This study material provides a comprehensive analysis of Bitcoin and its future prospects. It includes trend lines for weekly closing prices, histograms of weekly returns, and descriptive statistics for NAB, Wesfarmers, and Woodside. The material also discusses the potential risks and benefits of investing in Bitcoin.
Contribute Materials
Your contribution can guide someone’s learning journey. Share your
documents today.
Running head:BUSINESS STATISTICS Business Statistics Name of the Student: Name of the University: Author Note:
Secure Best Marks with AI Grader
Need help grading? Try our AI Grader for instant feedback on your assignments.
1BUSINESS STATISTICS Table of Contents Introduction................................................................................................................................3 Trend line for weekly closing price...........................................................................................3 Histogram of weekly return.......................................................................................................4 Three aspects of descriptive analysis.........................................................................................4 Analysis of NAB, Wesfarmers and Woodside...........................................................................5 Conclusion................................................................................................................................10 Reference..................................................................................................................................11
2BUSINESS STATISTICS Executive Summary Bitcoin is a payment network which is very well-known as a cryptocurrency that uses the block chain technology. Some says, Bitcoin as a secure, global and digital currency represents the future of finance and some are not optimistic about it. A statistical analysis is needed to judge that whether it is recommendable or not to invest in Bitcoin. Data on the closing price and the return of Bitcoin on weekly basis can be used to get the best results from the analysis. The trend and the statistics can suggest the better option between investin and not investing on Bitcoins.
3BUSINESS STATISTICS Introduction Blockchain,primarilyblock chain,isa distributeddecentralizeddigitalledger. Cryptocurrencyisanapplicationofblockchaintechnology.Cryptocurrencyusesthe encryptiontechniquestosecureandregulatethefinancialtransaction,generationof additional units and confirm the relocation of assets. A very well-known example of cryptocurrency is Bitcoin. Bitcoin is a new kind of payment network and it uses the technology to control without banks, manage transactions and issue the Bitcoins collectively using the network (Easley, O'Hara and Basu 2019). The reasons for being optimistic about the future of Bitcoin are market stability, Scalability of mainstream use, adoption, favorable regulatory decisions, successful platform launches and strong cryptocurrency. The reason behind not being optimistic about the future of Bitcoin is the supply of Bitcoin is fixed in the long-run. Now, even if it follows the constant Friedman growth rule it would not be possible to solve the problem. Trend line for weekly closing price Figure 1: Weekly closing price of Bitcoin over the year. 8/14/201312/27/20145/10/20169/22/20172/4/20196/18/2020 0 5000 10000 15000 20000 25000 30000 Weekly Closing Price of Bitcoin Time (Week) Closing Price (AU$)
Paraphrase This Document
Need a fresh take? Get an instant paraphrase of this document with our AI Paraphraser
4BUSINESS STATISTICS The above figure is scatter diagram presenting the weekly closing price of the Bitcoin. The scatter diagram is helpful to determine the relationship between two variables. To do so, it presents the dependent variable on the vertical axis and the independent variable on the horizontal axis. Then it presents the data of dependent variable against each value of independent variable. In the figure above the closing price of Bitcoin is presented on the vertical axis and the dots are presenting the closing price of Bitcoin against each week from 2014 to 2019. A trend line is presented which does not match with the scatter diagram of close price of Bitcoins. Therefore, it can be said that the price does not follow the trend line (Güçlü 2018). Histogram of weekly return Figure 2: Weekly return on Bitcoin over the year 3/9/2014 5/18/2014 7/27/2014 10/5/2014 12/14/2014 2/22/2015 5/3/2015 7/12/2015 9/20/2015 11/29/2015 2/7/2016 4/17/2016 6/26/2016 9/4/2016 11/13/2016 1/22/2017 4/2/2017 6/11/2017 8/20/2017 10/29/2017 1/7/2018 3/18/2018 5/27/2018 8/5/2018 10/14/2018 12/23/2018 3/3/2019 -60.00% -40.00% -20.00% 0.00% 20.00% 40.00% 60.00% 80.00% Weekly Return on Bitcoin Time (Week) Weekly Return (AU $) For normal distributions the top point of bars of histogram makes a shape of bell. But the above figure does not appear as a bell shaped and there are too many peaks that implies that the closing price is not normally distributed. The peak and bottom values of the return on Bitcoin are the evidence of the outliers. There are a number of peaks and bottoms that are shown by the longest bars of the histogram. Three aspects of descriptive analysis Return on Bitcoin
5BUSINESS STATISTICS Mean0.016 Standard Error0.008 Median0.012 Standard Deviation0.126 Sample Variance0.016 Kurtosis3.006 Skewness0.606 Range1.054 Minimum-0.398 Maximum0.657 Sum4.124 Count260 Table 1: Descriptive statistics of weekly return on Bitcoin Three points of descriptive analysis (location, shape and spread) of the weekly return on Bitcoin is presented by the above table. The location is presented by the mean value that equals to 0.016% of the variable around which the closing prices are stabilized. The shape is measured by the number of mode values, skewness and kurtosis. The distribution of weekly return on Bitcoin is multimodal distribution. The value of skewness is positive which indicates that the distribution is positively skewed that means most of the values are on the right side of the median. Kurtosis is 3.006 that indicates that the tail of the distribution is normal.The spread of a data set is described by the standard deviation of the data (Chambers 2017). The standard deviation of the weekly closing price is 0.126 that the return on Bitcoin varies between -0.11 and 0.142. The higher the value of SD, the higher the spread is. The probability of loss in inviting on Bitcoins is (114/260) or 43.85%. Analysis of NAB, Wesfarmers and Woodside Figure 3: Weekly closing price of NAB over the year
6BUSINESS STATISTICS The scatter diagram almost follows the trend line from the year 2013 to 2019 but there exist some values above and below the trend line. Figure 4: Weekly return on NAB over the year 3/9/2014 5/18/2014 7/27/2014 10/5/2014 12/14/2014 2/22/2015 5/3/2015 7/12/2015 9/20/2015 11/29/2015 2/7/2016 4/17/2016 6/26/2016 9/4/2016 11/13/2016 1/22/2017 4/2/2017 6/11/2017 8/20/2017 10/29/2017 1/7/2018 3/18/2018 5/27/2018 8/5/2018 10/14/2018 12/23/2018 3/3/2019 -10.00% -5.00% 0.00% 5.00% 10.00% 15.00% Weekly Return on NAB Time (Week) Weekly Return (AU $) The return on NAB is not normally distributed. There are a number of peaks and bottoms that are shown by the longest bars of the histogram that are the evidence of outliers. Return on NAB Mean-0.001 Standard Error0.002 Median0.001 Mode0.000
Secure Best Marks with AI Grader
Need help grading? Try our AI Grader for instant feedback on your assignments.
7BUSINESS STATISTICS Standard Deviation0.028 Sample Variance0.001 Kurtosis0.742 Skewness-0.186 Range0.179 Minimum-0.088 Maximum0.091 Sum-0.152 Count260 Table 2: Descriptive statistics of weekly return on NAB The mean value of the return is -0.001 %. The value of skewness is negative which means most of the values are on the left side of the median. Kurtosis is 0.742 that indicates that the tail of the distribution is very low than a normal tail.The standard deviation of the weekly return on NBA is 0.028 that the closing price varies between -0.029 and 0.027. The lower the value of SD, the lower the spread is. The probability of loss in inviting on NAB is (126/260) or 48.46%. Figure 5: Weekly closing price of Wesfarmers over the year 8/14/201312/27/20145/10/20169/22/20172/4/20196/18/2020 0 5 10 15 20 25 30 35 40 Weekly Closing Price of Wesfarmers WesfarmersLinear (Wesfarmers) Time (Week) Closing Price (AU$) The scatter diagram almost follows the trend line from the year 2013 to 2019. In this case it is clear that the closing price of the Wesfarmers follows a trend line.
8BUSINESS STATISTICS Figure 6: Weekly return on Wesfarmers over the year 3/9/2014 5/18/2014 7/27/2014 10/5/2014 12/14/2014 2/22/2015 5/3/2015 7/12/2015 9/20/2015 11/29/2015 2/7/2016 4/17/2016 6/26/2016 9/4/2016 11/13/2016 1/22/2017 4/2/2017 6/11/2017 8/20/2017 10/29/2017 1/7/2018 3/18/2018 5/27/2018 8/5/2018 10/14/2018 12/23/2018 3/3/2019 -10.00% -8.00% -6.00% -4.00% -2.00% 0.00% 2.00% 4.00% 6.00% 8.00% Weekly Return on Wesfarmers Time (Week) Weekly Return (AU $) The return on Wesfarmers is not normally distributed. There are a number of peaks and bottoms that are shown by the longest bars of the histogram that are the evidence of outliers. Return on Wesfarmers Mean0.001 Standard Error0.002 Median0.002 Standard Deviation0.024 Sample Variance0.001 Kurtosis0.907 Skewness-0.441 Range0.157 Minimum-0.086 Maximum0.070 Sum0.206 Count260 Table 3: Descriptive statistics of weekly return on Wesfarmers The mean value of the return is 0.001 %. The value of skewness is negative which means most of the values are on the left side of the median. Kurtosis is 0.907 that indicates that the tail of the distribution is lower than a normal tail.The standard deviation of the weekly return on NBA is 0.024 that means the closing price varies between -0.023 and 0.025. The probability of loss in inviting on Wesfarmers is (119/260) or 45.77%.
9BUSINESS STATISTICS Figure 7: Weekly closing price of Woodside over the year 8/14/201312/27/20145/10/20169/22/20172/4/20196/18/2020 0 5 10 15 20 25 30 35 40 45 50 Weekly Closing Price of Woodside WoodsideLinear (Woodside) Time (Week) Closing Price (AU$) The scatter diagram does not follow the trend line from the year 2013 to 2019. Figure 8: Weekly return on Woodside over the year 3/9/2014 5/18/2014 7/27/2014 10/5/2014 12/14/2014 2/22/2015 5/3/2015 7/12/2015 9/20/2015 11/29/2015 2/7/2016 4/17/2016 6/26/2016 9/4/2016 11/13/2016 1/22/2017 4/2/2017 6/11/2017 8/20/2017 10/29/2017 1/7/2018 3/18/2018 5/27/2018 8/5/2018 10/14/2018 12/23/2018 3/3/2019 -10.00% -5.00% 0.00% 5.00% 10.00% 15.00% Weekly Return on Woodside Time (Week) Weekly Return (AU $) The return on Woodside is not normally distributed. There is a huge number of peaks and bottoms that are shown by the longest bars of the histogram that are the evidence of outliers. Return on Woodside Mean0.000 Standard Error0.002 Median0.002 Standard Deviation0.031
Paraphrase This Document
Need a fresh take? Get an instant paraphrase of this document with our AI Paraphraser
10BUSINESS STATISTICS Sample Variance0.001 Kurtosis0.629 Skewness-0.058 Range0.187 Minimum-0.083 Maximum0.104 Sum0.060 Count260 Table 1: Descriptive statistics of weekly return on Woodside The mean value of the return is 0.000 %. The value of skewness is negative which means most of the values are on the left side of the median. Kurtosis is 0.629 that indicates that the tail of the distribution is lower than a normal tail.The standard deviation of the weekly return on NBA is 0.031 that means the spread is very low. The probability of loss in inviting on Woodside is (124/260) or 47.69%. Conclusion The above analysis shows that the return on Bitcoin is .016% which is very low and the spread is 0.126 which is also very low. That means the statistics is supporting the investmenttheinvestmenton Bitcoins.However,thedataon returnisnot normally distributed and the closing price is not following the trend line indicates the fluctuation of the closing price. These are not good indicators for investing in Bitcoin (Lim 2015).
11BUSINESS STATISTICS Reference Chambers, J.M., 2017.Graphical Methods for Data Analysis: 0. Chapman and Hall/CRC. Easley, D., O'Hara, M. and Basu, S., 2019. From mining to markets: The evolution of bitcoin transaction fees.Journal of Financial Economics. Güçlü,Y.S.,2018.MultipleŞen-innovativetrendanalysesandpartialMann-Kendall test.Journal of Hydrology,566, pp.685-704. Lim, K.G., 2015.Financial valuation and econometrics.