These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

115 related articles for article (PubMed ID: 35194325)

  • 1. Extracting Rules via Markov Chains for Cryptocurrencies Returns Forecasting.
    Nascimento KKFD; Santos FSD; Jale JS; Júnior SFAX; Ferreira TAE
    Comput Econ; 2023; 61(3):1095-1114. PubMed ID: 35194325
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Fractional gray Lotka-Volterra models with application to cryptocurrencies adoption.
    Gatabazi P; Mba JC; Pindza E
    Chaos; 2019 Jul; 29(7):073116. PubMed ID: 31370408
    [TBL] [Abstract][Full Text] [Related]  

  • 3. The effect of COVID-19 pandemic on return-volume and return-volatility relationships in cryptocurrency markets.
    Foroutan P; Lahmiri S
    Chaos Solitons Fractals; 2022 Sep; 162():112443. PubMed ID: 36068915
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Estimating the volatility of cryptocurrencies during bearish markets by employing GARCH models.
    Kyriazis ΝA; Daskalou K; Arampatzis M; Prassa P; Papaioannou E
    Heliyon; 2019 Aug; 5(8):e02239. PubMed ID: 31453399
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Discovering interlinkages between major cryptocurrencies using high-frequency data: new evidence from COVID-19 pandemic.
    Yousaf I; Ali S
    Financ Innov; 2020; 6(1):45. PubMed ID: 35024267
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Volatility Interdependence Between Cryptocurrencies, Equity, and Bond Markets.
    Harb E; Bassil C; Kassamany T; Baz R
    Comput Econ; 2022 Sep; ():1-31. PubMed ID: 36187467
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Modelling and forecasting risk dependence and portfolio VaR for cryptocurrencies.
    Cheng J
    Empir Econ; 2023 Jan; ():1-26. PubMed ID: 36684815
    [TBL] [Abstract][Full Text] [Related]  

  • 8. COVID-19 pandemic improves market signals of cryptocurrencies-evidence from Bitcoin, Bitcoin Cash, Ethereum, and Litecoin.
    Sarkodie SA; Ahmed MY; Owusu PA
    Financ Res Lett; 2022 Jan; 44():102049. PubMed ID: 35475023
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Forecasting and trading cryptocurrencies with machine learning under changing market conditions.
    Sebastião H; Godinho P
    Financ Innov; 2021; 7(1):3. PubMed ID: 35024269
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Price Movement Prediction of Cryptocurrencies Using Sentiment Analysis and Machine Learning.
    Valencia F; Gómez-Espinosa A; Valdés-Aguirre B
    Entropy (Basel); 2019 Jun; 21(6):. PubMed ID: 33267303
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Forecasting Bitcoin closing price series using linear regression and neural networks models.
    Uras N; Marchesi L; Marchesi M; Tonelli R
    PeerJ Comput Sci; 2020; 6():e279. PubMed ID: 33816930
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Impact of COVID-19 effective reproductive rate on cryptocurrency.
    Minutolo MC; Kristjanpoller W; Dheeriya P
    Financ Innov; 2022; 8(1):49. PubMed ID: 35601747
    [TBL] [Abstract][Full Text] [Related]  

  • 13. COVID-19 and information flow between cryptocurrencies, and conventional financial assets.
    Assaf A; Mokni K; Youssef M
    Q Rev Econ Finance; 2023 Jun; 89():73-81. PubMed ID: 36908506
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Blockchain networks: Data structures of Bitcoin, Monero, Zcash, Ethereum, Ripple, and Iota.
    Akcora CG; Gel YR; Kantarcioglu M
    Wiley Interdiscip Rev Data Min Knowl Discov; 2022; 12(1):e1436. PubMed ID: 35865106
    [TBL] [Abstract][Full Text] [Related]  

  • 15. The predictive capacity of GARCH-type models in measuring the volatility of crypto and world currencies.
    Naimy V; Haddad O; Fernández-Avilés G; El Khoury R
    PLoS One; 2021; 16(1):e0245904. PubMed ID: 33513150
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Asymmetric efficiency of cryptocurrencies during COVID19.
    Naeem MA; Bouri E; Peng Z; Shahzad SJH; Vo XV
    Physica A; 2021 Mar; 565():125562. PubMed ID: 35875204
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A New Approach to Predicting Cryptocurrency Returns Based on the Gold Prices with Support Vector Machines during the COVID-19 Pandemic Using Sensor-Related Data.
    Mahdi E; Leiva V; Mara'Beh S; Martin-Barreiro C
    Sensors (Basel); 2021 Sep; 21(18):. PubMed ID: 34577525
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Is Bitcoin Still a King? Relationships between Prices, Volatility and Liquidity of Cryptocurrencies during the Pandemic.
    Będowska-Sójka B; Kliber A; Rutkowska A
    Entropy (Basel); 2021 Oct; 23(11):. PubMed ID: 34828084
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Herding and feedback trading in cryptocurrency markets.
    King T; Koutmos D
    Ann Oper Res; 2021; 300(1):79-96. PubMed ID: 33462519
    [TBL] [Abstract][Full Text] [Related]  

  • 20. From code to market: Network of developers and correlated returns of cryptocurrencies.
    Lucchini L; Alessandretti L; Lepri B; Gallo A; Baronchelli A
    Sci Adv; 2020 Dec; 6(51):. PubMed ID: 33328237
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.