Journal articles on the topic 'Bitcoin trend App'

Objective.Analyze the utility of an algorithmic trading system based on artificial intelligence models that uses Google Trends as predictor of dozens of financial terms, to predict the evolution of S&P 500 index and Bitcoin. Methodology. A trading algorithmic system has been developed that opens a weekly long or short position in S&P 500 and Bitcoin, following the signals issued by an artificial intelligence model that uses Google Tends as predictor for next week market trend. The artificial intelligence models were trained using weekly data from 2013 to 2018 and have been tested in a prospective way from February 2018 to December 2021. Results. Google Trends is a good predictor for global investors’ mood. The artificial intelligence algorithmic trading systems tested in a prospective way has been profitable. Trading strategies based on investors’ mood have been more accurate and profitable for Bitcoin (beating the evolution of the cryptocurrency) than for S&P 500 (not beating the index). Conclusions. This evidence opens a new field for the investigation of trading systems based on big data instead of Chartism. Although there are many trading systems based on Chartism, there are no artificial intelligence trading syste

In this paper we analyze the existence of cointegrating relationships between Bitcoin, S&P 500, and the quantity of money M2. We perform our analysis with and without applying time warping pre-processing. In all cases we find strong evidence that, in the period 2016-2021 the three time series show two cointegrating relationships and therefore share a common stochastic trend. In addition, a low correlation between Bitcoin and S&P 500 is detected. These finding justify the increased interest of investors in Bitcoin as an alternative asset class. The economic interpretation is that the stock valuation is primarily determined by financial phenomena, in particular the availability of large quantity of money. Money supporting investment is due both to the actions of Quantitative Easing and to the exchange of creditor/debtor role that took place between households and firms. The price of both Bitcoin and stocks is increasingly influenced by the amount of money in circulation and follows the same stochastic trend.

Bitcoin’s market structure underwent a fundamental and irreversible transformation following the 2024 regulatory approval and launch of spot Exchange-Traded Funds (ETFs) in the United States. This event catalyzed an unprecedented wave of institutional adoption, signaling the asset's maturation from a fringe, retail-driven speculative vehicle into an emergent institutional-grade macro-asset. This study moves beyond traditional cyclical models, which are predicated on historical, pre-institutional market dynamics, to analyze Bitcoin's valuation within this profoundly evolved landscape. The primary objective is to project the potential price apex for Bitcoin in the 2024-2025 market cycle by developing and applying a transparent, replicable, and comprehensive multi-factor analytical framework. A multi-factorial, longitudinal analysis was conducted using a combination of publicly available data and simulated datasets from Q1 2022 to Q2 2025. The model is built upon a structured, semi-quantitative framework designed to synthesize three core analytical pillars: (1) Macroeconomic Environment, quantitatively assessing the impact of Federal Reserve interest rate policy, US Dollar Index (DXY) dynamics, and inflation trends through correlation analysis and sensitivity modeling. (2) On-Chain Intelligence, utilizing a suite of metrics from primary sources like Glassnode, including MVRV Z-Score, LTH-SOPR, and Illiquid Supply growth, while critically evaluating the continued validity of their historical thresholds. (3) Market & Flow Dynamics, which integrates technical analysis with a rigorous, quantitative assessment of spot ETF demand versus daily new supply, moving beyond subjective interpretations of price charts. A transparent weighting rubric was developed to integrate the findings from each pillar, mitigating subjective bias and ensuring the analytical synthesis is replicable. The synthesis of the model's components revealed a powerful confluence of bullish factors projected to intensify through late 2024 and into 2025. The Macroeconomic pillar scored moderately positive, forecasting a probable shift to monetary easing. The On-Chain pillar registered a strongly positive score, driven by a profound and persistent supply shock, evidenced by record illiquid supply growth and sustained exchange outflows, indicating strong holder conviction. The Market & Flow Dynamics pillar also scored strongly positive, with institutional demand via ETFs consistently outstripping newly mined supply by a significant multiple. The model's base-case scenario, derived from the weighted synthesis of these pillars, projects a Bitcoin price apex in the range of $150,000 to $200,000, with the most probable timing for this peak occurring between Q4 2024 and Q2 2025. In conclusion, the findings indicate that the 2024-2025 Bitcoin market cycle is fundamentally distinct from its predecessors, primarily driven by a structural, institutional-led demand shock that interacts with, and is amplified by, traditional macroeconomic tailwinds and established cyclical patterns. The projected price apex reflects a market structure that has matured, with future cycles likely to be more influenced by global liquidity conditions than the halving event alone. This research provides a robust, transparent, and theoretically grounded framework for valuing Bitcoin in its new role within the global financial system and offers a template for future analysis of digital assets as they integrate with traditional finance.

This research is the first attempt to customize a trading system that is based on second order stochastic dominance (SSD) to five known cryptocurrencies’ daily data: Bitcoin, Ethereum, XRP, Binance Coin, and Cardano. Results show that our system can predict price trends of cryptocurrencies, trade them profitably, and in most cases outperform the buy and hold (B&H) simple strategy. Our system’s best performance was achieved trading XRP, Binance Coin, Ethereum, and Bitcoin. Although our system has also generated a positive net profit (NP) for Cardano, it failed to outperform the B&H strategy. For all currencies, the system better predicted long trends than short trends.

In this paper, we use Analytic Hierarchy Process (AHP) to determine the appropriate weights and establish a bull market and bear market judgment indicator and investment risk models. Secondly, the Autoregressive Integrated Moving Average model (ARIMA) is constructed to make the expected trend for the next five years, and the optimal asset portfolio of gold assets and bitcoin assets is constructed through quadratic programming, and the Dynamic Programming (DP) model is used to compare strategies between two trades. Finally, the rationality of the model calculation is verified by the test of Long-Short-Term Memory (LSTM).

This paper explores the growing perception of Bitcoin as “digital gold” by examining its economic characteristics, historical evolution, and role in modern investment strategies. While gold has long served as a safe-haven asset and store of value, Bitcoin, launched in 2009, is a relatively new and volatile digital asset. However, both share several core attributes: limited supply, difficulty of production, and their appeal in times of economic uncertainty. The study conducts a comparative analysis of Bitcoin and gold, focusing on shared traits such as scarcity, production effort, and store-of-value properties, while also highlighting key differences in tangibility, regulatory environment, volatility, and energy consumption. Empirical research from recent years suggests a shift in how investors perceive Bitcoin, particularly after 2017. Studies such as Zwick & Syed (2019) identify a structural transformation in the correlation between Bitcoin and gold, with the two assets now increasingly moving in parallel, especially during periods of financial turmoil. Despite these convergences, Bitcoin faces significant challenges. Its scalability limitations, legal uncertainties, high energy demands, and dependency on market-driven mining incentives raise questions about its long-term viability and security. Moreover, the fragmented regulatory landscape across jurisdictions hinders its adoption as a fully mature financial instrument. Yet, there are promising signs of market maturation, such as institutional adoption, improved financial infrastructure, and regulatory clarity in certain regions. Ultimately, the paper concludes that Bitcoin has not yet fully attained the status of digital gold, but current trends suggest a gradual convergence in that direction. If it succeeds in stabilizing its volatility, reducing environmental impact, and achieving global regulatory coherence, Bitcoin could become a complementary store of value to gold, playing an integral role in the evolving architecture of the digital financial economy.

<abstract> <p>This research attempts to fit a polynomial auto regression (PAR) model to intraday price data of four major cryptocurrencies and convert the model into a real-time profitable automated trading system. A PAR model was constructed to fit cryptocurrencies' behavior and to attempt to predict their short-term trends and trade them profitably. We used machine learning (ML) procedures enabling our system to train using minutes' data for six months and perform actual trading and reporting for the next six months. Results have shown that our system has dramatically outperformed the naive buy and hold (B & H) strategy for all four examined cryptocurrencies. Results show that our system's best performances were achieved trading Ethereum and Bitcoin and worse trading Cardano. The highest net profit (NP) for Bitcoin trades was 15.58%, achieved by using 67 minutes bars to form the prediction model, compared to −44.8% for the B & H strategy. Trading Ethereum, the system generated 16.98% NP, compared to −33.6% for the B & H strategy, 61 minutes bars. Moreover, the highest NPs achieved trading Binance Coin (BNB) and Cardano were 9.33% and 4.26%, compared to 0.28% and −41.8% for the B & H strategy, respectively. Furthermore, the system better predicted Ethereum and Cardano uptrends than downtrends while it better predicted Bitcoin and BNB downtrends than uptrends.</p> </abstract>

E-currency is a form of digital currency that employs encryption to safeguard transactions, limit the manufacture of new units, and verify asset transfers. Bitcoin exchange rates and returns are the primary subjects of this study. In order to measure volatility, the standard deviation of logarithmic returns is determined. This study used a special test to determine whether or not the data were normal. Findings of high volatility were also made using a plot, a statistical process control chart, and other methods. Normality test (casual test) has been investigated accordingly to approve and validate the results. The F-test has been considered as the main indicator for the validity of the results. It has been based on the F-value of 9.3. As well as the financial performance has been done using the time and currency with upper and lower limits. The maximum limit is 34 with a G-value of 0.34. Furthermore, market return-based e-currency has been investigated and analyzed using free and fixed limits for both main variables time and currency. According to these data, the greatest value is 23 in fixed limit circumstances, while it is 18.4 in broad trend cases. The financial performance-based ANP method has been examined using the ANP approach with return values for the currency. The upper limit reached 544 with 0.43 as a G-value. An increasing number of people are valuing volatility. Because of the present high level of volatility, investing in Bitcoin is seen as a high-risk endeavor. The purpose of this study is to assist investors in developing a strategy that maximizes returns while minimizing risk

This study aims to analyze the impact of news related to Central Bank Digital Currency (CBDC) on the stock and cryptocurrency markets in the United States. Using the Time-Varying Parameter Vector Autoregression (TVP-VAR) method, this study examines the responses of the S&P 500 index, the CBOE Volatility Index (VIX), Bitcoin trading volume, and Ethereum trading volume to CBDC news from January 2020 to December 2023. The results indicate that CBDC news has a positive effect on stock market prices, but its impact on market volatility is negligible. Furthermore, Bitcoin and Ethereum trading volumes exhibit a declining trend in response to the rapid development of CBDC news. Although CBDC development is still in its early stages, these findings provide insights into the potential influence of CBDC news on financial market behavior, particularly in shaping investor sentiment and digital asset trading patterns. The study suggests that policymakers and investors should closely monitor CBDC developments, as they may gradually affect the financial ecosystem. Future research should further explore the long-term effects of CBDCs on financial market stability and cryptocurrency adoption.

Research background: As humanity evolves, so do the new payment options. Today, one of the most popular and powerful electronic money is Bitcoin. Over time, virtual currency is becoming one of the most widely available and used means of payment. Purpose of the article: The aim of this paper is to analyse ATMs in post offices, focusing on virtual currency ATMs. The paper also includes an analysis of available ATMs for virtual currencies and a comparison of their capabilities. Methods: We compare three most important ATM manufacturers and their most used models. It examines the use of those ATMs in post offices in Slovakia and abroad. Paper also analyses the attitude of customers of Slovak Post towards the deployment of virtual currency ATMs at its branches (on a sample of 400 respondents). Findings & Value added: In the Slovak Republic postal services are offered by several companies (19 out of 24 providers responded to our questionnaire). Slovak Post is leading provider of distribution, communication, and payment services in Slovakia. Czech Post is an example of country where virtual currency ATMs were introduced but subsequently withdrawn from post offices. In turn, Austrian Post Office is an example of a country where this system still operates and expands. While Slovak market still lacks such a service in the postal business, these trends will adapt over time. The virtual currency ATMs we have in Slovakia, are not operated by postal enterprises.

This paper describes the construction of the short-term forecasting model of cryptocurrencies’ prices using machine learning approach. The modified model of Binary Auto Regressive Tree (BART) is adapted from the standard models of regression trees and the data of the time series. BART combines the classic algorithm classification and regression trees (C&RT) and autoregressive models ARIMA. Using the BART model, we made a short-term forecast (from 5 to 30 days) for the 3 most capitalized cryptocurrencies: Bitcoin, Ethereum and Ripple. We found that the proposed approach was more accurate than the ARIMA-ARFIMA models in forecasting cryptocurrencies time series both in the periods of slow rising (falling) and in the periods of transition dynamics (change of trend).

Oil, gas and food are essential for modern human life. The price fluctuation of these things will significantly affect the economy of the world. This essay discusses the price changes of energy, bulk food, and hedging financial assets against the backdrop of global uncertainty, influenced by geopolitical conflicts such as the Russia-Ukraine war and the Saudi oil renewal crisis, as well as factors like the COVID-19 pandemic and climate change. The prices of energy sources are highly volatile from geopolitical influences. The prices of bulk food commodities fluctuate around a baseline level, with specific trends varying by type of food. Hedging financial assets like gold and Bitcoin have seen gradual increases in price with some volatility. Companies develop their hedging strategies based on the prices of these derivatives, holding different quantities of risk assets and adjusting their asset holdings based on expectations of changes in the prices of these derivatives.

E-currency is a form of digital currency that employs encryption to safeguard transactions, limit the manufacture of new units, and verify asset transfers. Bitcoin exchange rates and returns are the primary subjects of this study. In order to measure volatility, the standard deviation of logarithmic returns is determined. This study used a special test to determine whether or not the data were normal. Findings of high volatility were also made using a plot, a statistical process control chart, and other methods. Normality test (casual test) has been investigated accordingly to approve and validate the results. The F-test has been considered as the main indicator for the validity of the results. It has been based on the F-value of 9.3. As well as the financial performance has been done using the time and currency with upper and lower limits. The maximum limit is 34 with a G-value of 0.34. Furthermore, market return-based e-currency has been investigated and analyzed using free and fixed limits for both main variables time and currency. According to these data, the greatest value is 23 in fixed limit circumstances, while it is 18.4 in broad trend cases. The financial performance-based ANP method has been examined using the ANP approach with return values for the currency. The upper limit reached 544 with 0.43 as a G-value. An increasing number of people are valuing volatility. Because of the present high level of volatility, investing in Bitcoin is seen as a high-risk endeavor. The purpose of this study is to assist investors in developing a strategy that maximizes returns while minimizing risk

Abstract The paper provides a comparative empirical study of predictability of cryptocurrency returns and prices using econometrically justified robust inference methods. We present robust econometric analysis of predictive regressions incorporating factors, which were suggested by Liu, Y., & Tsyvinski, A. (2018). Risks and returns of cryptocurrency. NBER working paper no. 24877; Liu, Y., & Tsyvinski, A. (2021). Risks and returns of cryptocurrency. The Review of Financial Studies, 34(6), 2689–2727, as useful predictors for cryptocurrency returns, including cryptocurrency momentum, stock market factors, acceptance of Bitcoin, and Google trends measure of investors’ attention. Due to inherent heterogeneity and dependence properties of returns and other time series in financial and crypto markets, we provide the analysis of the predictive regressions using both heteroskedasticity and autocorrelation consistent (HAC) standard-errors and also the recently developed t t -statistic robust inference approaches, Ibragimov, R., & Müller, U. K. (2010). t-statistic based correlation and heterogeneity robust inference. Journal of Business and Economic Statistics, 28, 453–468; Ibragimov, R., & Müller, U. K. (2016). Inference with few heterogeneous clusters. Review of Economics and Statistics, 98, 83–96. We provide comparisons of robust predictive regression estimates between different cryptocurrencies and their corresponding risk and factor exposures. In general, the number of significant factors decreases as we use more robust t-tests, and the t-statistic robust inference approaches appear to perform better than the t-tests based on HAC standard errors in terms of pointing out interpretable economic conclusions. The results in this paper emphasize the importance of the use of robust inference approaches in the analysis of economic and financial data affected by the problems of heterogeneity and dependence.

This article examines the role cryptographic methods play in protecting digital assets through blockchain systems, with a particular focus on their adjustment to contemporary challenges and technological trends. An endeavor is undertaken to systematize major cryptographic algorithms, their effective appraisal in data protection, and development prospects under quantum computing threats. The study is relevant because centralized systems increasingly depend on cryptography due to greater regulatory pressures and, above all, a need for security through secrecy. The scientific novelty lies in the detailed comparative analysis of the said methodology (hashing, digital signatures, zero-knowledge proofs) for cases relating to major blockchain platforms (Bitcoin, Ethereum, Zcash), which hence demonstrate varied approaches towards security provision. The study's methodological foundation consists of analyzing 13 sources, merging a qualitative examination of algorithms and ECDSA with zk-SNARKs with a quantitative assessment of their effectiveness. Hash functions and Merkle trees ensure data integrity while reducing the computational costs of verification; asymmetric cryptography and Zero-Knowledge Proofs guarantee authenticity and confidentiality for the function of the transaction. Main findings support that cryptography is the cornerstone technology for blockchain security, but it has to be tailored to meet new challenges. Development in post-quantum algorithms and the infusion of homomorphic encryption will soon become imperative for quantum threats. This paper strongly advocates hybrid solutions that would bring traditional ways merged with novelties, which will provide sustainability over time for digital assets. Thus, this article will be useful for Developers of Blockchain Systems, Cryptographers, Cybersecurity Experts, & Regulators willing to know how protection methods for digital assets evolve.

Libraries are actively exploring innovative methods to leverage advanced technological breakthroughs like Blockchain, driven by the rapid evolution of information technology. The inherent benefits of blockchain, including its decentralized, transparent, and safe data management capabilities, offer compelling solutions for various library operations. While Bitcoin remains a prominent application, libraries can harness Blockchain's underlying potential to significantly enhance efficiency and security across numerous facets of their services. This study delves into the multifaceted potential effects of blockchain technology on libraries. It meticulously examines possible applications, long-term benefits, and the critical significance of seamlessly integrating blockchain technology into existing library services. For instance, blockchain could revolutionize interlibrary loan systems by creating an immutable, tamper-proof record of every transaction, thereby drastically reducing administrative burdens, minimizing disputes over borrowed materials, and expediting the overall lending process. Furthermore, it offers a robust framework for enhanced intellectual property management for digital resources, ensuring that creators' rights are meticulously protected and providing transparent, auditable tracking of digital content usage. This level of verifiable provenance is particularly crucial for academic and research libraries managing vast collections of scholarly works. Ultimately, the objective is to move towards Blockchain-based library management systems that require less manual labor, thereby improving overall understanding, fostering creativity in service design, and streamlining operational efficiency. 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Purpose The purpose of this study is to examine Bitcoin's price behavior across market conditions, focusing on the influence of Bitcoin's historical prices, news sentiment and market indicators like oil prices, gold and the S&amp;P index. The authors also assess the stability of Bitcoin-inclusive hedging portfolios under different market conditions, for example, bearish, bullish and moderate market states. Design/methodology/approach This study uses the Quantile Autoregressive Distributed Lag model to explore the effects of different factors on Bitcoin's prices across various market situations. This method allows for a detailed analysis of historical trends, investor expectations and external market influences on Bitcoin's price movements and systematic stability. Findings Key findings reveal historical prices and investor expectations significantly influence Bitcoin in all market scenarios, with news sentiment exhibiting substantial volatility. This study indicates that oil prices have minimal impacts on Bitcoin, whereas gold is a stabilizing asset in bear markets, with the S&amp;P index influencing short-term fluctuations. At the same time, Bitcoin's volatility varies with market conditions, proving more efficient as a hedging tool in bear and stable markets than in bull ones. Originality/value This study highlights the intrinsic correlation between Bitcoin's prices, news sentiment and financial market indicators, enhancing understanding of Bitcoin's market dynamics. The authors demonstrate Bitcoin's weak direct correlation with commodities like oil, the stabilizing role of gold in crypto portfolios and the stock market's indirect effect on Bitcoin prices. By examining these factors' impacts across various market conditions, the findings offer strategies for investors to improve hedging and portfolio management in cryptocurrency markets.

PurposeThis study delves into Bitcoin’s return dynamics to address its pronounced volatility, particularly in extreme market conditions. We analyze a broad range of explanatory variables, including traditional financial indicators, innovative cryptocurrency-specific metrics and market sentiment gauges. We uniquely introduce the Conference Board Leading Economic Indicator (LEI) to the cryptocurrency research landscape.Design/methodology/approachWe employ quantile regression to examine Bitcoin’s daily and monthly returns. This approach captures timescale dependencies and evaluates the consistency of our findings across different market conditions. By conducting a thorough analysis of the entire return distribution, we aim to reveal how various factors influence Bitcoin’s behavior at different risk levels. The research incorporates a comprehensive set of explanatory variables to provide a holistic view of Bitcoin’s market dynamics. Additionally, by segmenting the study period, we assess the consistency of the results across diverse market regimes.FindingsOur results reveal that factors driving Bitcoin returns vary significantly across market conditions. For instance, during downturns, an increase in transaction volume is linked to lower Bitcoin returns, potentially indicating panic selling. When the market stabilizes, a positive correlation emerges, suggesting healthier ecosystem activity. Active addresses emerge as a key predictor of returns, especially during bearish phases, and sentiment indicators such as Wikipedia views reveal shifting investor optimism, depending on market trends. Monthly return analysis suggests Bitcoin might act as a hedge against traditional markets due to its negative correlation with the S&amp;P 500 during normal conditions.Practical implicationsThe study’s findings have significant implications for investors and policymakers. Understanding how different factors influence Bitcoin returns in varying market conditions can guide investment strategies and regulatory approaches.Originality/valueA novel contribution of this study is the identification of Bitcoin’s sensitivity to broader economic downturns as demonstrated by the negative correlation between LEI and returns. These insights not only deepen our understanding of Bitcoin market behaviour but also offer practical implications for investors, risk managers and policymakers navigating the evolving cryptocurrency landscape.

Abstract The structure and the number of bitcoin transactions encoded in the Blockchain reflect the behaviour of Bitcoin owners. &amp;#xD;Likewise, the formation of bullish and bearish trends in the crypto market reflects the behaviour of Bitcoin traders. &amp;#xD;Inspired by the above observations, in this work, we aim to assess whether human behaviour underlies some relationships between the Blockchain and the crypto market.&amp;#xD;To this end, we map the Blockchain to a spin-lattice whose configurations, representing the behaviour of Bitcoin owners, form ordered and disordered patterns.&amp;#xD;This approach allows us to obtain time series suitable to detect a causal relationship between the dynamics of the Blockchain and market trends of the Bitcoin and, in addition, to find that disordered patterns in the Blockchain precede Bitcoin panic selling. &amp;#xD;Results suggest that human behaviour, underlying Blockchain evolution and the crypto market, brings a fascinating connection between disorder and panic in Bitcoin dynamics to light.

This research investigates the strategic adoption of Bitcoin as a corporate asset in Indonesia, focusing on its potential as an inflation hedge and its impact on enhancing shareholder value. Employing a mixed-method approach combining qualitative interviews and the Analytical Hierarchy Process (AHP), the study explores the challenges, risks, and opportunities associated with integrating Bitcoin into corporate financial strategies. The findings reveal that risk mitigation emerges as the primary priority for companies considering Bitcoin adoption, underscoring the need for robust strategies such as investment diversification, hedging, and scenario analysis. Stakeholder acceptance, encompassing investors, regulators, and market sentiment, is identified as the second most crucial factor, highlighting the importance of a supportive regulatory environment and investor confidence. The research also highlights the significance of analyzing price trends and optimizing asset allocation strategies. The AHP analysis identifies the Strategic Diversification approach as the most preferred alternative, aligning with Modern Portfolio Theory principles. Additionally, the study addresses accounting and financial reporting challenges associated with Bitcoin adoption, emphasizing the need for clear guidance and standards. The implementation plan outlines key aspects such as infrastructure development, education initiatives, risk management frameworks, and regulatory collaboration to facilitate the responsible integration of Bitcoin into Indonesian corporate finance strategies.

The blockchain and cryptoasset sector, since coming to the attention of the mainstream business and financial markets during the bitcoin bull run of 2017, continues to accelerate and evolve rapidly. Decentralized finance (DeFi), a new iteration of what was previously referred to as open finance, has emerged as an innovative use case and service enabled by blockchain technology. As with any innovation or new tool, however, there remains a range of questions and considerations that will have to be addressed prior to wider adoption and utilization. This research attempts to contextualize the development of DeFi, frame it within the blockchain and cryptoasset sector, and explain potential obstacles and challenges to further development. Subsequent to this examination of DeFi trends, challenges, and opportunities, a potential framework for further development and implementation will be presented. Outlined and written in a manner approachable to both practitioners and academic users, this research should be used a springboard for further discussion, analysis, and progress.

Abstract This study adopts a Darwinian approach leveraging machine learning (ML) to analyze cryptocurrency returns and their interactions with traditional financial markets. Using a daily dataset from 2018 to 2023, the Random Forest model proved particularly effective in identifying key factors influencing cryptocurrency returns, including technology stock indices (NASDAQ), global equity indices (S&amp;P500, Eurostoxx600), commodity prices (gold, crude oil), and market sentiment (Google Trends). The analysis reveals consistent positive relationships between market sentiment and cryptocurrency returns, highlighting the crucial role of public interest in shaping long-term outcomes. Cryptocurrencies emerge as a distinct asset class with specific correlations to traditional markets and investor sentiment. The study provides strategic insights into understanding cryptocurrency behavior and integrating these dynamics into informed portfolio strategies. It emphasizes the importance of monitoring both traditional financial indices and market sentiment for investment decisions across various time horizons. JEL classification numbers: C58, G11, G15. Keywords: Crypto Assets, Bitcoin, Machine Learning, Investor Decisions.

Introduction In a 2019 report for the International Journal of Communication, Baym et al. positioned distributed blockchain ledger technology, and what would subsequently be referred to as Web3, as a convening technology. Riffing off Barnett, a convening technology “initiates and serves as the focus of a conversation that can address issues far beyond what it may ultimately be able to address itself” (403). The case studies for the Baym et al. research—early, aspirant projects applying the blockchain concept to music publishing and distribution—are described in the piece as speculations or provocations concerning music’s commercial and social future. What is convened in this era (pre-2017 blockchain music discourse and practice) is the potential for change: a type of widespread, broadly discussed, reimagination of the 21st-century music industries, productive precisely because near-future applications suggest the realisation of what Baym et al. call dreams. In this article, we aim to examine the Web3 music field as it lies some years later. Taking the latter half of 2021 as our subject, we present a survey of where music then resided within Web3, focussing on how the dreams of Baym et al. have morphed and evolved, and materialised and declined, in the intervening years. By investigating the discourse and functionality of 2021’s current crop of music NFTs—just one thread of music Web3’s far-reaching aspiration, but a potent and accessible manifestation nonetheless—we can make a detailed analysis of concept-led application. Volatility remains throughout the broader sector, and all of the projects listed here could be read as conditionally short-term and untested, but what they represent is a series of clearly evolved case studies of the dream, rich precisely because of what is assumed and disregarded. WTF Is an NFT? Non-fungible tokens inscribe indelible, unique ledger entries on a blockchain, detailing ownership of, or rights associated with, assets that exist off-chain. Many NFTs take the form of an ERC-721 smart-contract that functions as an indivisible token on the Ethereum blockchain. Although all ERC-721 tokens are NFTs, the inverse is not true. Similar standards exist on other blockchains, and bridges allow these tokens to be created on alternative networks such as Polygon, Solana, WAX, Cardano and Tezos. The creation (minting) and transfer of ownership on the Ethereum network—by far the dominant chain—comes with a significant and volatile transaction cost, by way of gas fees. Thus, even a “free” transaction on the main NFT network requires a currency and time investment that far outweighs the everyday routines of fiat exchange. On a technical level, the original proposal for the ERC-721 standard refers to NFTs as deeds intended to represent ownership of digital and physical assets like houses, virtual collectibles, and negative value assets such as loans (Entriken et al.). The details of these assets can be encoded as metadata, such as the name and description of the asset including a URI that typically points to either a file somewhere on the Internet or a file hosted via IPFS, a decentralised peer-to-peer hosting network. As noted in the standard, while the data inscribed on-chain are immutable, the asset being referred to is not. Similarly, while each NFT is unique, multiple NFTs could, in theory, point to a single asset. In this respect ERC-721 tokens are different from cryptocurrencies and other tokens like stable-coins in that their value is often contingent on their accurate and ongoing association with assets outside of the blockchain on which they are traded. Further complicating matters, it is often unclear if and how NFTs confer ownership of digital assets with respect to legislative or common law. NFTs rarely include any information relating to licencing or rights transfer, and high-profile NFTs such as Bored Ape Yacht Club appear to be governed by licencing terms held off-chain (Bored Ape Yacht Club). Finally, while it is possible to inscribe any kind of data, including audio, into an NFT, the ERC-721 standard and the underpinning blockchains were not designed to host multimedia content. At the time of writing, storing even a low-bandwidth stereo audio file on the ethereum network appears cost-prohibitive. This presents a challenge for how music NFTs distinguish themselves in a marketplace dominated by visual works. The following sections of this article are divided into what we consider to be the general use cases for NFTs within music in 2021. We’ve designated three overlapping cases: audience investment, music ownership, and audience and business services. Audience Investment Significant discourse around NFTs focusses on digital collectibles and artwork that are conceptually, but not functionally, unique. Huge amounts of money have changed hands for specific—often celebrity brand-led—creations, resulting in media cycles of hype and derision. The high value of these NFTs has been variously ascribed to their high novelty value, scarcity, the adoption of NFTs as speculative assets by investors, and the lack of regulatory oversight allowing for price inflation via practices such as wash-trading (Madeline; Das et al.; Cong et al.; Le Pennec, Fielder, and Ante; Fazil, Owfi, and Taesiri). We see here the initial traditional split of discourse around cultural activity within a new medium: dual narratives of utopianism and dystopianism. Regardless of the discursive frame, activity has grown steadily since stories reporting the failure of Blockchain to deliver on its hype began appearing in 2017 (Ellul). Early coverage around blockchain, music, and NFTs echoes this capacity to leverage artificial scarcity via the creation of unique digital assets (cf Heap; Tomaino). As NFTs have developed, this discourse has become more nuanced, arguing that creators are now able to exploit both ownership and abundance. However, for the most part, music NFTs have essentially adopted the form of digital artworks and collectibles in editions ranging from 1:1 or 1:1000+. Grimes’s February 2021 Mars NFT pointed to a 32-second rotating animation of a sword-wielding cherubim above the planet Mars, accompanied by a musical cue (Grimes). Mars sold 388 NFTs for a reported fixed price of $7.5k each, grossing $2,910,000 at time of minting. By contrast, electronic artists Steve Aoki and Don Diablo have both released 1:1 NFT editions that have been auctioned via Sotheby’s, Superrare, and Nifty Gateway. Interestingly, these works have been bundled with physical goods; Diablo’s Destination Hexagonia, which sold for 600 Eth or approximately US$1.2 million at the time of sale, proffered ownership of a bespoke one-hour film hosted online, along with “a unique hand-crafted box, which includes a hard drive that contains the only copy of the high-quality file of the film” (Diablo). Aoki’s Hairy was much less elaborate but still promised to provide the winner of the $888,888 auction with a copy of the 35-second video of a fur-covered face shaking in time to downbeat electronica as an Infinite Objects video print (Aoki). In the first half of 2021, similar projects from high-profile artists including Deadmau5, The Weekend, Snoop Dogg, Eminem, Blondie, and 3Lau have generated an extraordinary amount of money leading to a significant, and understandable, appetite from musicians wanting to engage in this marketplace. Many of these artists and the platforms that have enabled their sales have lauded the potential for NFTs to address an alleged poor remuneration of artists from streaming and/or bypassing “industry middlemen” (cf. Sounds.xyz); the millions of dollars generated by sales of these NFTs presents a compelling case for exploring these new markets irrespective of risk and volatility. However, other artists have expressed reservations and/or received pushback on entry into the NFT marketplace due to concerns over the environmental impact of NFTs; volatility; and a perception of NFT markets as Ponzi schemes (Poleg), insecure (Goodin), exploitative (Purtill), or scammy (Dash). As of late 2021, increased reportage began to highlight unauthorised or fraudulent NFT minting (cf. TFL; Stephen), including in music (Newstead). However, the number of contested NFTs remains marginal in comparison to the volume of exchange that occurs in the space daily. OpenSea alone oversaw over US$2.5 billion worth of transactions per month. For the most part, online NFT marketplaces like OpenSea and Solanart oversee the exchange of products on terms not dissimilar to other large online retailers; the space is still resolutely emergent and there is much debate about what products, including recently delisted pro-Nazi and Alt-Right-related NFTs, are socially and commercially acceptable (cf. Pearson; Redman). Further, there are signs this trend may impact on both the willingness and capacity of rightsholders to engage with NFTs, particularly where official offerings are competing with extant fraudulent or illegitimate ones. Despite this, at the time of writing the NFT market as a whole does not appear prone to this type of obstruction. What remains complicated is the contested relationship between NFTs, copyrights, and ownership of the assets they represent. This is further complicated by tension between the claims of blockchain’s independence from existing regulatory structures, and the actual legal recourse available to music rights holders. Music Rights and Ownership Baym et al. note that addressing the problems of rights management and metadata is one of the important discussions around music convened by early blockchain projects. While they posit that “our point is not whether blockchain can or can’t fix the problems the music industries face” (403), for some professionals, the blockchain’s promise of eliminating the need for trust seemed to provide an ideal solution to a widely acknowledged business-to-business problem: one of poor metadata leading to unclaimed royalties accumulating in “black boxes”, particularly in the case of misattributed mechanical royalties in the USA (Rethink Music Initiative). As outlined in their influential institutional research paper (partnered with music rights disruptor Kobalt), the Rethink Music Initiative implied that incumbent intermediaries were benefiting from this opacity, incentivising them to avoid transparency and a centralised rights management database. This frame provides a key example of one politicised version of “fairness”, directly challenging the interest of entrenched powers and status quo systems. Also present in the space is a more pragmatic approach which sees problems of metadata and rights flows as the result of human error which can be remedied with the proper technological intervention. O’Dair and Beaven argue that blockchain presents an opportunity to eliminate the need for trust which has hampered efforts to create a global standard database of rights ownership, while music business researcher Opal Gough offers a more sober overview of how decentralised ledgers can streamline processes, remove inefficiencies, and improve cash flow, without relying on the moral angle of powerful incumbents holding on to control accounts and hindering progress. In the intervening two years, this discourse has shifted from transparency (cf. Taghdiri) to a practical narrative of reducing system friction and solving problems on the one hand—embodied by Paperchain, see Carnevali —and ethical claims reliant on the concept of fairness on the other—exemplified by Resonate—but with, so far, limited widespread impact. The notion that the need for b2b collaboration on royalty flows can be successfully bypassed through a “trustless” blockchain is currently being tested. While these earlier projects were attempts to either circumvent or fix problems facing the traditional rights holders, with the advent of the NFT in particular, novel ownership structures have reconfigured the concept of a rights holder. NFTs promise fans an opportunity to not just own a personal copy of a recording or even a digitally unique version, but to share in the ownership of the actual property rights, a role previously reserved for record labels and music publishers. New NFT models have only recently launched which offer fans a share of IP revenue. “Collectors can buy royalty ownership in songs directly from their favorite artists in the form of tokens” through the service Royal. Services such as Royal and Vezt represent potentially massive cultural shifts in the traditional separation between consumers and investors; they also present possible new headaches and adventures for accountants and legal teams. The issues noted by Baym et al. are still present, and the range of new entrants into this space risks the proliferation, rather than consolidation, of metadata standards and a need to put money into multiple blockchain ecosystems. As noted in RMIT’s blockchain report, missing royalty payments … would suggest the answer to “does it need a blockchain?” is yes (although further research is needed). However, it is not clear that the blockchain economy will progress beyond the margins through natural market forces. Some level of industry coordination may still be required. (18) Beyond the initial questions of whether system friction can be eased and standards generated without industry cooperation lie deeper philosophical issues of what will happen when fans are directly incentivised to promote recordings and artist brands as financial investors. With regard to royalty distribution, the exact role that NFTs would play in the ownership and exploitation of song IP remains conceptual rather than concrete. Even the emergent use cases are suggestive and experimental, often leaning heavily on off-chain terms, goodwill and the unknown role of existing legal infrastructure. Audience and Business Services Aside from the more high-profile NFT cases which focus on the digital object as an artwork providing a source of value, other systemic uses of NFTs are emerging. Both audience and business services are—to varying degrees—explorations of the utility of NFTs as a community token: i.e. digital commodities that have a market value, but also unlock ancillary community interaction. The music industries have a longstanding relationship with the sale of exclusivity and access tailored to experiential products. Historically, one of music’s most profitable commodities—the concert ticket—contains very little intrinsic value, but unlocks a hugely desirable extrinsic experience. As such, NFTs have already found adoption as tools of music exclusivity; as gateways into fan experiences, digital communities, live events ticketing and closed distribution. One case study incorporating almost all of these threads is the Deathbats club by American heavy metal band Avenged Sevenfold. Conceived of as the “ultimate fan club”, Deathbats is, according to the band’s singer M. Shadows, “every single thing that [fans] want from us, which is our time, our energy” (Chan). At the time of writing, the Deathbats NFT had experienced expected volatility, but maintained a 30-day average sale price well above launch price. A second affordance provided by music NFTs’ ability to tokenise community is the application of this to music businesses in the form of music DAOs: decentralised autonomous organisations. DAOs and NFTs have so far intersected in a number of ways. DAOs function as digital entities that are owned by their members. They utilise smart contracts to record protocols, votes, and transactions on the blockchain. Bitcoin and Ethereum are often considered the first DAOs of note, serving as board-less venture capital funds, also known as treasuries, that cannot be accessed without the consensus of their members. More recently, DAOs have been co-opted by online communities of shared interests, who work towards an agreed goal, and operate without the need for leadership. Often, access to DAO membership is tokenised, and the more tokens a member has, the more voting rights they possess. All proposals must pass before members, and have been voted for by the majority in order to be enacted, though voting systems differ between DAOs. Proposals must also comply with the DAO’s regulations and protocols. DAOs typically gather in online spaces such as Discord and Zoom, and utilise messaging services such as Telegram. Decentralised apps (dapps) have been developed to facilitate DAO activities such as voting systems and treasury management. Collective ownership of digital assets (in the form of NFTs) has become commonplace within DAOs. Flamingo DAO and PleasrDAO are two well-established and influential examples. The “crypto-backed social club” Friends with Benefits (membership costs between $5,000 and $10,000) serves as a “music discovery platform, an online publication, a startup incubator and a kind of Bloomberg terminal for crypto investors” (Gottsegen), and is now hosting its own curated NFT art platform with work by the likes of Pussy Riot. Musical and cross-disciplinary artists and communities are also exploring the potential of DAOs to empower, activate, and incentivise their communities as an extension of, or in addition to, their adoption and exploration of NFTs. In collaboration with Never Before Heard Sounds, electronic artist and musical pioneer Holly Herndon is exploring ideological questions raised by the growing intelligence of AI to create digital likeness and cloning through voice models. Holly+ is a custom voice instrument that allows users to process pre-existing polyphonic audio through a deep neural network trained by recordings of Holly Herndon’s voice. The output is audio-processed through Holly Herndon’s distinct vocal sound. Users can submit their resulting audio to the Holly+ DAO, to whom she has distributed ownership of her digital likeness. DAO token-holders steward which audio is minted and certified as an NFT, ensuring quality control and only good use of her digital likeness. DAO token-holders are entitled to a percentage of profit from resales in perpetuity, thereby incentivising informed and active stewardship of her digital likeness (Herndon). Another example is LA-based label Leaving Records, which has created GENRE DAO to explore and experiment with new levels of ownership and empowerment for their pre-existing community of artists, friends, and supporters. They have created a community token—$GENRE—for which they intend a number of uses, such as “a symbol of equitable growth, a badge of solidarity, a governance token, currency to buy NFTs, or as a utility to unlock token-gated communities” (Leaving Records). Taken as a whole, the spectrum of affordances and use cases presented by music NFTs can be viewed as a build-up of interest and capital around the technology. Conclusion The last half of 2021 was a moment of intense experimentation in the realms of music business administration and cultural expression, and at the time of writing, each week seemed to bring a new high-profile music Web3 project and/or disaster. Narratives of emancipation and domination under capitalism continue to drive our discussions around music and technology, and the direct link to debates on ecology and financialisation make these conversations particularly polarising. High-profile cases of music projects that overstep norms of existing IP rights, such as Hitpiece’s attempt to generate NFTs of songs without right-holders’ consent, point to the ways in which this technology is portrayed as threatening and subversive to commercial musicians (Blistein). Meanwhile, the Water and Music research DAO promises to incentivise a research community to “empower music-industry professionals with the knowledge, network and skills to do more collaborative and progressive work with technology” through NFT tokens and a DAO organisational structure (Hu et al.). The assumption in many early narratives of the ability of blockchain to provide systems of remuneration that musicians would embrace as inherently fairer is far from the reality of a popular discourse marked by increasing disdain and distrust, currently centred on NFTs as lacking in artistic merit, or even as harmful. We have seen all this talk before, of course, when jukeboxes and player pianos, film synchronisation, radio, recording, and other new communication technologies steered new paths for commercial musicians and promised magical futures. All of these innovations were met with intense scrutiny, cries of inauthentic practice, and resistance by incumbent musicians, but all were eventually sustained by the emergence of new forms of musical expression that captured the interest of the public. On the other hand, the road towards musical nirvana passes by not only the more prominent corpses of the Digital Audio Tape, SuperAudio, and countless recording formats, but if you squint and remember that technology is not always about devices or media, you can see the Secure Download Music Initiative, PressPlay, the International Music Registry, and Global Repertoire Databases in the distance, wondering if blockchain might correct some of the problems they dreamed of solving in their day. The NFT presents the artistic and cultural face of this dream of a musical future, and of course we are first seeing the emergence of old models within its contours. 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