Efficiency of Cryptocurrency in Current Market Place - Public Survey

Efficiency of cryptocurrency in current market place
(Public Survey)
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Department Name
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FirstName Surname
Department Name
Institution/University Name
City State Country
[e-mail]
ABSTRACT
In the present era of digitalization, the crypto-currencies are achieving enormous popularity
and credibility. Their overall process and market capitals of resources are gaining different
heights every time. Various financial institutions are coming on their way to developing those
technologies of digital currency. The dynamics of the market is useful to understand how the
situation is viable. In this report, an experiment is conducted on various students of marketing
at Australia. The survey conducted here focusses on understanding how valuable is
cryptocurrency for share market traders. Firstly, the background of the overall situation is
analysed. Then, a study is conducted and results are interpreted from the survey.
KEYWORDS
Cryptocurrency, share market, efficiency of crypto-currency, Bitcoins, Altcoin
1. INTRODUCTION
The cryptocurrencies are found to be gaining credibility and popularity. The marketplaces of
the dynamics of the markets are helpful to
cryptocurrency ecosystems are viable and how the choices of design have been
market. It is seen that one of the potential threats for cryptocurrencies is the
traders to sell or buy [2].
Here, an effective experimental methodology is used for conducting a public based survey.
efficiency of the innovation in the present market. This is helpful to understand how
current markets are peer influencing from different trading behaviors of
background of the study is analyzed. Then the overall process of the
retrieved from the study are discussed here.
2. BACKGROUND
The crypto coins or cryptocurrencies are found to be gaining popularity in the present
Here, the market cap and process of the resources are touching many highs with values
every day. They are presently being traded in crypto coins. Butenko et al. (2017)
that financial institutions are investing in developing the technologies of digital
based on block-chains are thriving. As any alternation, the market
increase in punctuated through a crisis. Simultaneously as the
rise is punctuated through crises. Hence, knowing the dynamics of the
to avoid and anticipate the further events of disruptions as per
[3]. Here, an essential threat to the innovation is derived from the speculative nature
are found to be trading because they expect cryptocurrency to
collective excitement has been leading to bubbles and thus resulting in market
design of the online exchanges where cryptocurrencies are traded has been
This might happen as the impacts of the present functionality, GUI or
Application program Interfaces are found to be promoting collective
Kraft (2018) highlighted that these markets include human artifacts and not a natural
considered as a target of designing. Therefore the current analysis strives to
helps in studying how they have been contributing to the collective
As per Peters, Gareth and Guy Vishnia (2016), this design of
been affecting the processes [4].
Study
Here a cross-sectional empirical data survey is used. These are collected from various
time. Here, the time is not seen as the study variable in the research design.
been providing data in the exact time. However, in one session, the
the questionnaire for some period [9]. Hence, cross-sectional data has
This has been making the sample under a relatively shorter
time is considered to the random impact, producing only variance
In this study, different types of cryptocurrencies are surveyed. A useful regression model is
found out. This denotes the main drivers of the crypto currency’s value. This is helpful to understand the
overall competition level. It has been occurring at the network of different producers, a rate of production
per unit and the complexity of an algorithm is used to mine the crypto-currencies [9].
At the core of the goals, lie the understanding why individuals have been deciding to invest
at a specific technology, idea and product and a particular time. As the resource of new and the
information about it are released, the investment has been a rational reaction to the current stage of
information. Additionally, the other factors involve authorities that have been endorsing the stake [8].
Further, big players have been developing noticeably huge bets on that. Next, another source of
hypothesized collective optimism is the peer influence taking place among various share-market traders.
Hence, knowing the endogenous peer effects of influence has become essential. Since the dynamics of
financial markets get profoundly affected by the help of small traders, various solutions are required to
stabilize the markets [10]. Hence, the peer influence has been playing a massive role in the ecosystem of
cryptocurrencies because of huge speculative kind of resources. As the universal intrinsic value of the
crypto-coins has been rising with the rise of levels of adoption, much of the trading become speculative.
Similar to the properties if various latest technologies, there is a huge deal of uncertainty with
cryptocurrencies. This has been eventually turning to be successful [12].
In this study, various students who are studying marketing at Australia are considered. Their
age is supposed to be below 25 years. Here regression results are utilized as the facilitator. The entire
series of related equations are formalized. It is done to calculate the units of cryptocurrency as a vital
producer [13]. Furthermore, the extrapolating model regarding accounting the average and regulating
values to aggregate the mining network for bitcoins. This indicates the model of production cost. It has
been approximating the market price closely for bitcoins against dollar values [11].
However, there have been some challenges regarding the determination of impacts of small
share market trades in the present financial scenario. Here, most of the responses of she students has
been retrieved from the analysing of observational data. However, this observational assessment is
subjected to various interpretations of confounding [14]. They are seen as evidence against various
traders who are engaged in entirely rational behaviour. This has been predicted by the working market
hypothesis. However, the correlations have been taking place because of overreaction and reaction to
different news events and due to the peer influences. The survey questions comprise of dichotomous
queries. Next, Likert-type scale is utilized here. At last some common questions are developed. These are
meant to be replied by the respondents in complete questions [9].

EFFICIENCY OF CRYPTOCURRENCY CURRENT MARKET PLACE
3. RESULTS
The analysis and results of the surveys are illustrated in the following table. The overall
less than 25 years of age. Here, the contents of equations and selection of
of the appendix section.
Table 1:
Participants' feedback on the dichotomous queries
Participant Gender Question 1 Question 3 Question 5 Question 6
1 F No Yes Yes Yes
2 M Yes Yes Yes No
3 M Yes Yes No Yes
4 F No No Yes Yes
5 F Yes Yes Yes Yes
6 M No No No No
7 F Yes No Yes Yes
8 F No Yes No Yes
9 M Yes Yes Yes No
10 M No Yes No Yes
Table 1: “Responses to question 1,3,5 and 6”
(Source: Created by Author)
Table 2:
Response to question number 2
Participant 1 better than real currency
Participant 2 better than real currency
Participant 3 similar to real currency
Participant 4 worse than real currency
Participant 5 better than real currency
Participant 6 similar to real currency
Participant 7 better than real currency
Participant 8 worse than real currency
Participant 9 worse than real currency
Participant 10 better than real currency
Table 2: “Responses to question 2”
(Source: Created by Author)
Table 3:
Response to question number 4
Participant 1 similar to real currency
Participant 2 better than real currency
Participant 3 similar to real currency
Participant 4 worse than real currency
Participant 5 better than real currency
Participant 6 similar to real currency
Participant 7 better than real currency
Participant 8 similar to real currency
Participant 9 worse than real currency
Participant
10 better than real currency
Table 3: “Responses to question 4”
(Source: Created by Author)
Table 4:
Participants' feedback on the Likert-type scale
Participant Gender Question 7 Question 8
1 F Strongly agree Strongly agree
2 M Agree Neutral
3 M Strongly agree Strongly agree
4 F Agree Strongly agree
5 F Strongly agree Strongly agree
6 M Agree Agree
7 F Agree Strongly agree
8 F Strongly agree Strongly agree
9 M Strongly agree Agree

EFFICIENCY OF CRYPTOCURRENCY CURRENT MARKET PLACE
10 M Strongly agree Strongly agree
Table 4: “Responses to question 7 and 8”
(Source: Created by Author)
Table 5:
Participants' feedback on Question 9 the Likert-type scale
Participant Gender Question 10
1 F Definitely not
2 M Definitely not
3 M Probably
4 F Definitely not
5 F Probably not
6 M Probably not
7 F Definitely not
8 F Definitely not
9 M Most probably
10 M Definitely not
Table 5: “Responses to question 9”
(Source: Created by Author)
Table 6:
Response from question 10
Participant 1 Bitcoin
Participant 2 Bitcoin
Participant 3 Ethereum
Participant 4 Bitcoin
Participant 5 Bitcoin
Participant 6 Ethereum
Participant 7 Bitcoin
Participant 8 Ethereum
Participant 9 Marker
Participant 10 Bitcoin
Table 6: “Responses to question 10”
(Source: Created by Author)
Table 7:
Responses from question 11
Participant 1 Bitcoin
Participant 2 Not sure
Participant 3 Bitcoin
Participant 4 Not enough knowledge
Participant 5 Litecoin
Participant 6 First Bitcoin and then Stellar XLM
Participant 7 Ethereum
Participant 8 Bitcoin
Participant 9 Not sure
Participant 10 Bitcoin
Table 7: “Responses to question 11”
(Source: Created by Author)
Table 8:
Results of Table 1 Number of "Yes" Number of "No"
Question 1 5 10
Question 3 8 2
Question 5 7 3
Question 6 7 3
Percentage 55.00% 45.00%
Table 8: “Analysis of question 1,3,5 and 6”