Modelling the dynamics of cryptocurrency prices for risk hedging: The case of Bitcoin, Ethereum, and Litecoin

被引:3
|
作者
Madichie, Chekwube V. [1 ,2 ]
Ngwu, Franklin N. [2 ]
Eze, Eze A. [3 ]
Maduka, Olisaemeka D. [3 ]
机构
[1] Pan Atlantic Univ, Lagos Business Sch, Km 22 Lekki Epe Expressway, Lagos 101245, Nigeria
[2] Pan Atlantic Univ, Lagos Business Sch, Lagos, Nigeria
[3] Nnamdi Azikiwe Univ, Dept Econ, Awka, Nigeria
来源
COGENT ECONOMICS & FINANCE | 2023年 / 11卷 / 01期
关键词
cryptocurrency; digital currency; Bitcoin; Ethereum; Litecoin; ARDL; wavelet decomposition; wavelet Granger; MARKETS; GOLD; OIL;
D O I
10.1080/23322039.2023.2196852
中图分类号
F [经济];
学科分类号
02 ;
摘要
Cryptocurrencies have, over the years, gained an unprecedented prominence in financial discourse, with the market fielding over 5,300 digital currencies and reaching over $2 trillion in market capitalisation in 2022. The surge in market values of digital currencies and their popularity in the world of e-commerce have remained unabated and equally received special attention from researchers focusing on identifying the underlying factors that drive changes in their market values. Thus, this study models the dynamics of the prices of cryptocurrencies alongside their interconnectedness, focusing on Bitcoin, Ethereum, and Litecoin along the time and frequency dimensions of monthly data from 1 March 2016 to 05/31/2022. Based on the ARDL model, results show that the volume of transactions of Bitcoin, Ethereum, and Litecoin, oil prices, and gold prices exert a more significant positive influence on their prices in the longrun than in the shortrun. However, the publicity of the selected cryptocurrencies (google search rates) does not significantly influence their prices. Interestingly, results from the Wavelet Granger causality tests show no causality between the raw series of Bitcoin, Ethereum, and Litecoin prices. However, a bi-directional causality exists between Bitcoin and Ethereum prices during the longrun in their low frequencies, a unidirectional causality running from Bitcoin to Litecoin prices during the longrun in their low frequencies, and a unidirectional causality running from Litecoin to Ethereum prices during the shortrun, medium run and longrun in their high, medium, and low frequencies. These findings have profound implications for the global financial market and investor decisions.
引用
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页数:23
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  • [1] Prediction of cryptocurrency prices by deep learning models: A case study for Bitcoin and Ethereum
    Mehrdoust, Farshid
    Noorani, Maryam
    [J]. INTERNATIONAL JOURNAL OF FINANCIAL ENGINEERING, 2023, 10 (04)
  • [2] Cryptocurrency as a safe haven for investment portfolios amid COVID-19 panic cases of Bitcoin, Ethereum and Litecoin
    Marobhe, Mutaju Isaack
    [J]. CHINA FINANCE REVIEW INTERNATIONAL, 2022, 12 (01) : 51 - 68
  • [3] On the efficiency and its drivers in the cryptocurrency market: the case of Bitcoin and Ethereum
    Mokni, Khaled
    El Montasser, Ghassen
    Ajmi, Ahdi Noomen
    Bouri, Elie
    [J]. FINANCIAL INNOVATION, 2024, 10 (01)
  • [4] On the efficiency and its drivers in the cryptocurrency market: the case of Bitcoin and Ethereum
    Khaled Mokni
    Ghassen El Montasser
    Ahdi Noomen Ajmi
    Elie Bouri
    [J]. Financial Innovation, 10
  • [5] Modelling the dynamics of Bitcoin and Litecoin: GARCH versus stochastic volatility models
    Tiwari, Aviral Kumar
    Kumar, Satish
    Pathak, Rajesh
    [J]. APPLIED ECONOMICS, 2019, 51 (37) : 4073 - 4082
  • [6] Structural breaks and double long memory of cryptocurrency prices: A comparative analysis from Bitcoin and Ethereum
    Mensi, Walid
    Al-Yahyaee, Khamis Hamed
    Kang, Sang Hoon
    [J]. FINANCE RESEARCH LETTERS, 2019, 29 : 222 - 230
  • [7] Cryptocurrency liquidity during the Russia-Ukraine war: the case of Bitcoin and Ethereum
    Theiri, Saliha
    Nekhili, Ramzi
    Sultan, Jahangir
    [J]. JOURNAL OF RISK FINANCE, 2023, 24 (01) : 59 - 71
  • [8] Information flow dynamics between cryptocurrency returns and electricity consumption: A comparative analysis of Bitcoin and Ethereum
    Almeida, Dora
    Dionisio, Andreia
    Ferreira, Paulo
    [J]. FINANCE RESEARCH LETTERS, 2024, 68
  • [9] Is there a risk-return trade-off in cryptocurrency markets? The case of Bitcoin
    Ahmed, Walid M. A.
    [J]. JOURNAL OF ECONOMICS AND BUSINESS, 2020, 108
  • [10] Modelling the risk of mosquito-borne diseases by System Dynamics: the case of human travel between different geographic regions
    Mecoli, M.
    De Angelis, V.
    Brailsford, S. C.
    [J]. 2010 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS (SMC 2010), 2010,