Discussion on the Prognosis of Cryptocurrency
Quantitative Social Science Using R: Text as Data, Geocoded Data, Network Data, or Data Suitable for Linear Regression
For this assessment, you will develop a research question and investigate it using data containing measures suitable for quantitative text analysis, spatial analysis, social network analysis, or linear regression. You are not required to use all of these methods; please select one (or more) appropriate methods to address your research question given the data you have chosen. You must do some essential things described below, but you are free to explore and analyse the data as you see fit, applying what you have learned in this course.
1. Describe your research question, as well as why you think it’s interesting. What do you hope to learn from the data?
2. Define at least one hypothesis that addresses your research question and can be tested empirically with your data (it should be a directional statement; e.g., younger people are more likely to be happy than older people). You may test additional hypotheses, but this is not required. Explain why you expect to find the hypothesized relationship (i.e., defend your hypothesis).
3. Describe your data. What type of data will you be using? Where did you get it from? How many observations are in the dataset? What are your key variables or measures, and how are they scaled/coded? What do low/high values on the scale mean? How well does this variable capture your outcome of interest? Did you create the variables or were they already contained in the dataset? Did you merge data from multiple sources or use a single dataset?
If using linear regression: your dependent variable (outcome) should be measured on a continuous or pseudo-continuous scale (i.e., 7 or more ordered points). Your independent variables may be measured on any type of scale (e.g., continuous, ordinal, or nominal) provided that you properly code them (e.g., nominal variables should be dummy coded).
Where can I find data?
In addition to databases that may be useful such as the UK Data Archive, Data.Gov.uk, Michigan’s ICPSR, and Harvard’s Dataverse, there are other open repositories like Kaggle, which may be of interest. And, of course, there’s always Google. Below are some specific suggestions regarding where to find data:
Textual Data: Project Gutenberg (books), Manifesto Project (political documents), LexisNexis Academic (TV and radio news transcripts), (screenplays)
Network Data: UCINET, Network Repository, UC Irvine Network Data Repository
Spatial Data: No specific datasets (search for geocoded or spatial data)
You may also use data from any of the lab exercises (provided you do not repeat the exact same analysis); the same rules apply for the textbook.
4. Describe your analytical approach. What analyses did you conduct and why? What are the strengths/weaknesses of this approach? If you used more than one method, then discuss how these methods compare to each other.
5. Substantively interpret your results. Make sure that you thoroughly discuss your findings and compare different outputs/statistics across approaches. For instance, if you analyse network data, you should discuss various statistics that measure centrality. Overall, what do the results tell you?
If using linear regression: estimate your regression model(s) using the ‘lm()’ function in R. Interpret the results from your regression model(s), beginning with the coefficients of your key predictors. What does a 1-unit change in this variable mean for your dependent variable? Are there any other predictors that have statistically significant or interesting results? Was your hypothesis supported by the data? How much variation in your outcome does your model explain? Make sure that you substantively interpret your findings so that a layperson could understand them (i.e., how large are the observed associations?).
6. Visualise your results. Again, discuss how your figure(s) help illustrate your main findings. Make sure that you label your figures with titles, axis labels, etc.
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Prognosis of Cryptocurrency
Introduction
Background to study
Bock chain has been accepted across the globe as a transactional technique. Besides, technology blockchain provides secure validation and decentralized mass interaction to establish a new asset category for international investors, hence its popularity within various markets. The interests not only of investors but also money regulatory and national securities authorities have picked up considerable unregulated money inflows into a transaction and international company. Blockchain technology has recently become a protected, peer-to-peer network for certifying digital activities and enabling transactions in such a quickly decentralized economic system (Ulyanava, 2018). It allows security certification, background check, and any size transactions, including centimeters. Businesses obtain profits from the introduction of accountable and transparent supplier chains and the removal of background checks which verify identifications. Moreover, most crucially for entrepreneurs, numerous challenges to entry are further decreased for persons and businesses with viable but underfunded plans because of the new, less regulated capital-raising methods and finance in recent years. Nevertheless, Blockchain and comparable technologies like virtual currency, security, and regulation are significantly affected, particularly given technology's early childhood and disruptive potential. People highlight in this work, therefore, the regulatory and safety consequences of blockchain technology and initial coin offers (ICOs) in a quickly decentralized market.
Generally, given its relevance to economies and communities, it is essential to understand these financial innovations better. The regulatory and development of their cryptographic currencies can be facilitated by technology progress and money development as a genuinely liquid means of Exchange. Money was initially used to exchange things. It was then referred to as the worldwide gold equivalent. The next step was the migration to paper money, which resulted in the emergence of electronic money in current times (e-money). Money is a social norm developed to promote confidence among strangers, both intertemporal and spot in economic transactions (Tasatanattakoolv and Techapanupreeda, 2018). A monetary exchange agreement allows for precious intertemporal transactions that otherwise would not be conceivable. According to this theory, persons who do not know or trust each other decide to settle their transactions by exchanging symbolic items, such as bank deposits or banknotes for products, work, and services, since they believe they and this trade arrangement are preferable to those that are accessible.
Statement of Problem
Despite widespread support for the new regulations as an improvement to customer trust in the nascent digital money business, some worry that modifiable exchanges will only drive investors overseas to pursue more hospitable jurisdictions. The study examines the potential effects of current counter-terrorism and anti-money laundering financing regulations on cryptocurrencies. Anyone who operates a registrable virtual currency exchange service is subject to the new legislation (Dark, Emery, Ma, and Noone, 2019). This includes any service involving converting fiat currencies, whether dollars or otherwise, to crypto or vice versa. The service must be rendered in the process of conducting a business involving the exchange of digital currencies.
Cryptocurrency or 'digital money is defined as 'digital representation of value as an exchange, storage or account unit.' In addition, digital currency is described as open to the public, convertible with money, considerable, and not government-issued. This definition excludes money in closed gaming environments and any future cryptocurrencies issued by the government. Australia's legislation may potentially be changed for specific digital currencies to be included or excluded in the future. In addition to this, cryptocurrency analysts generally agree that CTF laws will boost consumer confidence and foster the implementation in mainstream transactions of cryptocurrencies. Even crypto-to-crypto exchanges that are exempt from the new rules are likely to be impacted, as tracking a customer's data on a crypto-to-crypto exchange is still conceivable if the initial fiat-to-currency transaction happened on an CTF controlled exchange.
Thus, purchases of 'anonymous' cryptocurrencies such as Monero may be traceable under appropriate regulatory frameworks. The new laws effectively bring DCEs within the scope of existing money laundering and reporting requirements and counter-terrorism financing compliance, which many financial institutions already face, and will involve DCEs to incur costs and develop enhanced technical abilities to guarantee compliance (Lee, 2019). However, the new legislation is consistent with a global trend toward enforcing counter-terrorism financing and anti-money laundering regulations on cryptocurrency exchanges. Given that the ultimate goal of many cryptocurrencies is to attain widespread adoption, Australia's new rules should only serve to enhance further the authenticity of digital currency trading on the broader market.
Aim
The aim of this study is to determine the risks and potential shortcomings in the existing Australian regulatory framework in safeguarding the use of cryptocurrencies.
Research questions
Research questions to be addressed in this study include;
1.What are the main problems facing cryptocurrencies?
2.What are the risks involved in cryptocurrencies?
3.What are the potential shortcomings of cryptocurrencies?
Literature Review
Blockchain
According to Tasatanattakool, and Techapanupreeda (2018) cryptocurrencies can neither be manufactured nor controlled by any government. On the contrast, they are developed well-established digital payment systems that allows parties to deal directly with no an intermediary. In agreement, Hileman, and Rauchs, (2017) add that this technology aims to shift the attention from centralized entities to peer-to-peer exchanges on the market, with regulation dispersion as a fundamental objective. The technology's peer-to-peer structure and open data accessibility and security guarantee the direct Exchange amongst participants through encryption, without governments, banks, and other intermediaries interfering with it (Gainsbury, & Blaszczynski, 2017). Moreover, Ahn and Kim (2020) find disagreeing information, asserting that from some unknown underground currencies, cryptocurrencies is today a world-class asset with digital money future contracts mostly on Chicago Mercantile Exchange Inc with a market capitalization of over $136 billion. This trend has been achieved even in the presence of various limitations such as cybersecurity-related complications.
Miraz, & Ali, (2018), suggested that Blockchain is a public directory disseminated. It is a leader who can record practically any kind of transaction, from crypto-currency transactions to medical data and real-estate chains. It is constructed like a peer-to-peer chain which enables its partners to reach consensus in a mathematical procedure regarding the position of the manager at a given point. Contrastingly, Eyal, (2017) states that since each member works to ensure the correctness and security of the Blockchain, it does not depend on a central authority's operations. The Blockchain promises to resolve duplicate spending — the issue that had impeded the broad deployment of digital currency until that time.
According to Lee (2019), the Blockchains are pseudonymous, and it is not anonymous. The anonymity shall be deleted when the crypto money is purchased transitively with the nations fiat money. The exchanges which enable those transactions are subject to federal legislation and the anti-money laundering standards of people client (KYC) at a national level. However, Moyano, and Ross, (2017), agrees that some operators who maintain cryptocurrency or transfer the proceeds of their trades via cash or private transactions are still unregulated. The initial coin offers could be considered an another way for participants to trade fiat money or current tokens for entity-specific. The digital currencies have emerged as the primary tool for collecting funding used by block chain companies. Research shows that the global dissemination of cryptocurrencies relies on government financial regulatory authorities, the media platforms, and educational organizations as they impact the institutional acceptability of cryptocurrencies. In addition to that, Cassidy, & Huang, (2019), demonstrate that prohibitions of cryptocurrencies in Korea and China have ramifications for international hone governance that influence the spread of cryptocurrencies in other nations. Shin, (2018, June) argues that spillover of spreading and regulatory impacts from one country to another illustrates that a coordinated and harmonized regulatory approach is appropriate. These marketplaces are globally integrated, and the impact of regulating not just national borders.
Initial public offers (IPOs), through which corporations have sold their shares to the public, are sometimes contrasted to crypto money. Mittal, and Verma, (2016) both agreed that IPOs and virtual currencies are used to generate stock for emerging firms; they both manufacture significant quantities of cash and are capable of rapidly making company founders rich (Pham, et al & Bao, 2019). Here lies the resemblance. IPOs are extensively regulated on the opposite side. The Securities and 1934 Exchange act as well as the 1933 Securities Act in the United States as stated by Form, (2018), are subject to the responsibilities of undertakings to record, maintain compliance, and disclose them. These guidelines provide real, adequate, and correct data for fundraising companies. Due to its comprehensive and rigorous regulations, the IPO is responsible for a monthly procedure, including selection of legal counsel and an investment bank (Bradford, 2018). The acts require any security provided to the US public by either certified with SEC or comply with one of the very complicated exemptions listed.
Lorenzo Álvarez, and Arroyo Gallardo, (2021) confirms the results of the old used realm of building capital, businesses with exciting concepts about new goods or services must first construct a beta or prototype to show investors the idea's legitimacy. Following the demonstrated product functionality and typically following a given degree of adaption, a company may seek risk financing to build or scale the concept (Moratis, Melissen, & Idowu, 2018). In return for early seed round money, entrepreneurs are then obliged to abandon considerable stake in their own companies. This restricts entrepreneurs with concepts that don't have a great network of affluent certified investors. Also, Lorenzo, (2021) in the research agreed that it restricts who make investments as the earliest round of financing is limited to wealthy main and accredited investors. The crypto represent a significant shift or change in the manner concepts are generated and marketed. They allow creators with solid ideas about new applications to increase or raise funding from those investors who will eventually use the built-in products and services.
Ulyanava, (2018) suggests that the tokens created in a virtual currency do not provide buyers any equity or equity interest and urge in the issuing company. Also, most cryptocurrencies instead issue an implementation token or crypto-asset with some usefulness being generated within the software. Subramanian, (2017) and Al-Naji, & Diao, (2017) confirmed that these tokens could power decentralized blockchain applications or buy products and services from the decentralized protocol software issuing company. Although primarily intended for payment in the issuing entity's blockchain and main ecosystem, and app tokens can also function as an independent value store sold in online stated digital money exchanges. Burilov, (2019) argues that cryptocurrencies are much less like stated IPOs and much more closely related to pre-ordering, with investors buying assets that had value in the issuing body system if the system was established.
Methodology
Technically, different websites collect information about the price of bitcoins. There are specific attributes that must be collected to forecast the intended result. The information gathered here includes the % change in the total quantity of bitcoins over an hour, a day, and a week. These inputs are applied to various algorithms to predict the intended outcome. The whole supply of bitcoins may be found here. This information is used to create the model that forecasts the outcome. The dataset should be preprocessed before any algorithm for model design is applied. Our next step is to pr...