Microsoft Word - SIT718_Assessment-Task_2-T1_2019.docx ã Deakin University 1 ASSESSMENT DETAILS SIT718 Real World Analytics Assessment Task 2: Problem Solving Key information Due: Weighting: Friday 9...

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Microsoft Word - SIT718_Assessment-Task_2-T1_2019.docx ã Deakin University 1 ASSESSMENT DETAILS SIT718 Real World Analytics Assessment Task 2: Problem Solving Key information Due: Weighting: Friday 9 August 2019 11.30 pm AEST 25% Reference style: Harvard Learning Outcomes This assessment assesses the following Unit Learning Outcomes (ULO) and related Graduate Learning Outcomes (GLO): Unit Learning Outcome (ULO) Graduate Learning Outcome (GLO) ULO1 – assessed through student ability to apply knowledge of multivariate functions, data transformations and data distributions to summarise data sets. ULO2 – assessed through the student ability to analyse datasets by interpreting summary statistics, model and function parameters. ULO4 - assessed through student ability to develop software codes to solve computational problems for real world analytics. ULO5 – assessed through student ability to demonstrate professional ethics and responsibility for working with real world data. GLO1 - Discipline knowledge and capabilities GLO4 – Critical thinking GLO5 – Problem solving GLO8 – Global citizenship Purpose The aim of this assignment is to analyse the behaviour and performance of one company using historical data. You can use statistical data analysis and features you have been learning in R. Instructions The work is individual. Solutions and answers to the assignment must be explained carefully in a concise manner and presented carefully. Use of books, articles and/or online resources on share price related to SIT718 Real World Analytics is allowed. Students are expected to refer to the suitable literature where appropriate. The assessment consists of several tasks. Students must attempt all tasks and provide an individual written report in an appropriate word processor. The detailed problem set will be released to students on Friday 19th July. ã Deakin University 2 ASSESSMENT DETAILS Submission details • No more than 7 A4 sides, including Figures, Tables, Appendices and References. The report should be typed. Use minimal font 11pt and 2.5cm side margins. If the page limit is exceeded only the first 7 pages will be marked. • Assignment (a report in pdf format, software code and/or data) must be submitted via the assignment folder in the unit site (accessed via the unit Program page. • No e-mail or hardcopy submissions are accepted. Extension requests Requests for extensions should be made to Unit/Campus Chairs well in advance of the assessment due date. If you wish to seek an extension for an assignment, you will need to apply by email directly to Dr Ye Zhu ([email protected]), as soon as you become aware that you will have difficulty in meeting the scheduled deadline, but at least 3 days before the due date. When you make your request, you must include appropriate documentation (medical certificate, death notice) and a copy of your draft assignment. Conditions under which an extension will normally be approved include: Medical To cover medical conditions of a serious nature, e.g. hospitalisation, serious injury or chronic illness. Note: Temporary minor ailments such as headaches, colds and minor gastric upsets are not serious medical conditions and are unlikely to be accepted. However, serious cases of these may be considered. Compassionate e.g. death of close family member, significant family and relationship problems. Hardship/Trauma e.g. sudden loss or gain of employment, severe disruption to domestic arrangements, victim of crime. Note: Misreading the timetable, exam anxiety or returning home will not be accepted as grounds for consideration. Special consideration You may be eligible for special consideration if circumstances beyond your control prevent you from undertaking or completing an assessment task at the scheduled time. See the following link for advice on the application process: http://www.deakin.edu.au/students/studying/assessment-and-results/special-consideration Assessment feedback Students will receive written feedback to aid reflection and analysis of problem strategies and solutions for consideration in the upcoming problem. Referencing You must correctly use the Harvard method in this assessment. See the Deakin referencing guide. Academic integrity, plagiarism and collusion Plagiarism and collusion constitute extremely serious breaches of academic integrity. They are forms of cheating, and severe penalties are associated with them, including cancellation of marks for a specific assignment, for a specific unit or even exclusion from the course. If you are ever in doubt about how to properly use and cite a source of information refer to the referencing site above. mailto:[email protected] http://www.deakin.edu.au/students/studying/assessment-and-results/special-consideration https://www.futurelearn.com/your-programs/real-world-analytics/3/resources#header https://www.deakin.edu.au/students/studying/study-support/referencing/harvard ã Deakin University 3 ASSESSMENT DETAILS Plagiarism occurs when a student passes off as the student’s own work, or copies without acknowledgment as to its authorship, the work of any other person or resubmits their own work from a previous assessment task. Collusion occurs when a student obtains the agreement of another person for a fraudulent purpose, with the intent of obtaining an advantage in submitting an assignment or other work. Work submitted may be reproduced and/or communicated by the university for the purpose of assuring academic integrity of submissions: https://www.deakin.edu.au/students/study- support/referencing/academic-integrity https://www.deakin.edu.au/students/study-support/referencing/academic-integrity https://www.deakin.edu.au/students/study-support/referencing/academic-integrity https://www.deakin.edu.au/students/study-support/referencing/academic-integrity ã Deakin University 4 ASSESSMENT DETAILS Assessment Task 2: Problem Solving The aim of this assignment is to analyse the behaviour and performance of financial share prices of one company from the listed five Telecom & Utilities companies below: • Australia and New Zealand Banking Group (ASX: ANZ) • Downer EDI Limited (ASX: DOW) • SEEK Limited (ASX: SEK) • BHP Billiton Limited (ASX: BHP) • Rio Tinto Limited (ASX: RIO) You can use Yahoo Finance to download the historical data of the company you have chosen at https://au.finance.yahoo.com By completing this assignment, you are required to write a case study report of no more than 7 pages, which should include the following information: 1. Your company’s name and the “principal activities” of this company. Choose one company from the list. [5 marks] 2. Collect share price data (daily closing price) for 3 consecutive months from 1 March 2019 to 31 May 2019 inclusive for the company of your choice. Visualise company’s share price data (daily closing price) for this period. Describe the general trend of the share price for this period. Produce your own graph. [5 marks] 3. Research the information about modelling of share prices, particularly the stochastic modelling (based on Geometric Brownian motion), to describe the behaviour of the company’s share price. A simplified version of the model is given below: ?" = ?$exp ()? − ,- . / ?1, where, ?$ is the initial value ?" is the share price on day t (this would be the tth trading day in your analysis) ? is the drift ? is the volatility. Assume that drift and volatility in this model are constants. You are encouraged to research further the literature about ? and ? . Find and describe the meaning of the drift and volatility. Find appropriate formulas to compute their values – daily and annualised - from the historic data. [10 marks] https://au.finance.yahoo.com ã Deakin University 5 ASSESSMENT DETAILS Assessment Task 2: Problem Solving 4. State the condition that share prices have to satisfy in order to be represented by a Geometric Brownian motion. Do your data satisfy this condition? Produce appropriate evidence to support your answer. Hint: the logarithm of the daily share prices change, i.e., log(?"/?"9:), is a normal distribution. [20 marks] 5. Calculate the parameter values ? and ? (daily and annualised values) for the selected periods of three months (March-May) and for the last third month (May). What is the effect of time on ? and ?? Are the parameters constants (with time)? How this could affect the model performance? [20 marks] 6. Estimate the expected values of the share price on 4 days between 28 May and 31 May 2019 using the formula given above. Use the parameters ? and ? values, computed from the three months of historical data. Compare with the published real data. Comment on the results. [20 marks] 7. Find information publicly available for your company, e.g. reports and news releases, and discuss their effect on the values of ? and ?, and the values of the share price. Comment on the model’s performance and state the restrictions of the model. Link your results to the performance of the company and summarise your findings with around 300 words. [20 marks] All supporting information should be presented in the pdf report. It will be assessed for style and grammar, professional presentation of figures, tables and references. You should not exceed the 7 A4 sides page limit (including figures, tables, appendices (if needed) and references). List and quote in the text the references used, including books, articles and web resources. Use the Harvard style. SIT718_Assessment-Task_2-T1_2019.pdf SIT718_Assign1-v7.pdf
Answered Same DayAug 04, 2021SIT718

Answer To: Microsoft Word - SIT718_Assessment-Task_2-T1_2019.docx ã Deakin University 1 ASSESSMENT DETAILS...

Sudhanshu answered on Aug 08 2021
152 Votes
Stock price analysis
Introduction:
Here we are going to deal with the SEEK Limited data from March 2019 to May 2019. The
stock price of company has various issues to deal with. The stock price data file contains the
open, high, low, close and the volume of the trade. Open refers the price at which the price of
the stock
when the market opened in the morning. While the close refers to the price of stock
when the market closed in that day. High is the maximum price of the stock attained on that
day by the stock and low is the minima attained by the stock price attained by the stock at
that day. Moreover Volume refers to total volume of trade carried by in that day. So here we
are going to analyse the data of stock price movement over the given period of time.
SEEk is one the major companies started in Australia in year 1997, it was set up in
Melbourne .The company began with a slow start and soon reached the global market. The
company focuses making life easier for the job seekers and hirers. This behaves as the linking
agent between the students and the companies. This company keeps the portfolio of many
connected students and companies. Currently it has exceeded its market in 17 countries
including China, South East Asia, Brazil, Mexico, Africa and Bangladesh, Australia and New
Zealand. The company uses technology to help find the connections and even the world of
data analytics is helpful in finding the right connections. The company was founded in
November1997 by Andrew Bassat, Matt Rockman and Paul Bassat the web site of the
company was launched in March 1998.The company soon grown into a massive giant in the
world of market and started it advent in market .Today it is not only a company but a group
of companies offering various jobs to the candidates. The another fact which goes in the
favour of this company is that it now a multinational company it has put its work in china as
well and on the other hand the countries like Brazil is also experiencing it service which is
quite unexpected yet the company knows its work very well. The main reason for the upsurge
of the company is that it is using the technology in very broad sense for the development of
the business and for providing good services to the candidates and the companies associated
with them .As in they are using the concept of data science for finding the perfect match for
the companies so they can recommend the particular candidate to the particular company
whose chances of getting accepted in that company is high thus the effort by company is
saved not only the time but also the money is saved which is ultimately reflected in the stock
prices of the company.
Now we use the R programming language in order to carry forward the data analysis of the
data of the stock prices of the company. We use the following code …
df11=read.csv(file="SEK.AX.csv",header=T)
df11
summary(df11)
#df11["Open","Close","High","]
date=df11["Date"]
open=df11["Open"]
high=df11["High"]
low=df11["Low"]
close=df11["Close"]
vol=df11["Volume"]
#close=as.numeric(gsub(",","",df1$Close))
#vol=as.numeric(gsub(",","",df1$Volume))
#typeof((open))
m1=mean(unlist(open))
m2=mean(unlist(high))
m3=mean(unlist(low))
m4=mean(unlist(close))...
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