Examining the day-of-the-week-effect and the-month-of-the-year-effect in cryptocurrency market

Robiyanto, Robiyanto; Susanto, Yosua Arif; Ernayani, Rihfenti

doi:10.26905/jkdp.v23i3.3005

Cited by 12 publications

(12 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The analysis reveals that BTC returns were determined to be highest on Thursday. The results of the study by Robiyanto et al ( 2019 ) are consistent with those of this study. Contrary to these results, Durai and Paul ( 2018 ) and Evci ( 2020 ) determined that the lowest return was on Thursday.…”

Section: Discussionsupporting

confidence: 93%

“…Yaya and Ogbanna ( 2019 ) examined 2015–2019 data with dummy variables and concluded that the effect of the day-of-the-week on BTC returns is insignificant. Robiyanto et al ( 2019 ) examined the effect of the day-of-the-week and the month of the year on BTC and LTC from 2014 to 2018 using a GARCH model. They concluded that investors should buy BTC at the end of January and sell it at the end of February and that Monday, Wednesday, and Thursday have a positive impact on BTC returns.…”

Section: Literaturementioning

confidence: 99%

See 1 more Smart Citation

Artificial neural network analysis of the day of the week anomaly in cryptocurrencies

et al. 2023

View full text Add to dashboard Cite

Anomalies, which are incompatible with the efficient market hypothesis and mean a deviation from normality, have attracted the attention of both financial investors and researchers. A salient research topic is the existence of anomalies in cryptocurrencies, which have a different financial structure from that of traditional financial markets. This study expands the literature by focusing on artificial neural networks to compare different currencies of the cryptocurrency market, which is hard to predict. It aims to investigate the existence of the day-of-the-week anomaly in cryptocurrencies with feedforward artificial neural networks as an alternative to traditional methods. An artificial neural network is an effective approach that can model the nonlinear and complex behavior of cryptocurrencies. On October 6, 2021, Bitcoin (BTC), Ethereum (ETH), and Cardano (ADA), which are the top three cryptocurrencies in terms of market value, were selected for this study. The data for the analysis, consisting of the daily closing prices for BTC, ETH, and ADA, were obtained from the Coinmarket.com website from January 1, 2018 to May 31, 2022. The effectiveness of the established models was tested with mean squared error, root mean squared error, mean absolute error, and Theil’s U1, and $${R}_{OOS}^{2}$$ R OOS 2 was used for out-of-sample. The Diebold–Mariano test was used to statistically reveal the difference between the out-of-sample prediction accuracies of the models. When the models created with feedforward artificial neural networks are examined, the existence of the day-of-the-week anomaly is established for BTC, but no day-of-the-week anomaly for ETH and ADA was found.

show abstract

Section: Discussionsupporting

confidence: 93%

Section: Literaturementioning

confidence: 99%

Artificial neural network analysis of the day of the week anomaly in cryptocurrencies

et al. 2023

View full text Add to dashboard Cite

show abstract

“…By using an investment strategy based on this effect, higher returns were achieved than by making random investments over the sample period (2013)(2014)(2015)(2016)(2017). Robiyanto et al (2019), on the other hand, argued that investing in BTC at the end of January and selling towards the end of February is advisable, while Mondays, Wednesdays, and Thursdays hold the potential for higher returns in the case of day investors. Regarding LTC, there is significant positive return potential for investors in February.…”

Section: Literature Reviewmentioning

confidence: 99%

Day-of-the-Week and Month-of-the-Year Effects in the Cryptocurrency Market

Kahraman,

Kök

2024

MAKU IIBFD

View full text Add to dashboard Cite

This study examines the day-of-the-week (DoW) and month-of-the-year (MoY) effects in the cryptocurrency market, with a focus on Bitcoin (BTC) and Ethereum (ETH). Due to the absence of a specific closing time in the cryptocurrency market, the closing time of the daily data is taken as 23:59 UTC. Initially, an appropriate volatility model for the cryptocurrency market is established using the GARCH, EGARCH, and TGARCH models. The most appropriate model for BTC is ARMA(1,0)-EGARCH(1,1) and ARMA(1,0)-GARCH(1,1) for ETH. The results of the analysis indicate a leverage effect in the cryptocurrency market, where negative shocks cause a more significant increase in volatility than positive shocks. Based on this volatility structure, the DoW and MoY are analyzed. For BTC, returns on other days are lower compared to Mondays. However, for ETH, returns on Thursdays are lower than those on Mondays. In terms of volatility, both BTC and ETH show that the highest volatility occurs on Mondays. For the MoY effect, neither BTC nor ETH don’t exhibit a significant effect in the mean equation. Nevertheless, the variance equation indicates that January has higher volatility compared to other months, indicating the presence of a MoY effect in terms of volatility.

show abstract

“…Mata uang kripto ataupun cryptocurrency yang maksudnya suatu perwujudan dari terdapatnya pertumbuhan suatu teknologi yang mempunyai serangkaian kode kriptografi. Kode tersebut bisa dibangun sehingga kode tersebut bisa ditaruh dalam suatu fitur pc (Robiyanto et al, 2019) Kementerian Perdagangan (Kemendag) mencatat jumlah investor aset kripto (cryptocurrency) termasuk bitcoin, dogecoin, ethereum dkk hingga Mei tahun ini sudah menembus 6,5 juta pengguna di Indonesia, dengan nilai transaksi menembus Rp 370 triliun..Besaran angka tersebut sudah melebihi jumlah investor pasar modal di Bursa Efek Indonesia (BEI) kendati jumlah investor pasar modal juga masih terus menunjukkan tren peningkatan. Sampai dengan Februari 2021, BEI mencatat jumlah investor pasar modal mencapai 4,5 juta, naik 16,35% atau bertambah 634.000 investor baru dari posisi akhir tahun 2020.…”

Section: Pendahuluanunclassified

“…Tidak seperti mata uang tradisional yang dikeluarkan oleh bank sentral, Bitcoin tidak memiliki otoritas pusat dan tidak ada pihak yang mengendalikannya (Yeni & Kumala, 2020). Alih-alih mengandalkan otoritas pusat untuk memantau, memverifikasi dan menyetujui transaksi dan mengelola pasokan uang, Bitcoin didukung oleh jaringan komputer peer-to-peer (Robiyanto et al, 2019).…”

Section: Blockchainunclassified

Analisis Volatilitas Cryptocurrency Pada Sebelum Pandemi Dan Pada Saat Pandemi Covid 19 Dengan Metode Return Pada Bitcoin Dan Ethereum

Kuncara¹,

Anugrah

2023

keuang. dan. bisnis.

View full text Add to dashboard Cite

Cryptocurrencies like Bitcoin, Ethereum and are high volatility digital commodities, so using them as an alternative to trading investments is very dangerous. Volatility analysis, portfolio formation, and implementation forecasts need to be carried out to minimize risk levels and risk management to help investors/traders make decisions. If you estimate, its use is suitable for analyzing the returns and volatility of cryptocurrencies. The Metode used in this study are methods of converting data into returns, detecting constancy with the ADF test, and normality testing with the JarqueBera test. The result of this study is that there are differences in the rate of return on bitcoin and ethereum coins every year, in these two crypto coins have experienced a very significant increase from before the covid 19 pandemic to covid 19. The result of this study is that there are differences in the rate of return on bitcoin and ethereum coins every year, in these two crypto coins have experienced a very significant increase from before the covid 19 pandemic to covid 19.

show abstract

Examining the day-of-the-week-effect and the-month-of-the-year-effect in cryptocurrency market

Cited by 12 publications

References 15 publications

Artificial neural network analysis of the day of the week anomaly in cryptocurrencies

Artificial neural network analysis of the day of the week anomaly in cryptocurrencies

Day-of-the-Week and Month-of-the-Year Effects in the Cryptocurrency Market

Analisis Volatilitas Cryptocurrency Pada Sebelum Pandemi Dan Pada Saat Pandemi Covid 19 Dengan Metode Return Pada Bitcoin Dan Ethereum

Contact Info

Product

Resources

About