Bitcoin Exchange Rate Research Articles

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.

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 .

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.

The Impact of the COVID-19 Pandemic on the Volatility of Cryptocurrencies

This study aimed to investigate the interactions between Bitcoin to euro, gold, and STOXX50 during the period of COVID-19. First, a bibliometric analysis based on the R package was applied to highlight the research trends in the field during the period of the COVID-19 pandemic. While investigating the effects of the pandemic on Bitcoin, the number of cases of COVID-19 was used as a proxy. Using daily data for the period 1 March 2020 to 3 March 2020 and based on a vector autoregressive model, impulse response, and variance decomposition were utilized to analyze the dynamic relationships among the variables. The results revealed that the COVID-19 cases and gold hurt the exchange rate of Bitcoin to euro, while there was great volatility regarding the response of Bitcoin to a shock of STOXX50. The Granger causality test was constructed to investigate the relationships among the variables. The results show the presence of unidirectional causality running from new cases to STOXX50 and from STOXX50 to gold. This study contributes to the existing scholarly research into the dynamic relationships that appeared among Bitcoin, gold, and STOXX50 in a period of great uncertainty. Finally, the findings have significant implications for investors, who are interested in diversifying their portfolios.

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.

CRYPTOCURRENCY: FEATURES AND PROSPECTS OF DEVELOPMENT

Introduction. The development of information technologies led to the emergence of new financial instruments, payment systems, methods and payment platforms. Cryptocurrency is a means of circulation and payments fundamentally different from traditional ones. Awareness of the emergence and existence of electronic money is quite high, however, awareness of the mechanism of its functioning and the possibility of using/making calculations, financing projects is low. The puppose of the article is to highlight the main characteristic features of cryptocurrencies, to justify the advantages and disadvantages of cryptocurrencies, to analyze the state, dynamics and development prospects of the cryptocurrency market. Results. Characteristic features of cryptocurrencies include: lack of payment system administration; impossibility of forced return, withdrawal or "freezing" of payments (without access to the owner's private key). Cryptocurrency is an investment object, and the speculative-investor type of demand for cryptocurrencies is also noted. The authors identified the advantages of using cryptocurrencies, including: equal conditions of use by users, unlimited possibilities of transactions, their transparency, lack of complications in international transfers and the impossibility of blocking or freezing a cryptocurrency wallet and its funds, no commission, open code of cryptocurrency, decentralization. Among the disadvantages of cryptocurrencies are identified: the danger of losing the key to cryptocurrency; the difficulty of returning funds in case of erroneous currency transfer; lack of guarantees for keeping electronic wallets; intervention by hackers; instability of the cryptocurrency exchange rate, dependence of the exchange rate on demand; high energy consumption; distrust of users. The dynamics of the exchange rate of bitcoin and ethereum were analyzed, significant fluctuations in their exchange rate relative to the dollar during the research period were noted. The difference in the views of countries on the issue of regulating the circulation of cryptocurrencies is described (recognition of operations with cryptocurrency as illegal activity, full / partial ban, legalization of legal circulation of electronic money). Conclusions. Barriers and prospects for the development of the electronic money market have been identified. Given the described features of cryptocurrencies, the prospects of recognition / settlement of cryptocurrencies as a financial instrument at the same level as freely convertible currencies (dollar, euro, etc.) are unrealistic and impractical within the framework of the existing mechanisms of functioning of the cryptocurrency market. The prospects for the growth of cryptocurrency circulation in the sectors of NFT-tokens (in games, music, art, sports) were noted.

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.

SYSTEM ANALYSIS OF SUBJECTS CRYPTOCURRENCIES OPERATIONS IN THE CONDITIONS OF GLOBAL CHALLENGES

The article considers cryptocurrency as a new type of intangible assets and the regulatory and legal support for its implementation. Particular attention is paid to defining the content, legal status, features of accounting, and taxation of transactions with such assets. The market capitalization and bitcoin forecast are analyzed. The interdependence between the exchange rate of bitcoin and pairs of the most influential world currencies, world prices for precious metals, and securities rates on the largest stock exchanges is determined. The most significant influencing factors on the bitcoin price are determined using correlation and regression analysis. The advantages of using cryptocurrencies have been identified, including high speed of transactions, reduction of the intermediaries number, and low fees. The threatening nature of the crypto-industry development for the economic potential of the state is also determined, taking into account available with current global challenges such as cyberattacks and fraud and data theft. Real fraud schemes in the field of crypto-circulation are considered. 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 cryptocurrencies circulation, 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 crypto-assets, etc. Because of this, the functions of state authorities in regulating operations with cryptocurrencies are characterized, and the changes that will be introduced to the Tax Code of Ukraine are analyzed, regarding the taxation of transactions with cryptocurrencies, which in the future will make it possible to increase budget revenues, regulate and facilitate accounting and taxation of transactions with cryptocurrencies, use legal remedies for virtual assets, reduce possible tax evasion, 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.

ARIMA MODEL FOR FORECASTING THE BITCOIN EXCHANGE RATE AGAINST THE USD

This study analysis forecasting the bitcoin exchange rate against the USD. The dataset selected for this study starts from January 2015 to June 2022. This study's methodology uses autoregressive integrated moving average forecasting (ARIMA). The overall outcomes of this study were gathered from the statistical software Minitab 21.1. The Box Jenkins approaches are also used to predict the best model. To determine the ARIMA model parameter, this study did autocorrelation function (ACF) and partial autocorrelation function (PACF) analyses. According to the Box-Cox transformation method, log transformation was selected. The outcome demonstrates that the seasonal with the regular difference in the Bitcoin exchange rate against the USD is a stationary data series. The forecasting model used in this study is ARIMA (1,1,0) (2,1,1)12. This predicted model is identified through the Mean squared error by comparing the other guessing ARIMA models. After the prediction, 5 Month bitcoin exchange rate against the USD. Investors will be able to estimate the bitcoin exchange rate against the USD with the use of this information, but volatility must also be properly watched. This will aid investors in making better investment decisions and increase profits. In future studies, better consider another exchange rate of BTC and software experts will develop such type of software based on ARIMA models for prediction.

Analysis of cryptocurrency exchange rates vs USA dollars using a new Dagum model

This paper offers the introduction of a new updated form of the Dagum distribution. The new updated form of the Dagum model is called a novel generalized-Dagum distribution. The proposed novel generalized-Dagum distribution is a prominent updated form of the Dagum model with a single additional/extra parameter. The novel generalized-Dagum model is produced by mixing the Dagum distribution with the novel generalized-M distributions approach. The heavy-tailed properties of the novel generalized-Dagum model are obtained. The derivation of the estimators and a simulation study of the novel generalized-Dagum distribution are also provided. Finally, the novel generalized-Dagum model is illustrated by analyzing two real-life data sets related to the financial sector. The first data set represents the Bitcoin exchange rates vs the United States dollars. Whereas, the second data set represents the Ethereum exchange rates vs the United States dollars. Using the Bitcoin and Ethereum exchange rates data sets, the fitting power of the novel generalized-Dagum model is compared with the transmuted Dagum distribution and a new modified Dagum distribution.

Application Deep Learning to Predict Crypto Currency Prices and their Relationship to Market Adequacy (Applied Research Bitcoin as an Example)

redicting currency rates is important, for everyone who is trading and trying to build an investment portfolio from a range of crypto currencies. It is not subject to the same restrictions as fiat currencies. In this study, we seek to predict the exchange rate of BIT-COIN against the US dollar. The short-term data (365 observations) is processed using the LSTM model as one of the neural network models. Modeling is conducted by training a sample size of 67%, taking into account sharp fluctuations in the price of trade and a certain level of market efficiency. The GARCH model is used to select appropriate historical periods for how the LSTM model works and to test proficiency at the weak, semi-strong, and strong levels. The data series obtained from the website (Investing.com) have been processed. The researchers have found that the performance of the neural network improves as the EPOCH value increases with a training (research) period of 50 days before, which is consistent with the results of the proficiency test at the weak level. It agrees with the results of the sufficiency test at the weak level, which indicates that in the case under study (the Bitcoin market is effective at the weak level). It is advised that crypto-currency investors rely more on the historical trend of the price of the currency than on its current price, taking advantage of the artificial neural network model (LSTM) in dealing with little data of high volatility.

Analysis of the Competitive Environment in the Electronics Market: the Global Crisis of the Semiconductor Industry and Global Development Trends

The relevance of the study lies in the large-scale and progressive impact of the shortage in the semiconductor market on the key industries of modern electronics production. Currently, the production of microchips shows the highest growth rates, the sphere is directly associated with the fourth industrial revolution, so leading manufacturers are actively seeking either to increase market share or to gain leadership altogether. As a result, competition is intensifying both between individual companies and between countries. The purpose of the study is to determine the degree of influence of the shortage of semiconductors on the final cost of goods based on microchips. The main task is to analyze the dependence of the cost of video cards on the cryptocurrency exchange rate, the growth in demand for the extraction of which is one of the factors that influenced the semiconductor crisis. The article analyzes the current state of the semiconductor industry market, describes the key players, manufactured products by type. The chronology of events that led to the shortage of microchips – the main basis for any modern electronics – has been built. The article describes the main affected industries from the crisis in the semiconductor market, analyzes the consequences in quantitative and qualitative terms. Conclusions are drawn about the global role of cryptocurrency mining in the progressive shortage of microchips. In the course of the study, general scientific methods were applied, such as analysis, synthesis, comparison, as well as special methods (statistical-economic and econometric analysis). A paired linear regression model is constructed to identify the relationship between the Bitcoin exchange rate and the cost of popular video card models. As a result of the study, the relationship between the cryptocurrency exchange rate and the price of video cards was determined, and the stock index of the semiconductor industry was analyzed.

Parametric Distribution’s Scrutiny over the Exchange Rate of Bitcoin

Purpose: The research aims to analyze the log-returns of Bitcoin exchange rates against the US Dollar and Chinese Yuan by applying parametric distributions for understanding behavior and suggesting a best-fitted distribution.
 Design/Methodology/Approach: Methodology involves the volatility risk analysis using the GARCH model for analyzing the behavior of Bitcoin Exchange rates of USD and CNY.
 Findings: The results showed that the Weibull distribution gives the best fit to both of the currencies’ exchange rates
 Implications/Originality/Value: The exchange rates of Bitcoin analyzed in this study in midst of myriad other cryptocurrencies using parametric distributions thereby encouraging the application of nonparametric and semiparametric distributions in similar scenarios. The application of this study would enable not only individual investors but also institutional investors and venture capital firms to stay informed of alternating trends and movements through distributions for predicting future returns.

Effect of the Volatility of the Crypto Currency and Its Effect on the Market Returns

In this study, cryptocurrency is a type of digital money that uses cryptography to protect transactions, limit the production of new units, and verify asset transfers. The focus of this research is to see how volatile Bitcoin exchange rates and returns. The standard deviation of logarithmic returns is calculated to gauge volatility. The finding of the results was based on the Shapiro-Wilk test that was employed to predict normality in this investigation. In addition, the box-whisker plot and statistical process control chart were used to find high volatility. Volatility is now regarded to be a high value. Eventually, Because of the current high level of volatility, investing in Bitcoin is seen as a high-risk endeavor. The purpose of this study is to assist investors in developing a strategy that maximizes returns while minimizing risk.

ARFURIMA models: simulations of their properties and application

Abstract This article defines the Autoregressive Fractional Unit Root Integrated Moving Average (ARFURIMA) model for modelling ILM time series with fractional difference value in the interval of 1 < d < 2. The performance of the ARFURIMA model is examined through a Monte Carlo simulation. Also, some applications were presented using the energy series, bitcoin exchange rates and some financial data to compare the performance of the ARFURIMA and the Semiparametric Fractional Autoregressive Moving Average (SEMIFARMA) models. Findings showed that the ARFURIMA outperformed the SEMIFARMA model. The study’s conclusion provides another perspective in analysing large time series data for modelling and forecasting, and the findings suggest that the ARFURIMA model should be applied if the studied data show a type of ILM process with a degree of fractional difference in the interval of 1 < d < 2.

Analyzing and de-anonymizing Bitcoin networks: An IP matching method with clustering and heuristics

The anonymity and de-anonymity of blockchain and Bitcoin have always been a hot topic in blockchain related research. Since Bitcoin was created by Nakamoto in 2009, it has, to some extent, deviated from its currency attribute as a trading medium but instead turned into an object for financial investment and operations. In this paper, the power-law distribution that the Bitcoin network obeys is given with mathematical proof, while traditional de-anonymous methods such as clustering fail to satisfy it. Therefore, considering the profit-oriented characteristics of Bitcoin traders in such occasion, we put forward a de-anonymous heuristic approach that recognizes and analyzes the behavioral patterns of financial High-Frequency Transactions(HFT), with realtime exchange rate of Bitcoin involved. With heuristic approach used for de-anonymity, algorithm that deals with the adjacency matrix and transition probability matrix are also put forward, which then makes it possible to apply clustering to the IP matching method. Basing on the heuristic approach and additional algorithm for clustering, finally we established the de-anonymous method that matches the activity information of the IP with the transaction records in blockchain. Experiments on IP matching method are applied to the actual data. It turns out that similar behavioral pattern between IP and transaction records are shown, which indicates the superiority of IP matching method.