☆ 4.7 Article

Semi-strong efficient market of Bitcoin and Twitter: An analysis of semantic vector spaces of extracted keywords and light gradient boosting machine models

INTERNATIONAL REVIEW OF FINANCIAL ANALYSIS (2023)

相关参考文献

注意：仅列出部分参考文献，下载原文获取全部文献信息。

Article Business, Finance

The emotional cost-of-carry: Chinese investor sentiment and equity index futures basis

Song Cao et al.

Summary: This study examines the impact of investor sentiment on the basis changes of China's stock index futures. The findings suggest that Chinese investor sentiment plays a significant role in driving abnormal fluctuations in the basis of China's stock index futures, especially in specific circumstances.

CHINA FINANCE REVIEW INTERNATIONAL (2022)

添加到收藏夹

Article Business, Finance

An index of cryptocurrency environmental attention (ICEA)

Yizhi Wang et al.

Summary: This paper introduces a new index, ICEA, to capture the relative extent of media discussions surrounding the environmental impact of cryptocurrencies. The findings suggest that ICEA has a significant positive relationship with cryptocurrency indices, volatility index, Brent crude oil, and Bitcoin, and a significant negative relationship with global economic policy uncertainty and global temperature uncertainty. The paper also highlights the importance of considering the broader impacts of cryptocurrency environmental concerns on market volatility, uncertainty, and environmental sustainability.

CHINA FINANCE REVIEW INTERNATIONAL (2022)

添加到收藏夹

Article Business, Finance

The cryptocurrency uncertainty index

Brian M. Lucey et al.

Summary: The Cryptocurrency Uncertainty Index (UCRY) has been developed based on news coverage, capturing uncertainty in cryptocurrency price and policy. The index exhibits distinct movements around major events in the cryptocurrency space, and can be used for academic, policy, and practice-driven research beyond Bitcoin.

FINANCE RESEARCH LETTERS (2022)

添加到收藏夹

Article Economics

Twitter and market efficiency in energymarkets: Evidence using LDA clustered topic extraction

Efstathios Polyzos et al.

Summary: This article examines market efficiency in energy markets using Twitter data, finding differences in information topics between increasing and decreasing markets, and validating classifier accuracy in predicting market movements.

ENERGY ECONOMICS (2022)

添加到收藏夹

Article Computer Science, Information Systems

Twitter Attribute Classification With Q-Learning on Bitcoin Price Prediction

Sattarov Otabek et al.

Summary: This paper focuses on predicting the price of Bitcoin based on people's opinions on Twitter. The authors collect Bitcoin-related tweets and categorize them into four groups based on tweet attributes. They find that tweets posted by users with the most followers have the greatest impact on future prices. Utilizing these tweets leads to higher prediction accuracy and significant reductions in time and CPU consumption compared to traditional methods.

IEEE ACCESS (2022)

添加到收藏夹

Article Economics

Bitcoin price manipulation: evidence from intraday orders and trades

Bill Hu et al.

Summary: We analyze a total of 519.4 million Bitcoin orders placed on the Gemini Exchange from January 2016 to August 2019 and discover that limit orders dominate at 99.92%. We provide order-based evidence of price manipulation during the Bitcoin bubble in late 2017, with the number of market orders significantly exceeding the overall daily average. The observed changes in prices and liquidity satisfy the criteria outlined in Kyle and Viswanathan (2008) for defining price manipulation, and we also find a significant increase in market order imbalance associated with the modeled price manipulations in Jarrow, Protter, and Roch (2012).

APPLIED ECONOMICS LETTERS (2022)

添加到收藏夹

Article Economics

All the frequencies matter in the Bitcoin market: an efficiency analysis

David Vidal-Tomas

Summary: The study examines the efficiency of Bitcoin at different frequencies, showing that Bitcoin has become more efficient over time regardless of the frequency. Daily data has been the most efficient since 2016, while 1 min and weekly data are the least efficient. These findings are important for investors and scholars to identify profitable frequencies and emphasize the significance of analyzing different frequencies rather than just daily data.

APPLIED ECONOMICS LETTERS (2022)

添加到收藏夹

Article Business, Finance

An investigation of cryptocurrency data: the market that never sleeps

D. Vidal-Tomas

Summary: This paper delves into the adequacy of data in the cryptocurrency market, highlighting the significance of data processing by specialized crypto firms.

QUANTITATIVE FINANCE (2021)

添加到收藏夹

Article Business, Finance

Investor attention and bitcoin liquidity: Evidence from bitcoin tweets

Hyungeun Choi

Summary: This study uses high-frequency data and the number of tweets to investigate the real-time effects of tweets on Bitcoin liquidity, finding that tweets have a significant impact on Bitcoin liquidity. The study shows that an increase in the number of tweets can improve Bitcoin liquidity in the short term, but the positive impact weakens over time.

FINANCE RESEARCH LETTERS (2021)

添加到收藏夹

Article Business, Finance

Calendar effects in Bitcoin returns and volatility

Harald Kinateder et al.

Summary: The study found no evidence of classic day-of-the-week effect and Halloween calendar anomaly in Bitcoin returns, but there is a significant decrease in risk over the weekend with intensified volatility at the beginning of the week. Additionally, supporting evidence was found for a reverse January effect and a substantial drop in investors' risk in September.

FINANCE RESEARCH LETTERS (2021)

添加到收藏夹

Review Business, Finance

What do we know about cryptocurrency? Past, present, future

Mohammed Sawkat Hossain

Summary: This study conducts a systematic review analysis on cryptocurrency using a quali-quantitative approach known as meta-literature review, aiming to identify the current state, prospects, challenges, trends, and future research avenues. The findings highlight the distinctive features of cryptocurrency market and suggest potential research areas for further exploration. The study contributes to enhancing knowledge on digital finance, providing important investment implications for various stakeholders and shedding light on new investment opportunities in the global market.

CHINA FINANCE REVIEW INTERNATIONAL (2021)

添加到收藏夹

Article Economics

WHERE DO WE STAND IN CRYPTOCURRENCIES ECONOMIC RESEARCH? A SURVEY BASED ON HYBRID ANALYSIS

Aurelio F. Bariviera et al.

Summary: This survey aims to provide an updated state of the art in cryptocurrency economic literature by utilizing a dual analysis method, consisting of bibliometric examination and literature review. The methodology offers a comprehensive view of the research landscape and classifies the mounting research produced in a relatively short time span.

JOURNAL OF ECONOMIC SURVEYS (2021)

添加到收藏夹

Article Business, Finance

A critical investigation of cryptocurrency data and analysis

C. Alexander et al.

QUANTITATIVE FINANCE (2020)

添加到收藏夹

Article Computer Science, Information Systems

YAKE! Keyword extraction from single documents using multiple local features

Ricardo Campos et al.

INFORMATION SCIENCES (2020)

添加到收藏夹

Article Social Issues

Twitter data analytical methodology development for prediction of start -up firms' social media marketing level

Sang Hoon Jung et al.

TECHNOLOGY IN SOCIETY (2020)

添加到收藏夹

Article Business, Finance

The predictive power of public Twitter sentiment for forecasting cryptocurrency prices

Olivier Kraaijeveld et al.

JOURNAL OF INTERNATIONAL FINANCIAL MARKETS INSTITUTIONS & MONEY (2020)

添加到收藏夹

Article Business, Finance

What determines bitcoin exchange prices? A network VAR approach

Paolo Giudici et al.

FINANCE RESEARCH LETTERS (2019)

添加到收藏夹

Article Economics

Does twitter predict Bitcoin?

Dehua Shen et al.

ECONOMICS LETTERS (2019)

添加到收藏夹

Article Business, Finance

Efficiency, multifractality, and the long-memory property of the Bitcoin market: A comparative analysis with stock, currency, and gold markets

Khamis Hamed Al-Yahyaee et al.

FINANCE RESEARCH LETTERS (2018)

添加到收藏夹

Article Economics

Long Memory Interdependency and Inefficiency in Bitcoin Markets

Eng-Tuck Cheah et al.

ECONOMICS LETTERS (2018)

添加到收藏夹

Article Business, Finance

Does social network sentiment influence the relationship between the S&P 500 and gold returns?

Juan Pineiro-Chousa et al.

INTERNATIONAL REVIEW OF FINANCIAL ANALYSIS (2018)

添加到收藏夹

Article Business, Finance

Using sentiment analysis to predict interday Bitcoin price movements

Vytautas Karalevicius et al.

JOURNAL OF RISK FINANCE (2018)

添加到收藏夹

Article Economics

Informational efficiency of Bitcoin-An extension

Aviral Kumar Tiwari et al.

ECONOMICS LETTERS (2018)

添加到收藏夹

Article Business, Finance

Semi-strong efficiency of Bitcoin

David Vidal-Tomas et al.

FINANCE RESEARCH LETTERS (2018)

添加到收藏夹

Article Business, Finance

Time-varying long-term memory in Bitcoin market

Jiang Yonghong et al.

FINANCE RESEARCH LETTERS (2018)

添加到收藏夹

Article Business, Finance

Can Twitter Help Predict Firm-Level Earnings and Stock Returns?

Eli Bartov et al.

ACCOUNTING REVIEW (2018)

添加到收藏夹

Article Economics

How investible is Bitcoin? Analyzing the liquidity and transaction costs of Bitcoin markets

Anne H. Dyhrberg et al.

ECONOMICS LETTERS (2018)

添加到收藏夹

Article Economics

On the inefficiency of Bitcoin

Saralees Nadarajah et al.

ECONOMICS LETTERS (2017)

添加到收藏夹

Article Economics

The inefficiency of Bitcoin revisited: A dynamic approach

Aurelio F. Bariviera

ECONOMICS LETTERS (2017)

添加到收藏夹

Article Multidisciplinary Sciences

Predicting Fluctuations in Cryptocurrency Transactions Based on User Comments and Replies

Young Bin Kim et al.

PLOS ONE (2016)

添加到收藏夹

Article Economics

The inefficiency of Bitcoin

Andrew Urquhart

ECONOMICS LETTERS (2016)

添加到收藏夹

Article Business, Finance

Trade the tweet: Social media text mining and sparse matrix factorization for stock market prediction

Andrew Sun et al.

INTERNATIONAL REVIEW OF FINANCIAL ANALYSIS (2016)

添加到收藏夹

Article Computer Science, Information Systems

Using Twitter to Predict the Stock Market Where is the Mood Effect?

Michael Nofer et al.

BUSINESS & INFORMATION SYSTEMS ENGINEERING (2015)

添加到收藏夹

Article Economics

Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin

Eng-Tuck Cheah et al.

ECONOMICS LETTERS (2015)

添加到收藏夹

Article Economics

Crypto-currency bubbles: an application of the Phillips-Shi-Yu (2013) methodology on Mt. Gox bitcoin prices

Adrian (Wai-Kong) Cheung et al.

APPLIED ECONOMICS (2015)

添加到收藏夹

Article Multidisciplinary Sciences

The digital traces of bubbles: feedback cycles between socio-economic signals in the Bitcoin economy

David Garcia et al.

JOURNAL OF THE ROYAL SOCIETY INTERFACE (2014)

添加到收藏夹

Article Business, Finance

The Role of Dissemination in Market Liquidity: Evidence from Firms' Use of Twitter™

Elizabeth Blankespoor et al.

ACCOUNTING REVIEW (2014)

添加到收藏夹

Article Computer Science, Interdisciplinary Applications

Twitter mood predicts the stock market

Johan Bollen et al.

JOURNAL OF COMPUTATIONAL SCIENCE (2011)

添加到收藏夹

Article Business, Finance

Predicting the bear stock market: Macroeconomic variables as leading indicators

Shiu-Sheng Chen

JOURNAL OF BANKING & FINANCE (2009)

添加到收藏夹

Article Physics, Multidisciplinary

Algorithmic complexity theory and the relative efficiency of financial markets

R. Giglio et al.

EPL (2008)

添加到收藏夹

Editorial Material Computer Science, Information Systems

User-Generated Content Introduction

John Krumm et al.

IEEE PERVASIVE COMPUTING (2008)

添加到收藏夹

Article Business, Finance

Valuation ratios and price deviations from fundamentals

Jerry Coakley et al.

JOURNAL OF BANKING & FINANCE (2006)

添加到收藏夹

© Peeref 2019-2024. All rights reserved.