Analysis of Bitcoin and Comparison to Australian Companies

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The use of bitcoin has become popular as a means of online transactions. The person credited to start the cryptocurrency is a Japanese named Satoshi Nakamoto, and since then, the popularity has grown until multinational companies are beginning to think about incorporating the use of bitcoins in their transactions. In this paper, the bitcoin will be compared to three Australian companies namely the BHP Billiton (BHP) from the mining sector, Commonwealth Bank of Australia (CBA) from the bank sector, and Telstra Corporation (TLS) from the telecom sector. The source of data to be used in the analysis will be Yahoo Finance. The paper will start with an introduction of cryptocurrency, explaining the reason why it became popular and secure as a mode of online transaction. Line charts are used to show the trends of the bitcoins and TLS, CBA and BHP, which shows that the weekly return rates of bitcoins are increasing, the trend of BHP started decreasing and then increased and for the CBA, the trends is going down. Histograms of the weekly return rates shows that they all follow the normal distribution, the bell-shaped curve. The 95% confidence interval of bitcoins and CBA, BHP and TLS are also calculated on the paper. Lastly, a one-way ANOVA will be used to compare any difference between the three shares, CBA, BHP and TLS.


VIGNA & MICHAEL (2016) defines Cryptocurrency as a medium of exchanging digital money so as to secure financial transactions. Unlike the common cash, they are decentralized, that is, there is no single entity that controls their operation, such as the central banking systems. Therefore, the system which controls the transfer of cryptocurrency is known as the blockchain.

Originally developed by Satoshi Nakamoto, cryptocurrency was meant to be a peer-to-peer cash transfer system. The transfer of bitcoin is made possible by blockchains, a technology which allows the transfer of bitcoins from one person to an intended other, through a digital ledger. The digital ledger can be thought of as a spreadsheet which is constantly updated. Since it is not centralized, it can neither be hacked or corrupted, and several millions of computers can access it simultaneously. Bitcoins do not have a middle person because even user has a wallet where they use to buy stuff over the internet using the bitcoins. Every transaction is needs to be pass through the process of identity verifications, using generated keys. Two keys are produced when a bitcoin transaction is about to take place, the private and the public key. To confirm that the bitcoins were meant for them, the receiver has to match the private key of the transaction.

Currently, the use of bitcoins in transaction has become popular and several large corporations have been using the digital currency. In the second annual Global Blockchain Summit, BHP Billiton announced that it will use blockchain to record the movement of wellbore rocks and fluid samples so as to track real-time data in its business operations ( 2018).  BHP’s geophysicist, R Tyler Smith, further emphasized that the use of bitcoin will enable them to reap the benefits of allowing internal efficiency and allowing the working with partners to be more effective.  Furthermore, the Commonwealth Bank was recently chosen by the world Bank to be the first in the world to deliver blockchain Bond. The bank will be tasked to create, allocate, transfer and manage the blockchain technology. Telstra Corporation also announced it is working on accepting payments in form of bitcoins, if it demands of it will increase (Jeff Whalley, 2015).

In this paper, an analysis of bitcoin uses by the three companies. The data comes from the Yahoo Finance website, and it constitutes the weekly closing prices of the company. The unit of measure of the bitcoins are in Australian Dollars (AU$).


(a). Bitcoins

Graphical view of bitcoins

A line graph or line chart is an appropriate visual illustration of how data changes of time (time series). The x-axis of the line graph represents the time with equal interval, whereas the y-axis represents the values at each time. The line graph shown below shows the weekly closing prices of the Bitcoins.

Based on the line graph above, it is easier to see that the prices started to be low on May 2014 and remained to be constant until the beginning of 2016 where they started to gradually increase. By 2017, the weekly closing prices of bitcoins shot up significantly, from around zero to as high as 25,000. This shows that on 2017, they became more popular at increasing rates. The descriptive statistics of the weekly closing prices of the bitcoins shows that the minimum values recorded was 289.48 (26/01/2015) whereas the maximum value was 25986.55 (11/12/2017), giving a range of 25697.07. With the low values in 2015 and extreme values in 2017, it is evident that the weekly closing prices of the bitcoins has an increasing trend.

Histogram of weekly returns

A histogram shows the distribution of numerical data, where the area of the rectangular bars is proportional to the frequency of a variable and the width are equal to the class intervals. The histogram below shows the calculated weekly returns of the bitcoins. A normal distribution, also known as a bell-shaped curve, is characterized by the average being at the center, with the mean, mode and median aligning with the mean. Furthermore, it is unimodal, and symmetrical.

In our case, the histogram of the weekly returns shows that the distribution is normally distributed, with majority of the data being (mean) at the center and has only one mode. Furthermore, it is symmetrical.

Descriptive analysis of bitcoins

The location of the histogram shows that it is at the middle of the extremes, closer to zero weekly returns. This shows that the weekly returns of bitcoins are stable. The spread of the bitcoin is the expected amount of variation which is associated with the output. It is the range of the values which we are seeing. The spread is expressed as the standard deviation and in our case, the standard deviation is 12.986. The spread suggest that the weekly returns varies a lot. The shape shows the symmetry of the distribution. The histogram shows that the shape is symmetrical since it is neither skewed to the left of right.

The empirical probability is the probability that an event will occur given all possible events. The empirical probability of a loss are the negative weekly returns is 18%. This means that the out of all the weekly returns, loss was accumulated only 18 percent.

(b). BHP Billiton

The BHP Billiton is an Australian based company in the multinational mining, metals and petroleum industry. Its headquarters are in Melbourne, Victoria, Australia. Data for the BHP were available from Yahoo Finance and they will be used in the calculations below.

The line graph of the BHP Billiton is shown below.

According to the line chart above, it is easier to see that the prices of BHP started to generally decrease between 2014 and 2015. However, it started rising again gradually, but by the 15th of June 2018, it has not yet reached the peak on the same time in 2014. The trend therefore decreases from 2014 to 2015, then starts to rise from 2015 to 2018.

Histogram of BHP

The histogram of BHP shows that the distribution of weekly returns is approximately normally distributed. However, there is an extreme value at the far right of the histogram signifying that it is possible that there is an outlier in the dataset.

Descriptive analysis of BHP

The location of the histogram shows that the dataset is centrally located, with the peak around the zero mark. As for the shape, the histogram is bell-shaped, following the distribution of a normal distribution. The spread of the dataset shows that the histogram is more spread to the right than to the left. The spread also shows that the tail is heavier on the left than on the right.

Empirical Probability loss

The empirical probability loss of the BHP is more pronounced than the Bitcoin loss, which is 21.5%. This shows that BHP makes greater loss than the bitcoins.

(c). Commonwealth Bank of Australia (CBA)

The Commonwealth Bank of Australia (CBA) is an Australian multinational bank in the banking industry. Its operations are across New Zealand, Asia, the United States and the United Kingdom. The data of CBA used in the analysis is from Yahoo Finance.

The line chart displayed above shows that with the weekly values of CBA were fluctuating between the 80-mark. It slightly increased at the beginning of 2015 but then in the same year, return fluctuating in the 80-mark. The same trend continued through 2017, but as of 2018, it started decreasing again. The trend displayed in the line chart shows that it is constant over time, with minor fluctuations throughout the year.

Histogram of CBA

The histogram of weekly returns of CBA shows that the distribution resembles a normal distribution. This is because, the mean, mode and median of the data are all at the center, and furthermore, it is symmetrical. Less common data are at the tails of the distribution.


Descriptive Analysis

The location of the data shows that the data is centrally located, at approximately 0 mark on the x-axis. As for the shape, the distribution follows a normal distribution, which is bell-shaped, with majority of the data at the center. The spread of the data also symmetrical, but on the left, there are slightly more data than on the right. There seem to be no outliers in the dataset of weekly returns.

Empirical probability of a loss

The empirical probability of a loss of the CBA weekly returns is 0.26. This means that CBA makes a loss 26% of the time. Out of the three, the CBA is makes the loss the most.

(d). Telstra Corporation (TLS)

The Telstra Corporation (TLS) Limited is a telecommunication company in Australia. It mainly deals with markets voice, mobile, internet access, pay television and other telecommunication services. The source of TLS data was the Yahoo Finance.

Line Chart of TLS

The line chart displayed above shows that it started at around 5 and rose between 2014 to early 2015. From here, the line chart showed a decrease in its weekly data until 2018, where it was lower than its original price. Therefore, the general trend of TLS weekly data is that it is decreasing with time.

The histogram of the weekly returns of TLS shows that the data is normally distributed. However, on the extreme left of the histograms are isolated small bars, which are the outliers of the weekly returns of TLS.

Descriptive Analysis

The location of the histogram is that it is around the zero mark. The shape of the histogram resembles a normal distribution and since it is bell shaped. As for the spread, the outliers present in the left side of the histogram shows that the spread is more on the left than on the right, making the histogram to be slightly skewed.

Confidence interval

The confidence interval can be described as a type of interval estimation is used to estimate an observed data might contain the true values of an unknown population parameter. Specifically, the 95% confidence interval means that there is a 95% certainty that the true parameter of the population is within the intervals.

The formula for calculating the confidence interval is given as follows

Where,  is the sample mean

            t is the associated standard t-score

            n is the number of items.

However, there is an easier way of calculating it using the data analysis package in Microsoft Excel.

95% confidence interval of Bitcoin

The summary statistics of Bitcoin dataset is displayed below

Descriptive statistics of Bitcoin weekly returns



Standard Error






Standard Deviation


Sample Variance
















To calculate the 95% confidence interval,

The mean is 2.052245, the t value is 1.96. Therefore,

 = 2.052245 ± 1.76054= [0.2917, 3.8128]

Therefore, the 95% confidence interval of the population mean falls between 0.2917 and 3.8128

The 90% confidence interval is

 = 2.0552 ± 1.477 = [0.57475, 3.5297]

Therefore, the 90% confidence interval of the population mean of bitcoins falls between 0.57475 and 3.5297.

When we compare the 95% and the 90% confidence interval, it is easier to see that the 95% confidence interval is narrower than the 90% confidence interval. This is because, at 95% confidence interval, the certainty is higher, reducing the probability of making a type I error than the 90% confidence interval.

95% confidence interval of BHP, CBA, and TLS


The descriptive statistics of BHP based on excel calculation is displayed below.




Standard Error






Standard Deviation


Sample Variance
















With the mean 25.76 and t value of 1.96(95%), the confidence interval is as follows


Therefore, the 95% confidence interval will be 25.7639 ± 0.683 = [25.080, 26.447]

The BHP confidence interval shows that the population mean falls between 25.080 and 26.447

95% confidence interval for CBA

The descriptive statistics of CBA based on excel calculations is given below




Standard Error






Standard Deviation


Sample Variance
















With the mean being -0.03823, standard deviation is 2.54 and t is 1.96, The 95% confidence interval is given below

 = -0.03823 ± 0.3435

Therefore, the confidence interval of the mean is [-0.3818, 0.3053]. therefore, the 95% confidence of the mean falls between -0.3818 and 0.3053

95% confidence interval of TLS

The descriptive statistics of TLS is displayed below




Standard Error






Standard Deviation


Sample Variance
















In calculating the 95% confidence interval we will need the sample mean which is -0.26361, the standard deviation which is 2.618976 and the 95% t value is 1.96.

 = -0.26361 ± 0.354 = [-0.6178275, 0.0906075]

Therefore, the 95% confidence interval falls between -0.6178275 and 0.0906075.

Hypothesis testing

The hypothesis we would like to test will be as follows

H0: weekly return rate of bitcoin = 4%

HA: weekly return rate of bitcoin ≠ 4%

For the other three shares

H0: BHP = CBA = TLS = 0

HA: at least one pair is not equal to zero.

For the bitcoin hypothesis, a two tailed hypothesis will be tested.

The sample mean of the Bitcoin return to investment is 2.052245. From this information, the test statistic id -2.16839 and the degrees of freedom is 209 (210 – 1). The calculated two tailed t-value is 0.9687. Since the calculated two tailed t-value is greater than the significance level of 0.05, we fail to reject the null hypothesis and conclude that the weekly return of bitcoin is indeed 4%, and that the investor is right.

As for the other shares of investment, the null and alternative hypothesis is as follows.

H0: BHP = CBA = TLS = 0

HA: at least one pair is not equal to zero.

Because we are comparing more than 2 groups, the appropriate statistical test which will be used will be a One-Way Anova. When we run the data of the three shares of investment, the following is the output.

Data Summary




Std. Deviation

Std. Error
















The ANOVA summary table is displayed below

ANOVA Summary







Between Groups






Within Groups







At 0.05 level of significance, the F (2,624) = 0.576 and the associated p-value is 0.5625. Because the p-value is greater than the level of significance, we fail to reject the null hypothesis and conclude that there is no difference between the three shares, CBA, BHP and TLS.


Top of Form

VIGNA, P. &. C., MICHAEL. (2016). Cryptocurrency. Random House UK. (2018, August 23) CBA picked by World Bank to deliver world's first standalone blockchain bond. Retrieved from of Form

Rizzo, P. (2016, September 24). World's Largest Mining Company to Use Blockchain for Supply Chain. Retrieved from

Jeff Whalley (April 8, 2015) Bitcoin may get Telstra’s call as telco considers digital payments. Herald Sun. Retrieved from

August 18, 2023



Personal Finance

Subject area:

Bitcoin Money

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