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Price Manipulation in the Bitcoin Ecosystem
Abstract
To its proponents, the cryptocurrency Bitcoin offers the potential to disrupt payment systems and traditional currencies. It has also been subject to security breaches and wild price fluctuations. This paper identifies and analyzes the impact of suspicious trading activity on the Mt. Gox Bitcoin currency exchange, in which approximately 600,000 bitcoins (BTC) valued at 150 to more than $1,000 in two months.
... Cryptocurrencies are the type of cross-border undertaking that requires same level of rules across the borders, however, the setting of new common standard is truly challenging when different economic and political systems are in play. These research problems put into the framework of modern challenges and opportunities mean that the process of elaboration of the efficient regulatory impacts targeted at the management of cryptocurrency risks that threaten the stability of the world's financial market remains urgent and very challenging (Gandal et.al 2018) [9]. ...
... Another factor due to which cryptocurrencies pose threats to financial stability is their descriptions as assets with decentralized and pseudonymous components (Gikay et.al 2018) [11]. Gandal et al. (2018) [9] also pointed out that these features front the activities that are detrimental to the stability of financial systems, including money laundering and tax evasion. According to Foley et al., (2019) [10], their study revealed that a considerable percentage of the trade in Bitcoin is related to the illicit business hence presenting a pull factor for regulatory issues and even an unsteady market. ...
... Another factor due to which cryptocurrencies pose threats to financial stability is their descriptions as assets with decentralized and pseudonymous components (Gikay et.al 2018) [11]. Gandal et al. (2018) [9] also pointed out that these features front the activities that are detrimental to the stability of financial systems, including money laundering and tax evasion. According to Foley et al., (2019) [10], their study revealed that a considerable percentage of the trade in Bitcoin is related to the illicit business hence presenting a pull factor for regulatory issues and even an unsteady market. ...
Cryptocurrencies are rapidly developing into the financial systems all over the world and, therefore, can be regarded as alarming authorities and financial supervisory agencies. This paper focuses on the complex relationship between the increasing use of cryptocurrencies and the fluctuations of the world economy. It explores the industry's fundamentally low relative volatile nature that includes cryptocurrencies, risks of hacking attacks, frauds and money laundering that disrupt classical economical system frameworks. The emphasis is made on the regulatory activity in various areas, evaluating the efficiency of these measures in minimizing the identified risks. Thus, based on the analysis of the regulatory frameworks of the countries, which have different economic conditions and the level of using cryptocurrencies, those should be defined, which are successful and which difficulties may be encountered at the legislative level. Therefore, the results indicated that while some measures of regulations, which have been implemented in order to increase both market transparency and investors' protection, proved to be effective, others have been consistently failing to adapt to the fast-growing phenomenon of digital currencies. At the end of the paper, the author presents a set of proposals concerning a comprehensive international regulation that should take into account the peculiarities of the examined phenomenon while providing a proper balance between creation and constraint. This paper adds to literature on financial stability and presents findings regarding the strategies that need to be adopted to create sound policies to tackle the challenges of the cryptocurrency market.
... Traditional fiat currencies, though advantageous in terms of divisibility and ease of use, are prone to challenges such as inflation, monetary manipulation, and dependency on centralized governance (Ahamad, Imran, and Uddin 2022). These centralized systems often involve intermediaries like banks, Copyright which increase transaction costs, delays, and the risk of data breaches, leaving users with limited control over their personal financial data (Gandal et al. 2018). Over the past few decades, systemic crises, such as the 2008 financial collapse, have further eroded trust in centralized financial models (Urquhart 2016). ...
... However, the cryptocurrency market is characterized by extreme price volatility, influenced by various dynamic factors, including market sentiment, regulatory changes, and macroeconomic trends (Gandal et al. 2018). This volatility, while providing opportunities for lucrative gains, poses significant risks, especially for investors and traders. ...
The cryptocurrency market is characterized by its high volatility and complex temporal dependencies, posing significant challenges for accurate price prediction. This study introduces advanced hybrid Recurrent Neural Network (RNN) architectures—LSTM-GRU, GRU-BiLSTM, and LSTM-BiLSTM—to enhance the predictive accuracy of cryptocurrency price forecasting. By leveraging the strengths of each RNN variant, the hybrid models effectively capture intricate time-series patterns and nonlinear dependencies inherent in cryptocurrency data. The research follows a comprehensive methodology, including the collection of historical price data for Bitcoin (BTC), Ethereum (ETH), and Litecoin (LTC), rigorous data preprocessing, and the integration of hybrid architectures. Extensive experiments are conducted, and the models are evaluated using key performance metrics, such as Mean Squared Error (MSE), Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE). Results highlight the superior performance of hybrid RNNs, with LSTM-BiLSTM excelling in BTC price prediction, GRU-BiLSTM and LSTM-GRU demonstrating robust performance for ETH and LTC. This study not only establishes the efficacy of hybrid RNN architectures for time-series forecasting but also underscores their potential for real-world applications in trading strategies. The findings set a new standard for leveraging deep learning in cryptocurrency markets, paving the way for more accurate, reliable, and adaptive forecasting systems. Future work will focus on extending this approach to a broader range of cryptocurrencies and incorporating external market factors to further enhance predictive capabilities.
... However, in cryptocurrency markets, regulatory oversight remains inconsistent across different jurisdictions. Many crypto-exchanges operate with limited or no regulatory frameworks, creating an environment where pump-and-dump schemes flourish [9]. Unlike traditional financial markets, where strict disclosure requirements and trading surveillance mechanisms help detect manipulative activities, cryptocurrency exchanges often lack these safeguards, allowing bad actors to orchestrate and execute such schemes with relative ease. ...
... From each exchange, they selected 50 trading pairs (symbols). For each symbol, they obtained historical data of OHLCV (Open, High, Low, Close, Volume) [9,21] for a period of 20 days at hourly intervals. Ultimately, the dataset was compiled using data from five exchanges and 450 symbols, amounting to 480 hourly candles per trading pair. ...
We propose a simple yet robust unsupervised model to detect pump-and-dump events on tokens listed on the Poloniex Exchange platform. By combining threshold-based criteria with exponentially weighted moving averages (EWMA) and volatility measures, our approach effectively distinguishes genuine anomalies from minor trading fluctuations, even for tokens with low liquidity and prolonged inactivity. These characteristics present a unique challenge, as standard anomaly-detection methods often over-flag negligible volume spikes. Our framework overcomes this issue by tailoring both price and volume thresholds to the specific trading patterns observed, resulting in a model that balances high true-positive detection with minimal noise.
... It can aid in investor protection and can include determining the expertise of executives responsible for managing the cryptocurrency exchange, criminal record checks, and assessing past job history. Furthermore, it becomes critical to evaluate key information metrics such as trading history, trading volume, and sudden price changes to determine whether they may be caused by illicit activity (Farrugia, Ellul, & Azzopardi, 2020;Gandal, Hamrick, Moore, & Oberman, 2018). ...
... The need for such a focus is critical as cryptocurrency has continued to be associated with financial crimes (Gandal et al., 2018;Smith, 2020). These crimes fund drug and human trafficking, finance activities of rogue states such as nuclear weapons proliferation, and assist malicious states and actors to evade sanctions and interfere in democratic institutions (Ferrill, Leuprecht, & Simser, 2023). ...
... [15] examined the price dynamics of Bitcoin, identifying significant speculative bubbles. Similarly, [16] provided evidence of market manipulation affecting cryptocurrency prices. These findings underscore the need for robust valuation models that account for the unique features of digital currencies. ...
... Cryptocurrencies are highly volatile, often influenced by speculative trading rather than economic fundamentals, which poses a risk to financial stability [16]. ...
... Cheah & Fry (2015) expressed this viewpoint after analysing the price dynamics of Bitcoin and speculative bubbles, highlighting volatility concerns. Gandal, Hamrick, Moore & Oberman (2018) contributed to this proposition by providing evidence of price manipulation in cryptocurrency markets. Bariviera (2017) also contributed to the development of this theory by assessing the financial stability risks posed by high cryptocurrency volatility. ...
... Bariviera (2017) Assessed risks to financial stability due to high volatility in cryptocurrency valuation. Gandal et al. (2018) Provided evidence of price manipulation and speculative demand in cryptocurrency markets. Balancing digital currency use with environmental sustainability; promoting energy-efficient protocols. ...
... Immediately, FTX lost billions in its valuation, followed by a liquidity crisis, eventually leading to its bankruptcy. Because activities on CEXs are highly anonymous and difficult to trace, price and volume manipulation are common (Cong et al. 2023;Gandal et al. 2018). 2 Most leading crypto CEXs apply knowyour-customer rules and take custody of traders' assets to facilitate order matching. ...
Using almost three years of minute‐level data, we show that the efficiency of Uniswap v3 is much improved relative to v2, and some v3 pools are approaching or even exceeding Bitstamp in terms of price discovery ability. Regression results suggest that the channels of influence for these improvements are an increase in informed liquidity providers and swappers, who nevertheless prefer to use centralized exchanges when markets become volatile. At such times, there are relatively more uninformed speculative traders in all Uniswap pools, and cross‐exchange arbitrage activities become more prevalent. However, these decrease the price discovery ability of Uniswap pools relative to Coinbase and Bitstamp. The informed traders that remain on Uniswap during periods of high uncertainty tend to switch to the higher‐fee v3 pools to compensate for efficiency loss, or to v2 pools where there is sufficient liquidity to complete large trades.
... Therefore, the contract is free from human interference while automating the financial processes of loan, insurance, and asset management. As Gandal et al. [14] mentioned, "smart contracts may eliminate paperwork and quicken financial transactions; in fact, making financial operations more transparent and efficient than ever". ...
This paper further elaborates on how the emergent effects of CBDCs, blockchain technology, and artificial intelligence alter the global financial landscape regarding transaction costs, customer satisfaction, and operational efficiency. The research uses a dataset of 100 institutions drawn from diversified global markets in pre-and post-implementations of CBDCs and blockchain technology. It considers that AI reduces transaction costs, besides providing customers with an experience with even better operational performance. SPSS was used during the statistical and correlation analysis computation. At the same time, Python was implemented during visualization work, and a box plot with multi-line graph drawing was used to represent results. The adoption of CBDCs and blockchain implementation resulted in high reductions in transaction costs, improvements in customer satisfaction and efficiency through AI-driven solutions, and, to a large extent, measured improvement in speed and service quality of transactions. In that sense, the findings show that these technologies change the face of financial transactions towards becoming faster, cheaper, and more personal. All of these research findings suggest that these new digital technologies could make the world's financial sector more efficient, accessible, and competitive thereafter.
... Даний аспект також досліджується в роботі Сайфедіна Аммуса[3], який розглядає біткоїн як децентралізовану альтернативу центральному банківському регулюванню.https://a-economics.com.ua/index.php/home/about ISSN 3041-2129 Увесь контент ліцензовано за умовами Creative Commons BY 4.0 International license Ризики волатильності та ринкових маніпуляцій в екосистемі криптовалют детально проаналізовані в дослідженнях Юкуна Лю та Алеха Цивінського[22], а також Ніла Гандала та співавторів[9]. Ці роботи емпірично демонструють схильність ринку криптовалют до маніпуляцій і виявляють фактори, що впливають на волатильність цін, що критично важливо для формування стратегій управління фінансовими ризиками в бізнесі.Кібербезпека та технічні аспекти захисту криптоактивів стають фокусом досліджень Віндена Вайлда та співавторів[29], а також Абхішека Кумара та колег[14], які деталізують проблему подвійних витрат і потенційні вразливості в блокчейн-системах. Дані дослідження підкреслюють необхідність комплексного підходу до забезпечення безпеки при інтеграції криптовалют у бізнес-процеси. ...
У роботі обґрунтовано стратегії мінімізації ризиків, що інтегрують технологічні, економічні, соціальні та культурні аспекти функціонування біткоїна в підприємницькій діяльності. Мета. Дослідження спрямована на теоретичне обґрунтування підходів до управління ризиками при інтеграції біткоїна в бізнес-процеси з використанням акторно-мережевої методології, що дозволяє розглядати криптовалютну систему як сукупність взаємодіючих гетерогенних елементів. Методи. У роботі використано міждисциплінарний підхід, що об'єднує акторно-мережеву теорію, концепції інформаційної безпеки та інституційний аналіз криптоекономічних систем. Проведено систематизацію досліджень функціонування протоколу Біткоїн з позиції взаємодії технічних і соціальних компонентів. Застосовано компаративний аналіз архітектури безпеки традиційних фінансових систем і децентралізованих криптовалютних структур. Результати. Систематизовано основні категорії ризиків, пов'язаних з використанням біткоїна в бізнесі (волатильність цін, регуляторна невизначеність, кіберзагрози, операційні та репутаційні ризики), оцінено їхню специфіку з урахуванням децентралізованої природи криптовалюти. Виявлено подвійну природу транзакцій, що виступають одночасно засобом передачі вартості та об'єктом економічної конкуренції, що створює специфічне середовище ризиків. Проаналізовано практичний досвід провідних учасників криптовалютної індустрії, що демонструє ефективність багаторівневих підходів до управління ризиками. Розглянуто роль технічних особливостей протоколу Біткоїн (децентралізація, криптографічний захист, прозорість реєстру, незмінність даних) в управлінні ризиками. Обґрунтовано, що ці характеристики створюють принципово іншу архітектуру безпеки порівняно з традиційними фінансовими системами, що вимагає від бізнесу переосмислення підходів до оцінки та мінімізації ризиків. Висновки. Ефективне управління ризиками при використанні біткоїна в бізнесі вимагає комплексного підходу, що інтегрує технологічні рішення з фінансовими та організаційними заходами. Фундаментальні характеристики протоколу Біткоїн створюють принципово іншу архітектуру безпеки порівняно з традиційними системами, що зумовлює необхідність перегляду класичних методів оцінки та мінімізації ризиків.
... The literature on bitcoin price formation is growing, and the existing literature shows that bitcoin has relatively independent price behavior from other traditional financial assets such as stocks, bonds, and commodities, and thus may be beneficial for portfolio diversification. [5] 135 ...
This research aims to examine the current practices of accounting for
bitcoins by reviewing some studies which related to this topic, and thus for
achieving the main objective of the study, which is to develop a proposed
model to account for bitcoins that unifies accounting practices of bitcoins.
The main objective of the study is to develop a proposed model to account
for bitcoins that unifies accounting practices of bitcoins. To achieve this
objective, the researchers divided the research to include the following:
―Introduction‖ which aimed to gain a holistic view for the research, and then
" Literature Review." In this part the researchers clarify the nature,
characteristics, pros and cons, and also how the bitcoin system works,
through reviewing number of papers, accounting academic journals,
professional publications. After that, the researchers reviewed the different
current accounting practices for bitcoins, and the efforts of some formal
organizations in accounting for bitcoins.
Finally, the researchers introduced A proposed framework for unifying
the accounting practices for bitcoins; the proposed framework consisted of
five main pillars, recognition and classification of bitcoins, measurement of
bitcoins and disclosures for bitcoins. The researchers represented a case of
financial statements to apply the proposed framework for accounting for
bitcoins, and show the effect of the proposed accounting model on the
financial statements.
... In traditional banking systems, cross-border payments involve multiple intermediaries, including correspondent banks and clearinghouses, leading to prolonged processing times and increased transaction costs (Bech & Garratt, 2017). Blockchain-based solutions such as Ripple (XRP), Stellar, and central bank digital currencies (CBDCs) offer an alternative by enabling nearinstantaneous, cost-effective international transactions (Gandal et al., 2018). The ability of blockchain to overcome barriers in financial transactions makes it a compelling subject for comparative analysis across different economic contexts. ...
Cross-border transactions are critical to global trade and economic integration, yet traditional financial systems face significant challenges, including high costs, lengthy processing times, lack of transparency, and security risks. This study explores the role of blockchain in enhancing cross-border transactions, offering a comparative analysis between emerging and developed markets. By leveraging decentralized ledger technology (DLT), smart contracts, and cryptographic security, blockchain presents a transformative solution to address inefficiencies in international payments. Using a mixed-methods research approach, this study analyses primary data from industry experts and financial institutions alongside secondary data from regulatory reports, academic literature, and blockchain adoption case studies. Findings indicate that blockchain reduces transaction times from multiple days to minutes, with transaction fees dropping from 10% to less than 2%. The technology also enhances security by reducing fraud risks and eliminating chargeback disputes. However, blockchain adoption varies across economies. Developed markets prioritize institutional integration and regulatory compliance, while emerging markets focus on financial inclusion, remittances, and decentralized finance (DeFi) solutions. Despite its advantages, regulatory uncertainty, scalability limitations, and cybersecurity concerns hinder widespread adoption. Moreover, the emergence of Central Bank Digital Currencies (CBDCs) presents a competing framework for digital payments. This study concludes that blockchain has the potential to revolutionize cross-border transactions, provided that regulatory harmonization, interoperability, and cybersecurity risks are effectively managed. Future research should explore the impact of CBDCs, blockchain scalability, and privacy regulations to ensure sustainable adoption in the global financial landscape.
... The rapid growth of cryptocurrency has been the subject of varying research including technical term of cryptocurrency (Gandal et al, 2018;Griffin and Shams, 2018) and in terms of being an investment asset, such as, regulatory framework for cryptocurrency exchange (Ju et al., 2016;Pieters and Vivanco, 2017;Borri and Shakhnov, 2020), price determination and predictability (Brauneis and Mestel, 2018;Bouri et al., 2019;Kristoufek, 2019;Uras et al., 2020;Gurdgiev and O'Loughlin, 2020;Hachicha et al., 2023), roles as speculative trading products (Urquhart, 2016;Urquhart, 2017;Corbet et al., 2019), price volatility (Blau, 2017;Fry, 2018;Hu et al., 2018), diversification benefits (Corbet et al., 2018;Liu, 2019;Guesmi, 2019;Shrotryia and Kalra, 2022;Kyriazis et al., 2022) and market efficiency (Urquhart, 2016;Nadarajah and Chu, 2017;Caporale et al., 2018;Sensoy, 2019;Apopo and Phiri, 2021). ...
Cryptocurrency exchange in Asian emerging countries has grown rapidly in the past few years while there’s still inconsistency in the supervision of the official agency such as Central Bank and the Securities and Exchange Commission which made it unclear about the future direction of cryptocurrency exchange. This paper analyses herding behavior in 4 cryptocurrency exchanges which located in 4 emerging countries in Asian, using total of 18,313,994 trading data both daily and 4 types of high frequency data (240-min, 60-min, 30-min, and 15-min) for the period from 1st January 2019 to 30th November 2024 by the Cross-sectional absolute deviations (CSAD) approach. The result suggests that herding behavior always evident when apply the daily data but undetected with high-frequency data which is more appropriate data. This finding cast light on the efficiency of cryptocurrency exchange in Asian emerging countries and leads to a guideline for official authorities to regulate the market appropriately.
... The primary reason why cryptocurrency is being considered is due to its ability to provide a secure and efficient means of payment, which traditional currencies cannot offer. However, economists argue that cryptocurrency lacks the stability and acceptance of current currencies, making it difficult to be recognized or accepted as legal tender and become the true global currency (Gandal et al.,2018). In recent years through widespread media articles and significant amount of attention adoption cryptocurrency has generated it still faces multiple adversity's to be accepted as the medium of exchange. ...
While discussions about price determination and volatility in relation to stocks and currency have been prevalent in the financial markets, the true potential of Bitcoin as a market has not been fully realized. As a relatively new market, the main driving force behind Bitcoin's price volatility requires further study, especially considering the attention the topic has received in recent decades.
... The primary reason why cryptocurrency is being considered is due to its ability to provide a secure and efficient means of payment, which traditional currencies cannot offer. However, economists argue that cryptocurrency lacks the stability and acceptance of current currencies, making it difficult to be recognized or accepted as legal tender and become the true global currency (Gandal et al.,2018). In recent years through widespread media articles and significant amount of attention adoption cryptocurrency has generated it still faces multiple adversity's to be accepted as the medium of exchange. ...
... In our experiments, we used technical traders and no taxes, as there is no conclusion about its effect. [Moore et al., 2018] identified a price manipulation in the bitcoin market through suspicious trading activity in the Mt. Gox Bitcoin currency exchange. ...
This work aims to evaluate price manipulation provided by investors with great amount of capital and its overall effect in the stock market. In order to do so, we have created an artificial financial market using NetLogo. The experiments were carried out in a closed environment, with technical analysis speculators and other three different groups of agents, each one with a unique investment strategy. This work provides inputs for the creation of an artificial financial market, in which other diverse agent strategies could be added, and evidences of a market manipulation caused by excess demand.
... Böhme et al., (2015) conducted a study on the economics, technology, and governance of Bitcoin, highlighting the importance of ensuring interoperability with the existing financial infrastructure to promote its widespread adoption. Gandal et al., (2018) examined the manipulation of Bitcoin prices and emphasized the necessity of implementing regulatory measures to adhere to financial norms. According to Kshetri, (2017), blockchain to enhance the Internet of Things (IoT) must be compatible with IoT systems. ...
This study examines Pakistani citizens' behavioral intentions toward the adoption of cryptocurrency as a digital currency. Cryptocurrency refers to a form of currency that exists in digital or virtual form and relies on cryptography to ensure the security of transactions and regulate the generation of additional units. Cryptocurrencies have the potential to disrupt the global financial system. Cryptocurrency is a viable option for decentralized and secure transactions, offering enhanced transparency and lowering dependence on conventional financial institutions. The authors collected data from potential cryptocurrency customers or investors. Data were collected from Karachi (Pakistan). The study was conducted with the help of the diffusion of innovation theory (DOI), employing all its components (relative advantage, compatibility, complexity, trialability, and observability). The DOI model statements were modified and adapted to satisfy the requirements of this study. This empirical research report concludes that relative advantage (financial incentives, technology advancement, global accessibility, privacy and security, and P2P nature), compatibility (user-friendliness, integration with existing systems, compatibility with digital lifestyles), and complexity (ease of use and mass adoption) contribute to the adoption. Trailability (lack of familiarity and risk aversion) and observability (limited exposure, lack of social proof, and negative stigma) are unrelated to customer behavior toward cryptocurrencies. In all these contexts, cryptocurrency adoption can enhance value co-creation. Finally, this study provides valuable insights for stakeholders.
... Böhme et al., (2015) conducted a study on the economics, technology, and governance of Bitcoin, highlighting the importance of ensuring interoperability with the existing financial infrastructure to promote its widespread adoption. Gandal et al., (2018) examined the manipulation of Bitcoin prices and emphasized the necessity of implementing regulatory measures to adhere to financial norms. According to Kshetri, (2017), blockchain to enhance the Internet of Things (IoT) must be compatible with IoT systems. ...
This study examines Pakistani citizens’ behavioral intentions toward the adoption of cryptocurrency as a digital currency. Cryptocurrency refers to a form of currency that exists in digital or virtual form and relies on cryptography to ensure the security of transactions and regulate the generation of additional units. Cryptocurrencies have the potential to disrupt the global financial system. Cryptocurrency is a viable option for decentralized and secure transactions, offering enhanced transparency and lowering dependence on conventional financial institutions. The authors collected data from potential cryptocurrency customers or investors. Data were collected from Karachi (Pakistan). The study was conducted with the help of the diffusion of innovation theory (DOI), employing all its components (relative advantage, compatibility, complexity, trialability, and observability). The DOI model statements were modified and adapted to satisfy the requirements of this study. This empirical research report concludes that relative advantage (financial incentives, technology advancement, global accessibility, privacy and security, and P2P nature), compatibility (User-friendliness, Integration with existing systems, compatibility with digital lifestyles), and complexity (ease of use and mass adoption) contribute to the adoption. Trailability (lack of familiarity and risk aversion) and observability (limited exposure, lack of social proof, and negative stigma) are unrelated to customer behavior toward cryptocurrencies. In all these contexts, cryptocurrency adoption can enhance value co-creation. Finally, this study provides valuable insights for stakeholders.
... This shift is very evident in remittances; cross-border payments through crypto currencies are faster and cheaper compared to traditional banking channels (Rejeb et al., 2021). Research by (Gandal et al., 2018) Stable coins-the type pegged to traditional currency further blur what once were clearer distinctions between systems, further throwing competition in their direction (Kayani & Hasan, 2024). Adoption of blockchain-based solutions by financial institutions would be indicative of a hybrid model of finance with decentralized technology components and regulated structures (Addo Baidoo, 2019). ...
The paper looks into the impact of cryptocurrencies on Pakistan's traditional banking sector regarding issues of regulation, adaptation to technology, and the implications of digital money. The investigation employed a qualitative method and critical thematic analysis in analyzing data gathered through semi-structured interviews conducted with 14 crypto currency investors and 8 banking practitioners. The number of samples in the interview is sufficient enough to explore points of view about major stakeholders' sectors. A thematic analysis technique was used during the identification of patterns and codes on how crypto currency influences banking products, regulation, and implementation of block chain. Conclusion: This study concluded that opportunities for financial inclusivity and convenience exist with crypto currency but some notable issues with its regulation and instability still exist. The insights of the investigation are of useful value in ascertaining how digital money interfaces with conventional banks, which also has implications on future policy as well as the practices of banks.
... Similarly, the emergence of blockchain technology and cryptocurrencies represents a societal shift toward financial independence from traditional centralized institutions like banks and governments (Nakamoto, 2008). Early adopters of crypto-assets have encountered challenges including market volatility (Gandal et al., 2018), regulatory uncertainty, and security vulnerabilities (Castonguay & Stein Smith, 2020). These obstacles reflect the problems associated with adopting new financial paradigms at a societal level, as a fractal projection at a higher level of complexity, of the problems associated to transitioning from adolescence to adulthood and gaining financial independence. ...
This article examines the broader societal implications of blockchain technology and crypto-assets, emphasizing their role in the evolution of humanity as a "superorganism" with decentralized, self-regulating systems. Drawing on interdisciplinary concepts such as Nate Hagens' "superorganism" idea and Francis Heylighen's "global brain" theory, the paper contextualizes blockchain technology within the ongoing evolution of governance systems and global systems such as the financial system. Blockchain's decentralized nature, in conjunction with advancements like artificial intelligence and decentralized autonomous organizations (DAOs), could transform traditional financial, economic, and governance structures by enabling the emergence of collective distributed decision-making and global coordination. In parallel, the article aligns blockchain's impact with developmental theories such as Spiral Dynamics. This framework is used to illustrate blockchain's potential to foster societal growth beyond hierarchical models, promoting a shift from centralized authority to collaborative and self-governed communities. The analysis provides a holistic view of blockchain as more than an economic tool, positioning it as a catalyst for the evolution of society into a mature, interconnected global planetary organism.
... Preliminary academic intervention on this subject mainly focused on expounding the whole concept, that is the mechanisms and protocols behind crypto currencies. Studies by Peters et al. (2015), ElBahrawy et al. (2017), Gandal et al. (2018), Farell (2015) and Böhme et al. (2015) are some of the early studies that focused on giving an overview on the subject of crypto currencies especially Bitcoin, elucidating its mechanisms and components. Subsequently, empirical studies regarding cryptocurrency market have also been conducted over the years. ...
The emergence of crypto currency as an alternative source of currency has been dubbed as one of the greatest phenomenon of the 21st century. Over the years, crypto currencies have grossly interrupted the traditional financial system and they continue to act as a catalyst for its revolution. However, cryptocurrencies have not been free from misery and controversies. The aim of this study is to explore and investigate empirically the impact of Covid-19 pandemic on price and volume dynamics in crypto markets. The study makes use of two data samples, but these samples are analyzed separately and independently. The first sample consists of Top Five Cryptocurrencies in terms of market capitalization (Bitcoin, Ethereum, XRP, Binance coin and Litecoin) as at 7 November 2020. The second one is made up of the Bottom Five Cryptocurrencies among the top 40 cryptocurrencies (FTX Token, Huobi Token, Filecoin, Dash and Decreed) as at 7 November 2020 again. The data among the Top Five Cryptocurrencies ranges from 2014 to 2021 and the data among the Bottom Five Cryptocurrencies ranges from 2018 to 2021.. The empirical results reveal that all crypto-currencies are integrated at order 1 i.e. I (1). The empirical analysis confirms presence of strong evidence for intra-and-inter long run relationship between price and volume dynamics within the crypto market irrespective of whether it is pre-pandemic or pandemic period. More so, there is convincing evidence from the results that much of the variance among the prices and volumes of the top five cryptocurrencies is attributed to the Bitcoin price-volume dynamics. This implies that it is critical for crypto market traders, investors and portfolio managers, before making any investment decision must consider the dynamics of price and trading volumes of BITCOIN as they hugely impact the prices and volumes of other altcoins.
... However, the volatility of cryptocurrencies is higher than traditional assets, characterized by continuous trading and trading anonymity (Yue et al. 2021). Similarly, cryptocurrency has a high potential for manipulation (Gandal et al. 2018;Khurshid et al. 2023), speculative investing characteristics, and the possibility of intrinsic price bubbles (Corbet et al. 2018;Naeem et al. 2022;Kaneda et al. 2023). From another aspect, risk-averse investors seek assets with high diversification, minimal risk, and profitability prospects. ...
This study uses the Bayesian structural model to assess the causal effect of the futures exchange (FTX) insolvency on cryptocurrencies from October 2022 to December 14, 2022. Findings show that FTX insolvency negatively impacts cryptocurrencies. Moreover, the results indicate rapid divergence from counterfactual predictions, and the actual cryptocurrencies are consistently lower than would have been expected in the absence of the FTX collapse. Cryptocurrency is reacting strongly to the uncertainty caused by insolvency. In relative terms, the collapse of FTX has been highly detrimental to Solana and Ethereum. Furthermore, the outcomes show that cryptocurrencies would not have been negatively affected if the intervention had not occurred. FTX collapsed owing to a mismatch between the assets and liabilities. The industry is still mostly unregulated, and regulators must act quickly, highlighting the need for outstanding innovation and decentralized and trustless technology adoption.
... According to the authors, higher levels of information about the advantages and security of cryptocurrencies could lead to enhanced usage. Similarly, Gandal et al. (2018) focus on understanding market participants as well as whether or not pricing manipulation is possible in the context of Bitcoin. They mention that fluctuation of price can have impact on people's perception of cryptocurrency and its use in particular country where trading is usually speculative. ...
This paper explores the emergence of digital currencies in Pakistan and their potential role in reshaping the nation's position in global economic relations. It assesses the latest trends concerning the regulation of the technology and its exploration, drivers of adoption, and key impediments to its deployment. Including both qualitative information gathered during review of policy documents and policy, as well as quantitative analysis of assumed economic variables. Though Digital currencies are restricted by low internet connectivity and mobile phone smart device adoption in Pakistan the progress of payment systems Such as JazzCash & Easypaisa indicates future progress. But challenges such as blockchain readiness and cybersecurity are still need to be discussed. For blockchain to be fully adopted, there is need to pursue more investment in educating talent, and the regulatory framework. Security is key to the public trust and so it is important to secure wallets, payments and transactions data in particular. Opportunities and threats exist in Pakistan’s regulatory environment, nonetheless the prospects for developing the CBDCs still exist. Solving these challenges entail to define legal status, to simplify the process of licensing and to protect the consumer’s rights effectively. E-commerce conducted through the use of incorporative payment services in combination with CBDCs provides an opportune means of boosting Pakistan’s financial and economic outlook by catalyzing remittances transfer, cutting on cost, and expediting cross-border transfers as well as increasing access to financial services. Educational campaigns, influence from friends or relatives, and new trust-building JVs can successfully improve the situation with the adoption of digital currencies in Pakistan. There are also likely to increase the adoption of CBDCs, blockchain payment platforms, and mobile wallets if the efforts are implemented effectively.
Switching (both endogenous and exogenous) are unavoidable recurring features of financial time series, particularly Bitcoin prices. The latter are driven by frequent changes in investors’ sentiment as there is no theoretical fundamental value of crypto assets. Frequent switching in Bitcoin prices—which is often identified in empirical studies—is nevertheless primordially endogenous in nature. Therefore, endogenous switches of such a nature may not be at odds with empirical studies which find that long-memory persistence in economic and financial time series may be spuriously dominated by break points in the data. The theoretical lengths of the switches (i.e. the expected convergence behaviour of shocks to the zero mean) often encounter the intervention of another break point (of an unclaimed length) masking the inherent pattern of the series as being perennially persistent. In the empirical finance literature, both memory (persistence feature) and breaks (types of switching) have implications for the efficiency of the market. In this chapter, we outline an argument and present a theory-driven empirical apparatus to demonstrate that Bitcoin investors are driven, although not beaten by ‘memory’ as well as a number of endogenous switches in the price level. Both memory and endogenous switches are compatible with what we call an endogenous growth mechanism in Bitcoin market. The finding of persistence has also relevance to the theory of learning: an agent that learns synchronously is an agent that will depict fewer persistence behaviours. We employ a variant of the Auto-Regressive Fractionally Integrated Moving Average (ARFIMA) Markov model with endogenous switches to characterise the profile of price fluctuations in cross-market Bitcoin prices. We show that Bitcoin markets depict true long memory and that price dynamics are mostly driven by endogenous feedback mechanisms or market reflexivity.
Banks, financial service providers and insurance firms are considered the lifeblood of modern civilization, acting as a stimulus for the growth and development of a country with a growing economy like India. A systematic review and bibliometric analysis were conducted to explore the potential impact of blockchain technology on the banking, financial services and insurance (BFSI) industries in developing countries like India. The study found 148 articles and 33 papers assessing the benefits of blockchain technology based on institutional, market and technological factors. Acting managers, decision-makers and experts place a premium on having a solid foundational view before deciding whether to implement blockchain technology in their banking system, and our study will unquestionably be useful to those individuals. Furthermore, institutional, market and technical factors can be used to analyse the benefits of implementing blockchain in the BFSI sectors. To better understand the applications, prospects and difficulties of using blockchain technology in the BFSI sectors, we will attempt to cover the theoretical background based on earlier research in the study.
Predicting cryptocurrency prices is challenging due to market volatility and external influences like social media sentiment. This study integrates Twitter sentiment analysis with deep learning models (LSTM, GRU, Bi-LSTM, and Temporal Attention Model) to enhance Bitcoin price forecasting. Sentiment features were extracted using VADER and RoBERTa, with findings showing that RoBERTa-based models significantly outperform VADER. Bi-LSTM (RoBERTa) achieved the lowest MAPE of 2.01%, demonstrating the effectiveness of deep contextual embeddings. SHAP analysis identified Sentiment Momentum, RoBERTa Compound Score, and VADER Negativity Score as key predictors of price movements. These results highlight the value of sentiment-driven forecasting and provide insights for traders, investors, and researchers.
Cryptocurrency markets exhibit high volatility, making accurate price prediction a challenging task. This project aims to develop a cryptocurrency price prediction model using linear regression. The model is trained on historical price data, considering key features such as closing prices, trading volume, and market trends. The implementation is built with Streamlit, allowing for an interactive and user-friendly interface where users can input parameters and visualize predictions dynamically.
The development of the cryptocurrency segment within the global financial market has emerged as one of the most transformative phenomena of the digital economy over the past decade. The present study aims to analyse the global imperatives driving this development, focusing on the key trends, challenges, and opportunities shaping the cryptocurrency market. Methodology. This study uses a combination of analytical and comparative methodologies to examine the cryptocurrency segment within the global financial market. The analytical approach is used to assess the structural dynamics, market trends and capitalisation growth of cryptocurrencies, while the comparative method facilitates the assessment of differences and similarities in the adoption of cryptocurrencies across different countries and financial systems. Data was collected by reviewing publicly available financial reports, cryptocurrency market data and institutional studies. Quantitative analysis was performed to evaluate numerical trends in market capitalisation, transaction volumes, and cryptocurrency usage in payment systems. Furthermore, a qualitative analysis was conducted to elucidate the regulatory challenges and their ramifications for financial stability. Results. The findings indicate the preeminence of Bitcoin, its evolution into a global asset, and the expanding role of altcoins, utility tokens and stablecoins. The analysis reveals the rising use of cryptocurrencies in commercial payments, the issuance of national digital currencies, and the substantial adoption of blockchain technologies by global corporations. However, the study also identifies critical challenges, including regulatory ambiguities, security vulnerabilities, and systemic risks associated with financial stability. The value and originality of this research lie in its comprehensive approach to assessing the multifaceted nature of the cryptocurrency market. The integration of quantitative insights with policy implications has resulted in the formulation of a novel framework for comprehending the strategic role of cryptocurrencies in the evolving global financial landscape. The study's findings offer actionable recommendations for policymakers, investors, and financial institutions seeking to navigate the intricacies of the cryptocurrency ecosystem.
This study explores the evolving relationship between the Reserve Bank of India (RBI) and cryptocurrency investment trends, focusing on the role of RBI's policies and interventions in shaping the future of cryptocurrency markets in India. Through a comprehensive analysis, the study assesses the types of RBI policies that are perceived to positively influence cryptocurrency investments and the forms of interventions likely to impact the market. Additionally, it investigates RBI officials' perspectives on the current stance of the RBI regarding cryptocurrencies, the potential benefits of RBI-backed digital currencies, and the importance of investor education. The study finds that a supportive RBI policy is favored by most respondents, while interest rate adjustments and taxation policies are considered the most impactful forms of intervention. However, the findings also suggest that RBI interventions do not significantly influence investor perceptions toward cryptocurrencies. The research offers valuable insights for policymakers, investors, and financial institutions on the potential role of the RBI in fostering a stable cryptocurrency investment environment in India. The study concludes that while RBI policies are important, their direct impact on investor behavior remains limited. Introduction The growing influence of cryptocurrencies on global financial markets has prompted central banks worldwide to reconsider their roles in regulating and shaping these digital assets. In India, the Reserve Bank of India (RBI) has been actively involved in formulating policies that affect the cryptocurrency market, influencing investor behavior and market trends. As cryptocurrencies continue to gain popularity among investors, understanding the RBI's role in regulating and guiding this emerging asset class is critical for ensuring market stability and protecting investor interests. This study delves into the nature of RBI interventions and explores how these policies can either encourage or inhibit cryptocurrency investments. The research highlights the potential benefits and drawbacks of various RBI-backed digital currencies and investigates the types of regulatory measures that could most effectively support the growth of the cryptocurrency market in India. By examining the perspectives of RBI officials and analyzing the impact of different policy approaches, the study aims to provide a clearer understanding of the RBI's role in the evolving digital economy. With the introduction of new digital assets and the growing interest in cryptocurrencies, it is essential to assess how the RBI can foster a secure investment environment while ensuring that regulations are robust enough to mitigate risks. This study seeks to offer insights into the future of cryptocurrency investment in India and the central bank's influence on shaping that future.
This study employed both bibliometric analysis and a comprehensive review of the existing literature to examine 3844 publications in cryptocurrency research, which were collected from the Web of Science Core Collection Database. The study has utilized bibliometric methods to analyze the most productive countries and regions, research institutions, and authors in cryptocurrency research. Cluster analysis of co‐citation articles indicates three main themes in cryptocurrency research over the past decade: the efficiency of the cryptocurrency market, innovation, application, and governance of blockchain technology as well as risk management of cryptocurrencies. Keyword co‐occurrence analysis reveals three major future research directions regarding cryptocurrency: (1) using machine learning methods to forecast price returns of cryptocurrencies; (2) how to enhance the security, legitimacy, and environmental sustainability of cryptocurrencies; (3) further exploration of the impact of various unexpected events on the risks of cryptocurrencies under global instability. In the section of literature review, two to three representative papers from the five most‐cited authors in cryptocurrency research are summarized. Additionally, 28 of the most noteworthy papers, selected based on three different criteria, are presented. These papers cover different periods and research topics, and a brief yet comprehensive overview of these 28 influential papers is provided.
This body of research aims to study the relationship between two distinct disruptive technologies, Bitcoin, and the Dark Market, as both entities are used in tandem and are not mutually exclusive. Bitcoin is a virtual currency, independent of government control, and its popularity is derived from its features such as decentralisation, anonymity, and its ability to bypass financial intermediaries. The Dark Market is an illegal arena where the sale of illicit goods and services occurs. Dark Market consumers have adopted Bitcoin as the primary tender used for transactions, with circa 46% of all Bitcoin transactions being related to the sale of goods on the dark web. Given this fact, this study aims to determine a causal relationship between Dark Market activity and Bitcoin returns in an attempt to legitimise Bitcoin as a credible asset, determine Bitcoin price formation and aid in regulation formation and oversight. The results highlight no causal relationship between Dark Market activity and Bitcoin returns, however, an interesting takeaway of this study in terms of regulation is the causal relationship between Dark Market activity and the privacy coin, Monero. This study is unique in the sense that no research in this field has been completed before, thus filling a gap in the literature. The contribution to the literature is noted in chapter five. The economic and regulatory significance of these results are also presented, which discuss Bitcoin price formation, and suggestions for a cryptocurrency regulatory trajectory.
Streamlit-powered data science visualizing cryptocurrency markets is a pioneering and user-centric platform meticulously crafted to immerse users in the captivating realm of cryptocurrencies. By harnessing state-of-the-art technologies such as Python, Streamlit, Matplotlib, Seaborn, and Base64, this application introduces an engaging and immersive experience for both cryptocurrency enthusiasts and astute investors. Hosted on the robust Google Cloud Shell infrastructure, it not only assures scalability but also reinforces reliability, offering users unfettered access to invaluable insights and interactive tools tailored for traversing the dynamic and ever- evolving cryptocurrency market. The fundamental goal of this project is to furnish an expansive and user- friendly gateway to the multifaceted world of cryptocurrency analysis. The Streamlit-powered data science visualizing cryptocurrency markets empowers users with a rich tapestry of interactive data visualizations and in-depth insights, thereby arming them with the essential instruments required to delve into and comprehend the complex cryptocurrency landscape. Whether you are an ardent cryptocurrency aficionado yearning to stay apprised of the latest trends or an astute investor in pursuit of data-driven decision-making, our web application stands as an invaluable and irreplaceable resource in the vast expanse of the cryptocurrency space.
This report presents a comparative analysis of cryptocurrency investments versus traditional assets (stocks, bonds, and gold) from 2019 to 2023, evaluating key performance metrics such as returns, volatility, and risk-adjusted performance. The study reveals that while cryptocurrencies delivered significantly higher annualized returns (28.5% vs. 8.2% for traditional portfolios), they exhibited extreme volatility (65.3% vs. 12.1%) and severe drawdowns (−73% in 2022). Key risks—including price volatility, regulatory uncertainty (e.g., China’s 2021 ban), and security vulnerabilities (e.g., FTX collapse)—are analyzed alongside behavioral factors like FOMO and herd mentality. The report provides actionable recommendations: aggressive investors may allocate 5–10% to cryptocurrencies, while conservative investors should limit exposure to 1–2%, emphasizing diversification and stop-loss strategies. Supported by 11 peer-reviewed sources, the findings underscore the high-risk, high-reward nature of crypto assets and advocate for a balanced portfolio approach. This study serves as a foundation for understanding crypto investment dynamics, though post-2023 market developments warrant further investigation.
Abstract
This report presents a comparative analysis of cryptocurrency investments versus traditional assets (stocks, bonds, and gold) from 2019 to 2023, evaluating key performance metrics such as returns, volatility, and risk-adjusted performance. The study reveals that while cryptocurrencies delivered significantly higher annualized returns (28.5% vs. 8.2% for traditional portfolios), they exhibited extreme volatility (65.3% vs. 12.1%) and severe drawdowns (−73% in 2022). Key risks—including price volatility, regulatory uncertainty (e.g., China’s 2021 ban), and security vulnerabilities (e.g., FTX collapse)—are analyzed alongside behavioral factors like FOMO and herd mentality. The report provides actionable recommendations: aggressive investors may allocate 5–10% to cryptocurrencies, while conservative investors should limit exposure to 1–2%, emphasizing diversification and stop-loss strategies. Supported by 11 peer-reviewed sources, the findings underscore the high-risk, high-reward nature of crypto assets and advocate for a balanced portfolio approach. This study serves as a foundation for understanding crypto investment dynamics, though post-2023 market developments warrant further investigation.
Cryptocurrency (CRP) has grown in popularity over the last decade. Since there is no central body to control the Bitcoin (BTC) markets, they are extremely volatile. However, several similar variables that cause price volatility in traditional markets also affect cryptocurrencies. Several bubble phases have taken place in BTC prices, mostly during the years 2013 and 2017. Other digital currencies of primary importance, such as Ethereum and Litecoin, also exhibited several bubble phases. Among traditional methods of analysis for this volatile market, only a small number of studies focused on Machine Learning (ML) techniques. The present study objective is to get an in-depth knowledge of the time series properties of CRP data and combine volatility models with ML models. In the hybrid method, we first apply the Nonlinear Generalized Autoregressive Conditional Heteroskedasticity (NGARCH) model with asymmetric distribution to calculate standardized returns, then forecast the UP and DOWN movement of standardized returns through ML models such as Logistic Regression (LR), Linear Discrimination Analysis (LDA), Quadratic Discrimination Analysis (QDA), Artificial Neural Networks (ANNs), K-Nearest Neighbors (KNN), and Support Vector Machine (SVM). The findings show that the proposed hybrid approach of time series models and ML accurately predicts prices; specifically, the KNN model reveals that the scheme can be applicable to CRP market prediction. It is deduced that ML methods combined with volatility models have the tendency to better forecast this volatile market.
We analyze the determinants of Bitcoin (BTC) trade volume in decentralized exchanges (DEXs) and test the claim that BTC trades on these platforms are censorship-resistant. The study finds that overall economic freedom, particularly monetary freedom, correlates indirectly with BTC trade volumes, while capital restrictions on residents' transactions abroad correlate in two different directions. Purchase transactions inversely correlate with BTC volume in DEXs, while sales transactions correlate directly. These results suggest that BTC can be used to hedge against poor institutional frameworks, particularly against poor monetary governance, and as a vehicle for institutional hedging against repressive capital controls and institutional failures. The study's originality lies in its use of on-chain panel data on the volume of BTC transactions, which are country-specific and allow for comparing the impact of country-specific socio-institutional variables on BTC volumes.
How competition affects manipulation by firms of information about important attributes of their products and how such information manipulation impacts firms’ short-term and long-term performance are open empirical questions. We use a setting that is especially suitable for answering these questions—centralized crypto exchanges, on which information manipulation takes the form of inflated trading volume. We find that static and dynamic competition measures are positively associated with volume inflation, indicating that competition may lead to increased information manipulation. Exchanges that manipulate volume obtain short-run benefits but are punished in the long run, consistent with the trade-off between short-lived increases in rents and future losses because of damaged reputation.
This paper was accepted by Agostino Capponi, finance.
Funding: The authors thank the Israel Science Foundation [Grant 2225/21], the Coller School of Management Blockchain Research Institute, the Henry Crown Institute for Business Research in Israel, and the Cornell Fintech Initiative for financial support.
Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2021.02903 .
This article is dedicated to a detailed analysis of market cycles in cryptocurrencies and their impact on investment strategies. The article thoroughly examines various stages of these cycles, their characteristics, and their interconnections with other economic factors. It explores the factors influencing the duration and intensity of these cycles, as well as methods of utilizing them to develop successful investment strategies. The research findings highlight the importance of understanding psychological factors such as FOMO (fear of missing out) and FUD (fear, uncertainty, and doubt), as well as the impact of halving on the cryptocurrency market. Investors who comprehend these aspects and adapt their strategies to the volatile market conditions can achieve success in their investments. The article also emphasizes the importance of in-depth analysis of market cycles for developing effective investment strategies. Special attention is given to the stages of accumulation, markup, distribution, and markdown in the cryptocurrency market, each of which has its unique characteristics and can be leveraged for profit maximization. The influence of regulatory changes, technical innovations, and global financial events on these cycles is examined. The authors also analyze the interaction of supply and demand, particularly how the reduction in mining rewards (halving) affects cryptocurrency values. The study shows that understanding market cycles allows investors to better predict market movements and make more informed decisions. Examining the impact of psychological factors on investor decisions is crucial for avoiding unjustified losses and maximizing gains. Additionally, the article considers long-term investment strategies that take into account halving periods, which can lead to significant increases in asset values. Based on the analysis of cryptocurrency market cycles and the influence of various factors, the work concludes that a deep understanding of these processes is necessary for successful investing. The recommendations provided in the article can be useful for investors looking to develop resilient and effective strategies in the highly volatile cryptocurrency market.
We investigate how distributed denial-of-service (DDoS) attacks and other disruptions affect the Bitcoin ecosystem. In particular, we investigate the impact of shocks on trading activity at the leading Mt. Gox exchange between April 2011 and November 2013. We find that following DDoS attacks on Mt. Gox, the number of large trades on the exchange fell sharply. In particular, the distribution of the daily trading volume becomes less skewed (fewer big trades) and had smaller kurtosis on days following DDoS attacks. The results are robust to alternative specifications, as well as to restricting the data to activity prior to March 2013, i.e., the period before the first large appreciation in the price of and attention paid to Bitcoin.
Cryptocurrencies, such as Bitcoin, have ignited intense discussions. Despite receiving extensive public attention, theoretical understanding is limited regarding the value of blockchain-based cryptocurrencies, as expressed in their exchange rates against traditional currencies. In this paper, we conduct a theory-driven empirical study of the Bitcoin exchange rate (against USD) determination, taking into consideration both technology and economic factors. To address co-integration in a mix of stationary and non-stationary time series, we use the autoregressive distributed lag (ARDL) model with a bounds test approach in the estimation. Meanwhile, to detect potential structural changes, we estimate our empirical model on two periods separated by the closure of Mt. Gox (one of the largest Bitcoin exchange markets). According to our analysis, in the short term, the Bitcoin exchange rate adjusts to changes in economic fundamentals and market conditions. The long-term Bitcoin exchange rate is more sensitive to economic fundamentals and less sensitive to technological factors after Mt. Gox closed. We also identify a significant impact of mining technology and a decreasing significance of mining difficulty in the Bitcoin exchange price determination.
Bitcoin is a purely online virtual currency, unbacked by either physical commodities or sovereign obligation; instead, it relies on a combination of cryptographic protection and a peer-to-peer protocol for witnessing settlements. Consequently, Bitcoin has the unintuitive property that while the ownership of money is implicitly anonymous, its flow is globally visible. In this paper we explore this unique characteristic further, using heuristic clustering to group Bitcoin wallets based on evidence of shared authority, and then using re-identification attacks (i.e., empirical purchasing of goods and services) to classify the operators of those clusters. From this analysis, we consider the challenges for those seeking to use Bitcoin for criminal or fraudulent purposes at scale.
We analyze how network effects affect competition in the nascent cryptocurrency market. We do so by examining early dynamics of exchange rates among different cryptocurrencies. While Bitcoin essentially dominates this market, our data suggest no evidence of a winner-take-all effect early in the market. Indeed, for a relatively long period, a few other cryptocurrencies competing with Bitcoin (the early industry leader) appreciated much more quickly than Bitcoin. The data in this period are consistent with the use of cryptocurrencies as financial assets (popularized by Bitcoin), and not consistent with winner-take-all dynamics. Toward the end of our sample, however, things change dramatically. Bitcoin appreciates against the USD, while other currencies depreciate against the USD. The data in this period are consistent with strong network effects and winner-take-all dynamics. This trend continues at the time of writing.
Bitcoin is a purely online virtual currency, unbacked by either physical commodities or sovereign obligation; instead, it relies on a combination of cryptographic protection and a peer-to-peer protocol for witnessing settlements. Consequently, Bitcoin has the unintuitive property that while the ownership of money is implicitly anonymous, its flow is globally visible. In this paper we explore this unique characteristic further, using heuristic clustering to group Bitcoin wallets based on evidence of shared authority, and then using re-identification attacks (i.e., empirical purchasing of goods and services) to classify the operators of those clusters. From this analysis, we characterize longitudinal changes in the Bitcoin market, the stresses these changes are placing on the system, and the challenges for those seeking to use Bitcoin for criminal or fraudulent purposes at scale.
The Bitcoin scheme is a rare example of a large scale global payment system in which all the transactions are publicly accessible (but in an anonymous way). We downloaded the full history of this scheme, and analyzed many statistical properties of its associated transaction graph. In this paper we answer for the first time a variety of interest-ing questions about the typical behavior of users, how they acquire and how they spend their bitcoins, the balance of bitcoins they keep in their accounts, and how they move bitcoins between their various accounts in order to better protect their privacy. In addition, we isolated all the large transactions in the system, and discovered that almost all of them are closely related to a single large transaction that took place in November 2010, even though the associated users apparently tried to hide this fact with many strange looking long chains and fork-merge structures in the transaction graph.
In the cryptocurrency Bitcoin, users can deterministically derive the private keys used for transmitting money from a password. Such “brain wallets” are appealing because they free users from storing their private keys on untrusted computers. Unfortunately, they also enable attackers to conduct unlimited offline password guessing. In this paper, we report on the first large-scale measurement of the use of brain wallets in Bitcoin. Using a wide range of word lists, we evaluated around 300 billion passwords. Surprisingly, after excluding activities by researchers, we identified just 884 brain wallets worth around $100K in use from September 2011 to August 2015. We find that all but 21 wallets were drained, usually within 24 h but often within minutes. We find that around a dozen “drainers” are competing to liquidate brain wallets as soon as they are funded. We find no evidence that users of brain wallets loaded with more bitcoin select stronger passwords, but we do find that brain wallets with weaker passwords are cracked more quickly.
We examine deals between listed firms and promoters who have been secretly hired to increase their stock prices. This behavior by the secret promoter is illegal (and leads to prosecution) but the actions of the hiring firm are legal. We use data from these prosecutions to analyze the behavior and motivations of the hiring firms. We find that secret promotion leads to an initial increase in the price and trading volume of the firms on the date that the secret promotion started. Subsequently, however, we find that this increase in price is reversed when regulators (e.g. SEC or NASD) take action against these promoters for not disclosing their relationships with the hiring firms. We find that the main motives behind these relationships are to maximize the private benefits of the firm’s managers and owners through pumping the share prices and subsequently dumping their shareholdings.
This paper aims to identify the likely determinants for cryptocurrency value formation, including for that of bitcoin. Due to Bitcoin’s growing popular appeal and merchant acceptance, it has become increasingly important to try to understand the factors that influence its value formation. Presently, the value of all Bitcoins in existence represent approximately 60 million of notional value changes hands each day. Having grown rapidly over the past few years, there is now a developing but vibrant marketplace for bitcoin, and a recognition of digital currencies as an emerging asset class. Not only is there a listed and over-the-counter market for bitcoin and other digital currencies, but also an emergent derivatives market. As such, the ability to value bitcoin and related cryptocurrencies is becoming critical to its establishment as a legitimate financial asset.
We present the first empirical analysis of Bitcoin-based scams: operations established with fraudulent intent. By amalgamating reports gathered by voluntary vigilantes and tracked in online forums, we identify 192 scams and categorize them into four groups: Ponzi schemes, mining scams, scam wallets and fraudulent exchanges. In 21 % of the cases, we also found the associated Bitcoin addresses, which enables us to track payments into and out of the scams. We find that at least $11 million has been contributed to the scams from 13 000 distinct victims. Furthermore, we present evidence that the most successful scams depend on large contributions from a very small number of victims. Finally, we discuss ways in which the scams could be countered.
Bitcoin has enjoyed wider adoption than any previous crypto- currency; yet its success has also attracted the attention of fraudsters who have taken advantage of operational insecurity and transaction irreversibility. We study the risk investors face from Bitcoin exchanges, which convert between Bitcoins and hard currency. We examine the track record of 40 Bitcoin exchanges established over the past three years, and find that 18 have since closed, with customer account balances often wiped out. Fraudsters are sometimes to blame, but not always. Using a proportional hazards model, we find that an exchange’s transaction volume indicates whether or not it is likely to close. Less popular exchanges are more likely to be shut than popular ones. We also present a logistic regression showing that popular exchanges are more likely to suffer a security breach.
Bit coin has emerged as the most successful cryptographic currency in history. Within two years of its quiet launch in 2009, Bit coin grew to comprise billions of dollars of economic value despite only cursory analysis of the system's design. Since then a growing literature has identified hidden-but-important properties of the system, discovered attacks, proposed promising alternatives, and singled out difficult future challenges. Meanwhile a large and vibrant open-source community has proposed and deployed numerous modifications and extensions. We provide the first systematic exposition Bit coin and the many related crypto currencies or 'altcoins.' Drawing from a scattered body of knowledge, we identify three key components of Bit coin's design that can be decoupled. This enables a more insightful analysis of Bit coin's properties and future stability. We map the design space for numerous proposed modifications, providing comparative analyses for alternative consensus mechanisms, currency allocation mechanisms, computational puzzles, and key management tools. We survey anonymity issues in Bit coin and provide an evaluation framework for analyzing a variety of privacy-enhancing proposals. Finally we provide new insights on what we term disinter mediation protocols, which absolve the need for trusted intermediaries in an interesting set of applications. We identify three general disinter mediation strategies and provide a detailed comparison.
Bitcoin is an online communication protocol that facilitates the use of a virtual currency, including electronic payments. Bitcoin's rules were designed by engineers with no apparent influence from lawyers or regulators. Bitcoin is built on a transaction log that is distributed across a network of participating computers. It includes mechanisms to reward honest participation, to bootstrap acceptance by early adopters, and to guard against concentrations of power. Bitcoin's design allows for irreversible transactions, a prescribed path of money creation over time, and a public transaction history. Anyone can create a Bitcoin account, without charge and without any centralized vetting procedure—or even a requirement to provide a real name. Collectively, these rules yield a system that is understood to be more flexible, more private, and less amenable to regulatory oversight than other forms of payment—though as we discuss, all these benefits face important limits. Bitcoin is of interest to economists as a virtual currency with potential to disrupt existing payment systems and perhaps even monetary systems. This article presents the platform's design principles and properties for a nontechnical audience; reviews its past, present, and future uses; and points out risks and regulatory issues as Bitcoin interacts with the conventional financial system and the real economy.
We provide a first systematic account of opportunities and limitations of anti-money laundering (AML) in Bitcoin, a decentralized cryptographic currency proliferating on the Internet. Our starting point is the observation that Bitcoin attracts criminal activity as many say it is an anonymous transaction system. While this claim does not stand up to scrutiny, several services offering increased transaction anonymization have emerged in the Bitcoin ecosystem - such as Bitcoin Fog, BitLaundry, and the Send Shared functionality of Blockchain.info. Some of these services routinely handle the equivalent of 6-digit dollar amounts. In a series of experiments, we use reverse-engineering methods to understand the mode of operation and try to trace anonymized transactions back to our probe accounts. While Bitcoin Fog and Blockchain.info successfully anonymize our test transactions, we can link the input and output transactions of BitLaundry. Against the backdrop of these findings, it appears unlikely that a Know-Your-Customer principle can be enforced in the Bitcoin system. Hence, we sketch alternative AML strategies accounting for imperfect knowledge of true identities but exploiting public information in the transaction graph, and discuss the implications for Bitcoin as a decentralized currency.
This is the first article that studies BitCoin price formation by considering both the traditional determinants of currency price, e.g., market forces of supply and demand, and digital currencies specific factors, e.g., BitCoin attractiveness for investors and users. The conceptual framework is based on the Barro (1979) model, from which we derive testable hypotheses. Using daily data for five years (2009–2015) and applying time-series analytical mechanisms, we find that market forces and BitCoin attractiveness for investors and users have a significant impact on BitCoin price but with variation over time. Our estimates do not support previous findings that macro-financial developments are driving BitCoin price in the long run.
A purely peer-to-peer version of electronic cash would allow online payments to be sent directly from one party to another without going through a financial institution. Digital signatures provide part of the solution, but the main benefits are lost if a trusted third party is still required to prevent double-spending. We propose a solution to the double-spending problem using a peer-to-peer network. The network timestamps transactions by hashing them into an ongoing chain of hash-based proof-of-work, forming a record that cannot be changed without redoing the proof-of-work. The longest chain not only serves as proof of the sequence of events witnessed, but proof that it came from the largest pool of CPU power. As long as a majority of CPU power is controlled by nodes that are not cooperating to attack the network, they'll generate the longest chain and outpace attackers. The network itself requires minimal structure. Messages are broadcast on a best effort basis, and nodes can leave and rejoin the network at will, accepting the longest proof-of-work chain as proof of what happened while they were gone.
We present theory and evidence of stock price manipulation. Manipulators trade in the presence of other traders seeking information about the stock's true value. More information seekers imply greater competition for shares, making it easier for manipulators to trade and potentially worsening market efficiency. Data from SEC enforcement actions show that manipulators typically are plausibly informed parties (insiders, brokers, etc.). Manipulation increases volatility, liquidity, and returns. Prices rise throughout the manipulation period and fall postmanipulation. Prices and liquidity are higher when manipulators sell than when they buy. When manipulators sell, prices are higher when liquidity and volatility are greater.
Cryptocurrency market capitalizations
- Coinmarketcap
The twilight zone: otc regulatory regimes and market quality
- U Brüggemann
- A Kaul
- C Leuz
- I M Werner
Total market capitalization (excluding bitcoin
- Coinmarketcap
Free willy! - identifying the gox buy bot
- Anonymous
Peter Rs theory on the collapse of Mt
- Anonymous
Dark markets may be more harmful than high-frequency trading
- McCrank
Mt. gox trial update: karpeles admits willy bot existence
- Suberg