Bitcoin Exchange Research Articles

The Rise of Bitcoin ETFs and its Impact on Existing Crypto Currency Exchanges

The emergence of Bitcoin Exchange-Traded Funds (ETFs) marks a significant milestone in the evolution of cryptocurrency investment. This research paper investigates the potential impact of Bitcoin ETFs on existing cryptocurrency exchanges, focusing on liquidity dynamics and institutional investment trends. By examining the mechanisms through which ETFs may draw liquidity away from direct Bitcoin exchanges, this study aims to shed light on the evolving landscape of cryptocurrency trading. Additionally, the paper explores the potential for Bitcoin ETFs to attract increased institutional investment in the cryptocurrency market, analyzing the factors that may contribute to this trend. Through a comprehensive analysis of market data and expert insights, this research provides valuable insights into the evolving relationship between Bitcoin ETFs and traditional cryptocurrency exchanges.

An optimized neural network with AdaHessian for cryptojacking attack prediction for Securing Crypto Exchange Operations of MEC applications

Bitcoin exchange security is crucial because of MEC's widespread use. Cryptojacking has compromised MEC app security and bitcoin exchange ecosystem functionality. This paper propose a cutting-edge neural network and AdaHessian optimization technique for cryptojacking prediction and defense. We provide a cutting-edge deep neural network (DNN) cryptojacking attack prediction approach employing pruning, post-training quantization, and AdaHessian optimization. To solve these problems, this paper apply pruning, post-training quantization, and AdaHessian optimization. A new framework for quick DNN training utilizing AdaHessian optimization can detect cryptojacking attempts with reduced computational cost. Pruning and post-training quantization improve the model for low-CPU on-edge devices. The proposed approach drastically decreases model parameters without affecting Cryptojacking attack prediction. The model has Recall 98.72%, Precision 98.91%, F1-Score 99.09%, MSE 0.0140, RMSE 0.0137, and MAE 0.0139. Our solution beats state-of-the-art approaches in precision, computational efficiency, and resource consumption, allowing more realistic, trustworthy, and cost-effective machine learning models. We address increasing cybersecurity issues holistically by completing the DNN optimization-security loop. Securing Crypto Exchange Operations delivers scalable and efficient Cryptojacking protection, improving machine learning, cybersecurity, and network management.

Direct Evidence of Bitcoin Wash Trading

We use the internal trading records of a major Bitcoin exchange leaked by hackers to detect and characterize wash trading—a type of market manipulation in which a single trader clears the trader’s own limit orders to “cook” transaction records. Our finding provides direct evidence for the widely suspected “fake volume” allegation against cryptocurrency exchanges, which has so far only been backed by indirect estimation. We then use our direct evidence to evaluate various indirect techniques for detecting the presence of wash trades and find measures based on Benford’s law, trade size clustering, lognormal distributions, and structural breaks to be useful, whereas ones based on power law tail distributions to give opposite conclusions. We also provide suggestions to effectively apply various indirect estimation techniques. This paper was accepted by Professor Bruno Biais, finance. Funding: J. Li acknowledges support by the U.S. Department of Homeland Security [Grant 205187] through the Criminal Investigations and Network Analysis Center. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2021.01448 .

Is decentralization sustainable in the bitcoin system?

The Bitcoin system is a decentralized monetary system in that any participant can potentially verify and record transactions onto a public ledger. Using a simple model, we show that the number of miners could be negatively (positively) related to the expected rewards if miners with low-operating costs also have less (more) severe financing constraints. We characterize the possibility of miners with low-operating (high-operating) costs facing less (more) severe financing constraints as large-size (small-size) miners. The empirical evidence supports the model's large- and small-size miner characterization prediction. The negative association between the number of miners and expected rewards is attributable to Bitcoin's exchange rate. Collectively, our evidence suggests that even though the Bitcoin system is designed as an egalitarian system, it is likely to evolve into a near-centralized system because of economic forces.

Modeling cryptocurrency market dynamics using machine learning tools

The article analyzes the dynamics of the cryptocurrency market (Bitcoin) using econometric estimation tools based on machine learning models. The forecasting method is improved based on time series decomposition and lagged shifts of financial indicators. An ensemble of short-term forecast models for the Bitcoin exchange rate is built, and its accuracy is analyzed and compared to individual component models. Time series models are used along with calculated financial indicators (ADODS, NATR, TRANGE, ATR, OBV, RSI, ADTV). The absolute deviation of the short-term forecast amounted to $9.5, which is 0.06% of the absolute value.

A Quantum-Resistant Blockchain System: A Comparative Analysis

Blockchain transactions are decentralized, secure, and transparent, and they have altered industries. However, the emergence of quantum computing presents a severe security risk to the traditional encryption algorithms used in blockchain. Post-quantum signatures are required to preserve integrity and reliability. Furthermore, combining the InterPlanetary File System (IPFS) with blockchain provides a long-term strategy for data storage and sharing. This study investigates the integration of post-quantum signatures with the IPFS in a blockchain system, which can considerably enhance blockchain system efficiency. We increase security and efficiency by recording hash values of signatures and public keys within the blockchain and storing their actual content using the IPFS. The study compares NIST-recommended post-quantum signatures with the ECDSA in a Bitcoin exchange scheme to show how effective the system is in countering quantum threats while maintaining optimal performance. This research makes an important addition to the long-term viability and dependability of blockchain technology in the face of the growing landscape of quantum computing breakthroughs.

Change Point Analysis of Time Series Related to Bitcoin Transactions: Towards the Detection of Illegal Activities

This paper proposes a unified framework for the detection of statistically significant changes in time series related to Bitcoin transactions. The time locations of these changes are linked to the occurrences of events which could be further investigated aiming to reveal potential illicit activity. The proposed framework includes: (a) the extraction of 28 features of interest in the form of time series from the Bitcoin transaction history; (b) the selection of features among the extracted ones based on the Partition Around Medoids clustering approach; and (c) the change point analysis of the multivariate time series which is formulated by the medoid time series of each cluster. This analysis enables the identification of structural breaks in the underlying behavior of the time series of interest at certain time points. The proposed framework is applied on the Bitcoin transactions of two entities that have been involved in illicit activities, namely Pirate@40, who orchestrated a high-yield investment programme, and the MintPal Bitcoin exchange platform that was hacked. The analysis results indicate that the estimated change points can be linked to certain event occurrences which may affect the transaction activity and could be further investigated for potential links to illicit actions.

SELECTION OF THE BEST B-SPLINE REGRESSION MODEL FOR ESTIMATING BITCOIN PRICE INCREASES BASED ON ORDER AND OPTIMAL KNOT POINT

The cryptographic virtual currency, bitcoin, is considered the main originator of cryptocurrencies that emerged due United States financial crisis in 2008. The idea was sparked by Nakamoto by introducing an alternative currency system that really refers to the strength of supply and demand. Based on INDODAX data, the bitcoin exchange rate during October 2020 to February 2021 is a condition of a large increase in a short time with a percentage increase of 450%. The increase in bitcoin prices can be modelled using the b-spline nonparametric regression method based on order and optimal knot points based on the smallest Generalized Cross Validation value. The resulting b-spline 4 degree and the number of knots points 5 as the best model with each bases described recursively.

The Impact of Derivatives on Spot Markets: Evidence from the Introduction of Bitcoin Futures Contracts

Cryptocurrencies provide a unique opportunity to identify how derivatives impact spot markets. They are fully fungible and trade across multiple spot exchanges at different prices, and futures contracts were selectively introduced on Bitcoin (BTC) exchange rates against the U.S. dollar (USD) in December 2017. Following the futures introduction, we find a significantly greater increase in cross-exchange price synchronicity for BTC–USD relative to other exchange rate pairs as demonstrated by an increase in price correlations and a reduction in arbitrage opportunities and volatility. We also find support for an increase in price efficiency, market quality, and liquidity. The evidence suggests that futures contracts allowed investors to circumvent arbitrage frictions associated with short-sale constraints, arbitrage risk associated with block confirmation time, and market segmentation. Overall, our analysis supports the view that the introduction of BTC–USD futures was beneficial to the Bitcoin spot market by making the underlying prices more informative. This paper was accepted by Will Cong, Special Section of Management Science: Blockchains and Crypto Economics. Funding: The authors acknowledge financial support from the Global Risk Institute. P. Augustin acknowledges financial support from the Canadian Derivatives Institute and from the Canada Research Chair Program of the Social Sciences and Humanities Research Council Canada. The paper has benefited significantly from a fellow visit of P. Augustin at the Center for Advanced Studies Foundations of Law and Finance funded by the German Research Foundation, project FOR 2774, and from a visiting position of P. Augustin at the finance department of the University of Luxembourg facilitated through the Inter Mobility Programme of the Luxembourg National Research Fund. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2023.4900 .

Arbitrageurs in the Bitcoin ecosystem: Evidence from user-level trading patterns in the Mt. Gox exchange platform

We mine the leaked history of trades on Mt. Gox, the dominant Bitcoin exchange from 2011 to early 2014, in order to detect the triangular arbitrage conducted on the platform. To this end, we exploit user identifiers per trade to identify and describe the individual trading patterns of 440 arbitrageurs. Moreover, we introduce proxies for expertise and document that the expert users' distribution of profits first-order stochastically dominates that of non-expert users. Most importantly, by including user fixed effects, we show that expert users make profits on arbitrage by reacting quickly to plausible exogenous variations on the official exchange rates. A small number of expert arbitrageurs are able to conduct the vast majority of the arbitrage actions and systematically yield higher profits: our results provide empirical evidence that arbitrageurs are few and sophisticated users, characterized by the ability to incorporate information and to quickly react to exogenous shocks within short time scale intervals.

Analysing Cryptocurrency Pump and Dump Scams through Social Media

Abstract: Over the past few years, despite their vulnerability to market manipulation owing to limited liquidity, cryptocurrencies have attracted a lot of public attention and investment. More than $100 billion is currently traded on cryptocurrency exchanges each month, and individuals who are not necessarily experts in the field have begun purchasing these digital assets. A multimodal technique is being utilised to identify and measure coordinated pump and dump scams that are carried out on bitcoin exchanges using social mediaplatforms like Telegram. This strategy attempts to anticipate if a pump effort will be effective by evaluating a variety of parameters.

Exploration of potential money laundering crimes with virtual currency facilities in Indonesia

PurposeThe purpose of this study is to exploration potential money laundering crimes with virtual currency facilities in Indonesia. Money laundering using crypto is the process of disguising the origin of money obtained illegally. Then, the perpetrator transfers it to a legitimate business. Virtual money then started to become a phenomenon in society since the emergence of cryptocurrencies as a form of technology development of e-commerce activities.Design/methodology/approachThis research method is normative law which is prescriptive. The data collection technique used is document study or literature study by collecting primary and secondary legal materials.FindingsThe results of this study show that the bitcoin virtual currency has the potential to act as a means of money laundering. There are technologies and online platforms that are moving with more sophisticated methods. Through bitcoin exchanges, it has the greatest potential for money laundering. The usage of virtual currency (cryptocurrency) by those who commit money laundering offenses is responsible for the actions’ severe negative effects on the State of Indonesia.Originality/valueTo the best of the author’s knowledge, this is the first study conducted in Indonesia that explores potential money-laundering crimes using virtual currency facilities.

Arbitrage across different Bitcoin exchange venues: Perspectives from investor base and market related events

AbstractThis paper examines the impact of market related events and investor base on the spread of Bitcoin prices between two exchange platforms, Coinbase and Binance. Based on high‐frequency data samples collected from 2019 to 2021, we show how investors from different bases react differently to market related events, which create the price spreads between exchange platforms. We also identify the arbitrage opportunities these spreads create and establish arbitrage strategies for all identified events to exploit the variations in Bitcoin prices traded on both platforms. Findings indicate arbitrage offers profits that are higher overall than holding Bitcoin on either platform.

The Essence and Place of Cryptocurrency in the Financial System

Abstract. Introduction. The history of the emergence of Bitcoin and other cryptocurrencies is analyzed. Basic concepts related to blockchain technology are explained. The main focus is on issues important from an investor's point of view, as well as on technical aspects, including the essence and importance of blockchain technology. Purpose. The purpose of the article is to generalize and systematize the available information about the emergence of cryptocurrencies and analyze their patterns. Results. The specifics of digital assets and the bitcoin exchange rate in 2012-2021 were studied in more detail. It was found that on the cryptocurrency market you can earn (as well as lose) both as a trader and as a so-called cryptocurrency hodlers. A rating of cryptocurrency exchanges was developed according to the following indicators: security, number of crypto currencies, fiat currencies, advantages of the exchange, disadvantages of the exchange. Cryptocurrency exchanges are a central part of the entire digital collection ecosystem today. Currently, there are already several hundred crypto exchanges on the market, which differ in terms of transactions, security levels or listed values. In this article, we have described cryptocurrency as objectively as possible so that you can assess for yourself whether it will be the right form of investment for you. Conclusions. The wide choice of service providers and the fact that digital currencies are a relatively new form of investment means that finding the best place to trade is not easy. The cooperation of international financial conglomerates in the development of blockchain technology will save these enterprises billions of dollars per year and will be able to improve their operations and eliminate errors related to the human factor. Participants in the financial system are forced to propose standards that would apply to each participant in the network without disturbing the established status quo in international markets.

Turn-of-the-candle effect in bitcoin returns

This study discovers a statistically and economically significant intraday anomaly on Bitcoin markets. Positive returns of 0.58 bps per minute are disproportionately concentrated at the turn of 15-min candles (in minutes 0, 15, 30, and 45 of each trading hour). Average returns in other trading minutes are negative. The effect is consistent across Bitcoin exchanges, in quantile regression models, and TGARCH-M estimations with heavy tails, and persist in out-of-sample tests. A high-frequency strategy that exploits this “turn-of-the-candle” effect can be net-outperforming with initial investment as low as $5,000. The anomaly is detected in the data starting from mid-to-late 2020, is potentially associated with algorithmic trading relying on the arrival of 15-min candle information, and its discovery contributes significantly to the understanding of cryptocurrency adaptive market efficiency.

CRYPTOCURRENCY MARKET TRANSFORMATION DURING PANDEMIC COVID-19

The pandemic and subsequent changes in various spheres of human activity have also transformed consumer behavior, particularly in the cryptocurrency market. The article is aimed at identifying the priority directions of transformations taking place in the cryptocurrency market in the conditions of the Covid-19 pandemic under the influence of certain groups of factors. System and network approaches to understanding the cryptocurrency market have been identified. The cryptocurrency market is considered from a functional and institutional point of view. From a functional point of view, the cryptocurrency market is a set of economic relations in cyberspace regarding cryptocurrency mining, initial coin offering (ICO) and circulation of cryptocurrencies based on the laws of supply and demand. From an institutional point of view, the cryptocurrency market is a set of participants in the virtual currency schemes who carry out cryptocurrency transactions. The following signs of cryptocurrency market segmentation are justified such as those depending on the market capitalization of the cryptocurrency; on the nature of the crypto assets movement; on operations carried out on the market; on the region; on consumers of services. Factors which influence the functioning of the cryptocurrency market are systematized according to the following groups: macroeconomic, price, environmental, geographic, market, behavioral and technological. The influence of gold, oil prices, the daily number of Covid-19 cases and deaths from Covid-19, the MSCI ACWI global stock index, the iShares MSCI All Country Asia ex Japan ETF, the Wilshire 5000 Total Market Index on the Bitcoin exchange rate is revealed. The trends in the cryptocurrency market development in the post-war period are justified, namely the growth of investors’ interest in cryptocurrencies against the background of the initial coin offering collapse; growth of payments in cryptocurrencies; strengthening the regulatory landscape on a global and national scale; integration of the cryptocurrency market with traditional finance; attracting non-typical participants to the cryptocurrency business; expansion of participants in the infrastructure of the cryptocurrency market due to the rapid cryptocurrency market development, in particular, due to the production of equipment for its operation.

Bibliometric analysis of Journal of Money Laundering Control: emerging trends and a way forward

PurposeThe purpose of this study is to provide a bibliometric analysis of the Journal of Money Laundering and Control (JMLC) from 2010 to 2021 and map its way forward.Design/methodology/approachA range of bibliometric techniques have been used to analyse the performance of JMLC from Volume 14 (Issue 1) to Volume 24 (Issue 4). The Scopus database has been used to analyse the documents of JMLC. A total of 294 documents are reviewed. The bibliographic data has been analysed using the software VOS viewer and R-studio (Biblioshine) to assess the trend of publications, word growth, keyword co-occurrence, citation analysis, most prolific authors and authors’ impact.FindingsJMLC’s academic contributions, influence and impact have grown progressively. The thematic structure of the journal has evolved into six bibliographic clusters, noted as prevention of corruption due to money laundering; compliance and regulation of money laundering; customer due diligence; role of Financial Action Task Force (FATF) in the financial system of developing countries; control of terrorism and terrorist financing; and role of money laundering in the proceeds of crime.Research limitations/implicationsThe constraint of this endeavour largely arises from its selection of bibliographic data being confined to Scopus.Practical implicationsThe results of the study would help the current and future authors to understand the emerging themes in the field of money laundering and control. They are also going to help the editors of the journals of this domain to understand the emerging themes and how the published documents are going to contribute the society, throwing light on the controlling and compliance part of money laundering. Future research directions are provided in tackling the problem of money laundering, corruption, terrorism, crime, etc. with the help of financial intelligence, strong FATF all around the world, machine learning, Bitcoin exchange management and global knowledge management.Originality/valueTo the best of the authors’ knowledge, this is the first objective assessment of the journal. Thus, the results of the study are useful to past and prospective authors, editorial board members, editors, readers and reviewers to gain a one-stop understanding of anti-money laundering actions through the contributions of JMLC.

THE STATE AND PROSPECTS OF THE DEVELOPMENT OF CRYPTOCURRENCIES IN THE DIGITAL ECONOMY

Purpose. The aim of the article is to determine the place of cryptocurrencies in the digital economy, assess their state and development trends, research prospective directions for expanding the scope of their use by introducing innovative technologies and tools, and reducing the risks of investing in crypto assets. Methodology of research. The following research methods were used to achieve the set goal: induction and deduction – in the process of identifying cause-and-effect relationships and trends in the development of cryptocurrencies in the digital economy; analysis and synthesis – in the process of studying the individual essential characteristics of the category "cryptocurrency"; comparison – in the process of researching changes in the market capitalization of cryptocurrencies, the dynamics of the Bitcoin exchange rate, the dynamics of the market capitalization of cryptocurrencies and DeFi; graphic – to visualize the results of the study. Findings. The influence of environmental factors on the dynamics of the development of cryptocurrencies during 2021‒2023 has been determined. The directions of their development in the digital economy are substantiated, which include the correlation of the crypto market with traditional markets and the financial sector of the economy, the emergence of new types of cryptocurrencies that expand the range of offered market tools, the expansion of the scope of use of cryptocurrencies through the introduction of innovative technologies and tools. Alternative directions for investing in crypto assets have been identified. A comparative assessment of the risks of traditional investing and investing in cryptocurrencies was carried out. Originality. Determining the essential characteristics of cryptocurrencies, such as price volatility, investment attractiveness and riskiness, has been further developed. Prospective directions for the use of innovative tools in the crypto industry, in particular, decentralized finance (DeFi), are substantiated. Practical value. Conclusions and proposals substantiated by the results of the research can be used in the process of carrying out operations with cryptocurrencies and making decisions by market subjects regarding directions and instruments for investing in crypto assets. Key words: cryptocurrencies, market capitalization, rate dynamics, price volatility, innovative technologies and tools in the crypto industry, decentralized finance (DeFi), alternative investments in crypto assets.

ОСНОВНІ ВИКЛИКИ ФУНКЦІОНУВАННЯ ІНДУСТРІЇ КРИПТОВАЛЮТ НА ФІНАНСОВОМУ РИНКУ

The article analyzes the rating of Ukraine according to the Global Cryptocurrency Adoption Index. It is noted that out of the TOP-20 countries in the rating, there are ten countries with below-average income, eight countries with above-average income and two countries with high income. This trend demonstrates the dominance of developing markets. The dynamics of the bitcoin and USD exchange rate are analyzed. Forecasting of the bitcoin exchange rate was carried out using the exponential smoothing method, because this method showed the smallest mean absolute error. The forecast results show the growth of the bitcoin rate. The interdependence between exchange rate of bitcoin cryptocurrency and pairs of the most influential world currencies, world prices for precious metals and securities rates on the largest stock exchanges is determined using correlation-regression analysis. The advantages of using cryptocurrencies have been identified, including high speed of transactions, reduction of the number of intermediaries and low fees. Also defined the threatening nature of the development of the crypto-industry for the economic potential of the state, taking into accountavailable withcurrent global challenges such as cyber-attacks and fraud and data theft. Real fraud schemes in the field of cryptocirculation are considered. The main challenges to the functioning of the cryptocurrency industry are analyzed, including volatility, uncertainty, risk of loss, insecurity of owners, lack of guarantees, large number of cryptocurrencies, technical risk, fraud and data theft. It is noted that without determining the clear legal status of cryptocurrencies in the country, it is impossible to resolve the legal, accounting and tax consequences of these transactions. It was determined that for the legal circulation of cryptocurrencies, the creation of a financial institution or a special state body, which should exercise control over the circulation of cryptocurrencies, must be ensured as a minimum; introduction of taxation for companies whose activities are related to the crypto industry; establishing the obligation of users to declare their income and profits from income regarding crypto-assets in the national currency, etc.

How many neurons are needed to make a short-term prediction of the Bitcoin exchange rate?

The goal of our work was to select a neural network architecture that would give the best prediction of the Bitcoin exchange rate using historical data. Our work fits into the very important topic of predicting the value of the cryptocurrency exchange rate, and makes use of recent data which, as a result of the high Bitcoin exchange rate dynamics of the last year, differs significantly from those of previous years. We propose and test a number of neural network-based architectures and conduct a discussion of the results. Unlike previous state-of-the-art works, we conducted a comprehensive comparison of three different neural network-based models: MLP (multilayer perceptron), LSTM (long short-term memory) and CNN (convolutional neural network). We tested them for a wide range of parameters. The results we present are, to the best of our knowledge, the most up to date when it comes to the application of artificial intelligence methods for the prediction of cryptocurrency exchange rates. The best-performing architectures were used for a website that gives real-time predictions of the Bitcoin exchange rate. The website is available at http://stpbtc-ii.up.krakow.pl/. Source codes of our research are available to download in order to make our experiment reproducible.