Bitcoin pricing: impact of attractiveness variables

Neves, Rodrigo Hakim das

doi:10.1186/s40854-020-00176-3

Cited by 32 publications

(20 citation statements)

References 26 publications

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“…(2018) also find Google searches as a significant factor in determining bitcoin prices. Hakim das Neves (2020) have similar findings, suggesting that the bitcoin price increase is significantly affected by the number of Google searches throughout the world. Hayes (2016) establishes a strong evidence toward energy consumption being a driver of bitcoin value.…”

Section: Literature Reviewsupporting

confidence: 54%

Short-run and long-run determinants of bitcoin returns: transnational evidence

Dubey

2022

RBF

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PurposeBitcoin has emerged as a phenomenal asset earning abnormal profits. However, the factors with predictability power over its price are not widely studied. Therefore, this study aims to explore the factors that determine bitcoin prices. The analysis explores the determinants belonging to four categories – macro economic, financial, technical and fundamental factors.Design/methodology/approachThe study employs random effects regression on the panel data of five countries. Then Granger causality test is applied on the time series of all the variables. Lastly, diagnostic tests are conducted to confirm the findings to be robust and reliable.FindingsThe findings suggest that oil price, bitcoin supply, trading volume and market capitalization significantly impact the price of bitcoin in the long run. In short run, bitcoin returns are only caused by oil price and market capitalization. Interestingly, bitcoin returns influence its attractiveness to investors, market capitalization, S&P 500 returns and trading volume, in the short run.Practical implicationsThe technical analysis is found to be redundant in the short run. In the long run, technical as well as fundamental analysis are useful. The bitcoin is found to be a good diversification tool as it has no linkages with the stock markets and gold market. It is also an inflationary hedger owing its limited supply.Originality/valueThe studies on cryptocurrency market have not conducted the analysis across countries. This study captures the cross-sectional effects along with time effects. The study also includes 17 variables belonging to four categories.

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Section: Literature Reviewsupporting

confidence: 54%

Short-run and long-run determinants of bitcoin returns: transnational evidence

Dubey

2022

RBF

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“…Studies also found evidence of micro or macro fundamental factors that affect Bitcoin price. For example, Neves [42] suggested that investment attractiveness had a prominent role in Bitcoin price formation, while other researchers [3,34,43,44] argued the stock market, exchange rate, gold, oil, Economic Policy Uncertainty (EPU), and the Geopolitical Risk Index, etc.…”

Section: Literature Reviewmentioning

confidence: 99%

Investor attention and cryptocurrency: Evidence from the Bitcoin market

Zhu

Zhang

et al. 2021

PLoS ONE

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This paper adds to the growing literature of cryptocurrency and behavioral finance. Specifically, we investigate the relationships between the novel investor attention and financial characteristics of Bitcoin, i.e., return and realized volatility, which are the two most important characteristics of one certain asset. Our empirical results show supports in the behavior finance area and argue that investor attention is the granger cause to changes in Bitcoin market both in return and realized volatility. Moreover, we make in-depth investigations by exploring the linear and non-linear connections of investor attention on Bitcoin. The results indeed demonstrate that investor attention shows sophisticated impacts on return and realized volatility of Bitcoin. Furthermore, we conduct one basic and several long horizons out-of-sample forecasts to explore the predictive ability of investor attention. The results show that compared with the traditional historical average benchmark model in forecasting technologies, investor attention improves prediction accuracy in Bitcoin return. Finally, we build economic portfolios based on investor attention and argue that investor attention can further generate significant economic values. To sum up, investor attention is a non-negligible pricing factor for Bitcoin asset.

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“…It was suggested in [23] that fundamental factors such as real use in transactions and money supply affect the long-term price of Bitcoin, and investors' interest in cryptocurrency reinforces this phenomenon. In [24], Google search term queries were used on Bitcoin to reveal that global interest in Bitcoin precedes price increases; in contrast, prices fall when fear of market collapse increases. In [25], it was found that public interest and Bitcoin prices had a high correlation.…”

Section: Factors Affecting Changes In the Price Of Bitcoinmentioning

confidence: 99%

Predicting Bitcoin Trends Through Machine Learning Using Sentiment Analysis with Technical Indicators

Jung¹,

Lee²,

Lee³

et al. 2023

Computer Systems Science and Engineering

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Predicting Bitcoin price trends is necessary because they represent the overall trend of the cryptocurrency market. As the history of the Bitcoin market is short and price volatility is high, studies have been conducted on the factors affecting changes in Bitcoin prices. Experiments have been conducted to predict Bitcoin prices using Twitter content. However, the amount of data was limited, and prices were predicted for only a short period (less than two years). In this study, data from Reddit and LexisNexis, covering a period of more than four years, were collected. These data were utilized to estimate and compare the performance of the six machine learning techniques by adding technical and sentiment indicators to the price data along with the volume of posts. An accuracy of 90.57% and an area under the receiver operating characteristic curve value (AUC) of 97.48% were obtained using the extreme gradient boosting (XGBoost). It was shown that the use of both sentiment index using valence aware dictionary and sentiment reasoner (VADER) and 11 technical indicators utilizing moving average, relative strength index (RSI), stochastic oscillators in predicting Bitcoin price trends can produce significant results. Thus, the input features used in the paper can be applied on Bitcoin price prediction. Furthermore, this approach allows investors to make better decisions regarding Bitcoin-related investments.

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Bitcoin pricing: impact of attractiveness variables

Cited by 32 publications

References 26 publications

Short-run and long-run determinants of bitcoin returns: transnational evidence

Short-run and long-run determinants of bitcoin returns: transnational evidence

Investor attention and cryptocurrency: Evidence from the Bitcoin market

Predicting Bitcoin Trends Through Machine Learning Using Sentiment Analysis with Technical Indicators

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