Academic papers on bitcoin exchange
Citation: Lennart Ante. Bitcoin transactions, information asymmetry and trading volume[J]. Quantitative Finance and Economics, , 4 3 : Article views PDF downloads Cited by 4. Tables 4.
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Academic papers on bitcoin exchange
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Content:
- Relationship between Bitcoin Exchange Rate and Other Financial Indexes in Time Series
- The rise of using cryptocurrency in business
- Bitcoin’s Price Was Artificially Inflated, Fueling Skyrocketing Value, Researchers Say
- Analysis of Return and Risk of Cryptocurrency Bitcoin Asset as Investment Instrument
- 16% of Americans say they have ever invested in, traded or used cryptocurrency
- What Is Cryptocurrency?
- Article Info.
- What To Know About Cryptocurrency and Scams
- Bitcoin Transaction Networks: An Overview of Recent Results
- What is bitcoin and how does it work?
Relationship between Bitcoin Exchange Rate and Other Financial Indexes in Time Series
The Bitcoin exchange rate BER is influenced by many variables such as human speculation and policies and, thus, is dependent on the financial system. The fluctuation of BER submitted has been extensively investigated. However, the correlation analysis of the short- and long-term effects by indicators of online sentiment is unexplored. The Bitcoin exchange rate BER is extremely volatile. Kurka concluded that BER is independent of any financial asset classes in the system, but its spillover effect affected the traditional financial markets [ 1 ].
The pricing models of stock price or exchange rate have assumptions of transactions by rational investors. However, researchers pointed out that investment decisions made by investors are not necessarily rational. Thus, behavioral financial theories emerged to explain irrational decisions. The higher the visibility of a firm, the more the interest investors have in the stock. It yields higher price returns and greater trading volume.
Cai et al. The vector autoregression VAR analysis of the short- and long-term impacts and Granger causal relationship [ 5 — 7 ] are employed to develop a prediction model for BER change for providing a reference for Bitcoin hedging operation to investors.
The BER is a new investment tool with higher volatility to the traditional financial product. Investors have little hedge and others reference target to avoid the risk of BER. The forecasting model of BER can offer mostly relation financial products and be applied for hedge, arbitrage for investors.
The result expected the SVI should have higher relationship in the short and long periods. Section 3 presents the VAR for the data analysis as the research method. Section 4 describes the analysis results.
Finally, Section 5 concludes this article. The other researchers also employed Google SVI to measure investor attention [ 10 , 11 ]. The time range for searching is customized or selected in the past 1, 4 hours, 1, 7, 30, 90, and 5 years.
Up to 5 keywords are analyzed simultaneously. The search items are searched for their trends in a single country or all over the world.
The categories are selected by the industry of interest or all categories. After determining the keywords, region, periods, and categories, Google Trends generate a trend chart with a standard quantitative range from 0 to and calculate the SVI data based on the average time series, but the data frequency is a week.
SVI calculation formula is as follows:. The SVI may yield different results for the same keywords according to different query, time, date, and geographic location. When Google compiles SVI data, it does not search all data but randomly selects samples.
However, different results did not change the research outcomes [ 12 ]. Takeda and Wakao present the SVI has a positive impact on the stock price and volume [ 13 ]. Aouadi et al. Zhang et al. Details are shown in Figure 2. The VIX greater than 40 indicates that market investors expect a strong fluctuation of stock index in the future, that is, irrational panic.
When the index is less than 15, it means the investors believe the volatility in the future stock market to be mild which shows irrational exuberance. Qadan et al. In a period of extreme uncertainty, investors tend to be more risk-averse and therefore need higher idiosyncratic volatility IVOL premium at a high level of VIX [ 15 ]. Tsai et al. Simon and Wiggins showed that the VIX index was used to predict the future stock market [ 17 ]. Lee pointed the new sentiment of the current period has a positive relationship with investment reports, and the new sentiment of the lagged period has a negative relationship with investment aspirations [ 18 ].
Dennis et al. When the VIX soars and the market shows extreme fear, it would be the best opportunity to enter the stock market. Kurka studied the interaction between Bitcoin and traditional finance assets [ 1 ]. The results showed that BER was independent of any financial system assets.
Though traditional financial assets had little impact on the BER trend, the spillover effect of BER was significant in the traditional financial market. The results supported that the SVI had a vital influence on the price and volume of Bitcoin. Dastgir et al. It employed the Granger causality to test the causal relationship between the interest in Bitcoin and investment returns.
The conclusion supported the existence of bidirectional causality between Bitcoin and investment returns. The research process was divided into two aspects as shown in Figure 3. For the short-term impact analysis, the VAR model and Granger causality were employed to test the explanatory variables of BER and verify their relationship, respectively. For the long-term impact, Nelson and Plosser argued that the variable difference was lost in the implicit information on the long-term equilibrium through the stationary sequence [ 22 ].
Therefore, the co-integration analysis and vector error correction model VECM validated the long-term relationship between the variables. Equation 4 , then, becomes. Equation 5 is used for the vector error correction model VECM in which each equation belongs to an error correction model [ 25 ]. Before establishing the VAR model, it is necessary to choose the optimal lagged periods.
The number of periods corresponding to the minimum value of the measurement of AIC or SC is the optimal number of lagged terms. Multivariate Granger causality analysis is performed by fitting a VAR model to the time series. Let be a d -dimensional multivariate time series. A time series X i is called a Granger cause of another time series X j , if at least one of the elements is significantly larger than zero.
This research mainly discussed the key factors that affect the changes in BER by referring to Cai et al. The period for sampling was from April 29, , to June 22, The data sources were Yahoo Finance and Bloomberg.
The data frequency was a day, and the data processing method did not affect the final results. If there was no observation value for any variable on the same day, the data of that day were deleted [ 28 ].
A total of 1, daily observation values for each variable were used. The analysis was carried out in two processes as shown in Figure 4. We used the VAR model and Granger causality to test the explanatory stationary time series variables for the short-term impact.
Then we used the co-integration analysis and vector error correction model VECM to validate the long-term relationship between the nonstationary variables. The descriptive statistics, VAR model analysis, and the co-integration relationship were performed and illustrated below. By taking the natural logarithm and first-order difference, all the variables were in a significant stationary sequence as shown in Table 2.
The research employed the AIC to determine the optimal number of two lagged periods. Table 3 shows the details of the optimal lagged periods. The first-order difference in the variables presents a stationary sequence and is used to analyze the short-term influence of the variables with the VAR model.
The results are shown in Table 4. BER of the two lagged periods had a positive impact 0. The Granger causality diagram of the short-term variables affected the BER. Nelson and Plosser supposed that a different process caused the time series to lose long-term information [ 22 ]. That is, all nonstationary time series become stationary after the first-order difference operation, so it is used to study the short-term influence between variables.
Johansen co-integration test was used to test long-term relationship among the variables, and the Trace test to obtain the number of co-integration vector CE equation sets for variables of no difference [ 31 , 32 ]. As shown in Table 6 , the hypothesis assumes that there is none CE, and the trace statistics shows Through the Johansen Co-integration test, two sets of co-integration vector equations were obtained by using the trace test method.
The coefficients of the equation variables are highly significant to each other. Granger causality is a statistical concept of causality that is based on VAR.
The coefficient of granger causality test is assumed that does not influence between two variables under null hypothesis as shown in Table 7. If the probability is larger than 0. The results of the granger causality test are shown in Table 7. Figure 5 shows all variables that affect BER in the long-term. The analysis results of this research suggested the co-integrated equilibrium and feedback relationship of the Granger causality between BER and Google SVI in the long term.
In addition to confirming the results of Cai et al. The price of Bitcoin fell back to the equilibrium value, which verifies the investor attention theory. The results help investors hedging or arbitrating engaged Bitcoin-related risks. The data used to support the findings of this study are available from the corresponding author upon reasonable request. This is an open access article distributed under the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Article of the Year Award: Outstanding research contributions of , as selected by our Chief Editors. Read the winning articles. Journal overview. Special Issues. Academic Editor: Teen-Hang Meen.
The rise of using cryptocurrency in business
Cryptocurrencies are distributed systems that allow exchanges of native and non- tokens between participants. The availability of the complete historical bookkeeping opens up an unprecedented possibility: that of understanding the evolution of a cryptocurrency's network structure while gaining useful insights into the relationships between users' behavior and cryptocurrency pricing in exchange markets. In this article we review some recent results concerning the structural properties of the Bitcoin Transaction Networks , a generic name referring to a set of three different constructs: the Bitcoin Address Network , the Bitcoin User Network , and the Bitcoin Lightning Network. The picture that emerges is of a system growing over time, which becomes increasingly sparse and whose mesoscopic structural organization is characterized by the presence of an increasingly significant core-periphery structure. Such a peculiar topology is accompanied by a highly uneven distribution of bitcoins, a result suggesting that Bitcoin is becoming an increasingly centralized system at different levels.
Bitcoin’s Price Was Artificially Inflated, Fueling Skyrocketing Value, Researchers Say
A bitcoin exchange is a digital marketplace where traders can buy and sell bitcoins using different fiat currencies or altcoins. A bitcoin currency exchange is an online platform that acts as an intermediary between buyers and sellers of the cryptocurrency. Bitcoin exchange platforms match buyers with sellers. Like a traditional stock exchange, traders can opt to buy and sell bitcoin by inputting either a market order or a limit order. When a market order is selected, the trader is authorizing the exchange to trade the coins for the best available price in the online marketplace. With a limit order set, the trader directs the exchange to trade coins for a price below the current ask or above the current bid , depending on whether they are buying or selling. To transact in bitcoin on an exchange, a user has to register with the exchange and go through a series of verification processes to authenticate their identity.
Analysis of Return and Risk of Cryptocurrency Bitcoin Asset as Investment Instrument
The Bitcoin exchange rate BER is influenced by many variables such as human speculation and policies and, thus, is dependent on the financial system. The fluctuation of BER submitted has been extensively investigated. However, the correlation analysis of the short- and long-term effects by indicators of online sentiment is unexplored. The Bitcoin exchange rate BER is extremely volatile. Kurka concluded that BER is independent of any financial asset classes in the system, but its spillover effect affected the traditional financial markets [ 1 ].
16% of Americans say they have ever invested in, traded or used cryptocurrency
Cryptocurrency is a type of digital currency that generally only exists electronically. There is no physical coin or bill unless you use a service that allows you to cash in cryptocurrency for a physical token. You usually exchange cryptocurrency with someone online, with your phone or computer, without using an intermediary like a bank. Bitcoin and Ether are well-known cryptocurrencies, but there are many different cryptocurrency brands, and new ones are continuously being created. People use cryptocurrency for quick payments, to avoid transaction fees that regular banks charge, or because it offers some anonymity. Others hold cryptocurrency as an investment, hoping the value goes up.
What Is Cryptocurrency?
There is growing scepticism in El Salvador as the country prepares to be the first in the world to recognise Bitcoin as legal tender on 7 September. The government has presented the measure as a way to boost economic development and jobs. Polls suggest Salvadorians are not prepared for the move, and the World Bank has warned against its adoption. Analysts say it is an "attention-seeking move" from an "authoritative regime". Next week's landmark day follows a vote by lawmakers in June to legalise the crypto-currency. Under the country's Bitcoin Law, businesses will be obliged to accept it or the US dollar, the country's other official currency, as payment. More than new cash machines are being installed across El Salvador to enable dollars to be converted into Bitcoin.
Article Info.
A cryptocurrency exchange , or a digital currency exchange DCE , is a business that allows customers to trade cryptocurrencies or digital currencies for other assets, such as conventional fiat money or other digital currencies. Exchanges may accept credit card payments, wire transfers or other forms of payment in exchange for digital currencies or cryptocurrencies. A cryptocurrency exchange can be a market maker that typically takes the bid—ask spreads as a transaction commission for is service or, as a matching platform, simply charges fees. Some brokerages which also focus on other assets such as stocks, like Robinhood and eToro , let users purchase but not withdraw cryptocurrencies to cryptocurrency wallets.
What To Know About Cryptocurrency and Scams
Can bitcoin surpass the dollar in popularity and make El Salvador the first state to operate entirely with a private currency? This piece was original published in Money Review and El Economista. In September , the government of El Salvador became the first to make bitcoin legal tender. This means it can now be used to make payments and settle debts, if businesses have the technology to accept it. Importantly, one of the implications of this legal change is that if creditors do not accept settlement of debts in bitcoin, then that debt is cancelled.
Bitcoin Transaction Networks: An Overview of Recent Results
Financial Innovation volume 6 , Article number: 21 Cite this article. Metrics details. The research seeks to contribute to Bitcoin pricing analysis based on the dynamics between variables of attractiveness and the value of the digital currency. Using the error correction model, the relationship between the price of the virtual currency, Bitcoin, and the number of Google searches that used the terms bitcoin , bitcoin crash and crisis between December and February is analyzed. The study also applied the same analysis to prices of Bitcoin denominated in different sovereign currencies traded during the same period. The Johansen J Econ Dyn Control , test demonstrates that the price and number of searches on Google for the first two terms are cointegrated. This research indicates that there are strong short-term and long-term dynamics among attractiveness factors, suggesting that an increase in worldwide interest in Bitcoin is usually preceded by a price increase.
What is bitcoin and how does it work?
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