencies in the efficiency ranking: Chainlink (LINK), Solana (SOL), Avalanche (AVAX), BNB (BNB), XRP (XRP), and Dogecoin (DOGE).

Correlation coefficients for the percentage of efficient windows and the efficiency change rate

Test/result Coefficient p-value
Interval Spearman Kendall Spearman Kendall
1 min 0.17 0.10 0.59 0.62
5 min −0.58 −0.52 0.02 0.01
30 min −0.84 −0.72 0.00 0.00

Correlation coefficients for the ranks of cryptocurrencies

Test/result Coefficient p-value
Spearman Interval 1 min 5 min 30 min Interval 1 min 5 min 30 min
1 min 1.00 1 min 1.00
5 min 0.21 1.00 5 min 0.49 1.00
30 min −0.79 −0.04 1.00 30 min 0.00 0.88 1.00
Kendall Interval 1 min 5 min 30 min Interval 1 min 5 min 30 min
1 min 1.00 1 min 1.00
5 min 0.10 1.00 5 min 0.68 1.00
30 min −0.59 0.03 1.00 30 min 0.00 0.92 1.00

The summary of the results of the MDH tests

Interval 1 minute 5 minutes 30 minutes All intervals
Cryptocurrency Windows tested Efficient windows Efficiency change rate Windows tested Efficient windows Efficiency change rate Windows tested Efficient windows Efficiency change rate Efficient windows Efficiency change rate
Polygon 709 97% 2% 97% 2%
Avalanche 571 90% 7% 697 94% 3% 709 95% 2% 94% 4%
Chainlink 571 83% 8% 697 96% 4% 709 90% 5% 90% 6%
Bitcoin Cash 571 83% 8% 697 91% 5% 709 95% 3% 90% 5%
Solana 571 72% 12% 697 95% 3% 709 97% 3% 89% 6%
Cardano 571 74% 9% 697 93% 5% 709 96% 3% 89% 5%
BNB 571 87% 8% 697 87% 6% 709 83% 5% 85% 6%
Shiba Inu 571 83% 9% 684 92% 5% 686 75% 7% 83% 7%
Polkadot 51 96% 4% 687 82% 7% 83% 7%
NEAR Protocol 571 53% 8% 684 93% 4% 700 90% 6% 80% 6%
Ethereum 571 44% 7% 697 93% 5% 709 95% 2% 80% 5%
Bitcoin 571 39% 9% 697 89% 5% 709 99% 1% 78% 5%
XRP 571 23% 4% 685 82% 6% 709 91% 5% 68% 5%
TRON 41 63% 16% 709 30% 7% 32% 8%
Toncoin 406 31% 9% 160 15% 3% 25 22% 15% 26% 8%
Dogecoin 380 3% 2% 697 24% 5% 709 24% 3% 20% 3%
Average 544 59% 8% 572 80% 5% 663 79% 5% 74% 5%
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