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代寫MGMT20005、代做Decision Analysis程序

時間:2023-12-16  來源:合肥網hfw.cc  作者:hfw.cc 我要糾錯


MGMT20005-Business Decision Analysis

Assignment 2: Group Assignment

Page | 1

Introduction: This is a group assignment of up to 3 students (**3 students) from the same tutorial group. You are also

allowed to form a group with students of the same tutor. Note that if the group is formed with students of different

tutors, you will receive zero marks for this assignment. You can complete your assignment individually, if you wish,

however, you are strongly encouraged to complete this assessment in a group setting.

Weight: 30% of the total mark.

Format: PowerPoint file (.pptx/.pdf) + Recorded presentation (.mp4) + Excel workbook (.xlsx)

Due date: 6pm Week 11, Friday October 13, 2023.

Submission: Only one submission (with all your files) is required for each group. Make sure you include the names and

student numbers for all team members on the front slide of your PowerPoint file submission!

Late submission: It will attract a marking penalty. A 10% penalty will be applied for every day of late submission for up

to 3 days. Assignments submitted later than 3 days after the due date will not be marked and will receive no mark.

Special Consideration: No extension will be provided for this assignment (since this is a group submission no

submission will be provided even for individual work).

Submission format and word limit:

1. Prepare your submission using Microsoft PowerPoint (or similar presentation software is also okay). You can

use up to 30 slides and up to 2,500 words in your slides altogether (excluding figures, tables, references, and

appendices). Your slides should be well-organised, coherent, and visually appealing. Note that it is important

to cover all below the requirements in your submission.

2. A maximum of 5-minute recorded presentation outlining your analysis and assessment of your portfolio

optimisation methods used. You may choose to use the same deck of slides that you and your group have put

together (or a revised slide deck) if you find this suitable and appropriate for the 5-minute presentation. You

must submit an .mp4 file (or similar) for your video presentation and it is a requirement to show your face/s in

your presentation recording.

Assignment Details

This assignment is designed to let you explore and evaluate a number of approaches for portfolio optimisation, using

live real-world data from the Yahoo finance website. The relevant URL for finding stock prices is

https://au.finance.yahoo.com/. Under the “Quote lookup”, you can search for the industry/business you are

interested in to explore investment (assets).

Portfolio Optimisation - Risk and Return: An investment portfolio consists of a collection of investment items (or

stocks or assets) held by an individual or organisation, in which the investor seeks to purchase a variety of assets to

gain a good return (profit) through increasing assets value. Individual assets vary in value from minute to minute, and

whilst over time, they might grow in value, their value fluctuates over time. The possibility of such fluctuations

represents a risk to the investor. Accordingly in portfolio selection, investors should wisely choose to invest across a

range of assets, ideally those total value is less liable to fluctuation than the individual assets.

In this assignment, you are required to use asset return data from a period of 4 years to identify the optimum

portfolio using a variety of different optimisation methods. The assignment report (slides) should include three main

sections: Preliminary Work, Optimisation Models and Conclusion. The requirements of each part are detailed below.

The breakdown of marks (a total of 30) is given on this document and as a Rubric in Canvas.

MGMT20005-Business Decision Analysis

Assignment 2: Group Assignment

Page | 2

Preliminary Work (4 marks: Data collection + Classifications)

The first stage is to identify a set of 10 investment items from which you will subsequently determine optimum

portfolios using various optimisation models. You may select any global assets (including indices) whose data is

provided on the Yahoo finance website. After you searched for the stock under the “Quote lookup”, go to the

“Historical data” tab, then choose the appropriate Time period, and Frequency before downloading the data.

The chosen assets must satisfy the following general conditions:

 Each must have at least 48 months (August 2019 - August 2023) of monthly data available, up to and

including August 2023.

 They should be selected from any 3 different sectors/categories of your choice (let’s called them C1, C2,

and C3) e.g., banking, pharmaceuticals, media, technology, government bonds, property trusts, etc., with at

least 2 assets in each category.

 You need to calculate the monthly return of each asset by (Stock_value_new –

Stock_value_old)/(Stock_value_old). Then the average return of an asset is the mean of return of that asset

over the 48 months. Similarly, the risk is calculated as the standard deviation of return over 48 months. A

sample Excel file is provided that includes a sample data with the calculation of return and risk.

Data should span a reasonable range of volatilities/risks. Classify the assets into 4 groups according to

(ascending) risk (let’s call them R1, R2, R3, and R4). A simple classification approach would be to calculate

the standard deviation of each asset (as explained in the previous dot point) and define risk categories

based on the 4 quartiles. Therefore, R1 should include investment stocks with the lowest risk (lowest

standard deviation).

Recall that each asset lies in one of the Rs and in one of the Cs.

Optimisation Models

The assignment requires you to consider two different optimisation techniques: linear programming and integer

linear programming. For each optimisation model, explain the optimisation approach taken, the mathematical

formulation and identify how the Excel Solver is to be used (explain any constraints used – e.g., that a variable needs

to be an integer or binary).

 LP model (11 marks: Mathematical Model + Excel Solver and Reports + Discussion): In this approach, the aim is

to achieve the maximum overall return of the portfolio, subject to specified requirements on risk mix

(percentages in R1 to R4) and category mix (percentages in C1 to C3). Note that the overall return of a portfolio

(or its expected return) is calculated as a weighted average of the expected returns of all assets, where the

weights represent the proportions of the portfolio that should be invested in each asset.

The following investment guidelines are to be applied to the Linear Programming model:

1. Investment in the highest-risk assets shouldn’t exceed 15% of the portfolio, while the lowest risk assets

should have the highest investments among all other risk categories.

MGMT20005-Business Decision Analysis

Assignment 2: Group Assignment

Page | 3

2. The ratio investment in R2 to R3 must be at least 2 to 1.

3. To ensure diversification, each sector category must have a minimum of 20% invested; apart from one sector

that you choose (your discretion) to have a minimum of 30% invested.

4. The minimum investment in each asset should be 10%.

Use Excel’s reports to comment on binding constraints, and the impacts of changes to the risk and category

constraints on the optimum portfolio (sensitivity analysis). Further, if an asset(s) is not selected in your optimal

solution, explain how much its return should be changed, so that asset can be included in your optimal selection.

 ILP model (6 marks: Mathematical Model + Excel Solver and Discussion): In this approach, we assume that a

balanced portfolio of exactly 6 stocks is to be chosen. The 3 asset categories (the C classification) must be

included. In addition, at most 1 of the assets can be in the riskiest group, and at least 2 must be in the least risky

group. Finally, an asset from R3 can be selected only if at least one asset from R2 is selected.

Conclusion (4 marks: comparison + conclusion + overall presentation)

Summarise your work (of all the above parts), present all your results comparatively, coherently and compellingly.

Then, based on your assessment of the various approaches, briefly explain a strategy that you might prefer to use for

this portfolio optimisation problem. Include a summary table detailing each chosen portfolio and the basis of choice,

compare each of your chosen portfolios.

Recorded 5-minute Presentation (5 marks)

Your task is to create a concise 5-minute recorded presentation about portfolio optimisation strategies.

You can imagine you are addressing a distinguished panel of executives at a leading investment firm. Begin by

providing a comprehensive overview of your carefully selected 10 investment items, showcasing your keen

understanding of the market landscape. Afterward, briefly explain a preferred portfolio optimisation strategy,

providing reasons for your choice and including a summary table comparing each selected portfolio. This

presentation should showcase your understanding of investment strategies and your ability to communicate them

effectively. You may choose to use the same deck of slides that you and your group have put together to support

your presentation, if you find this suitable and appropriate.

Begin by providing an overview of your 10 investment items and then assess the two approaches you have examined

above using real-time data from Yahoo Finance. Afterward, briefly explain a preferred portfolio optimisation

strategy, providing reasons for your choice and including a summary table comparing each selected portfolio. This

presentation should showcase your understanding of investment strategies and your ability to communicate them

effectively. You may choose to use the same deck of slides that you and your group have put together to support

your presentation, if you find this suitable and appropriate.

You must submit an mp4 file (or similar) for your video presentation. We recommend using Zoom (see Zoom

Recording Basics) to record your video presentation, but you may use another tool of your choice and then upload

the video file into Canvas in the submission tool with your presentation slides. It is a requirement to show your

face/s in your presentation recording.

MGMT20005-Business Decision Analysis

Assignment 2: Group Assignment

Page | 4

Marking guide

Assignments will be marked based on the methodologies adopted and the quality of work. Given the vast range of

assets to select from on the Yahoo website, it is highly unlikely that you will choose the same portfolio of stocks as

another student group.

It is important to pay special attention to spelling, grammar, and punctuation to avoid ambiguity and confusion.

Students can include relevant graphs, tables, and other exhibits such as appendices. They must be clearly labelled and

will not be included in the word count.

Marking Scheme for Assignment 1 Files Marks

Prelim – 4 marks

Data acquisition, background and description Excel & PowerPoint 2

Classifications, explanation of procedure Excel & PowerPoint 2

Linear Programming – 11 marks

Mathematical model PowerPoint 3

Solver, results and discussion Excel & PowerPoint 4

Sensitivity Analysis and discussion Excel & PowerPoint 4

Integer Linear Programming – 6 marks

Mathematical model PowerPoint 3

Solver, results and discussion Excel & PowerPoint 3

Overall Discussion and Conclusion – 4 marks

Comparison, conclusion, and overall presentation PowerPoint 4

Recorded Presentation – 5 marks MP4 file 5

TOTAL – 30 marks 30

Feedback prior to submission: Students can seek assistance from the teaching staff to ascertain whether their

assignment conforms to submission guidelines through:

- Discussion board (Canvas): as other students can also benefit from your questions and replies.

- Consultation: with prior arrangement with your tutor or lecturer.

Feedback after submission: Your assignment feedback will be returned within two weeks of the due date in a rubric

on the LMS site with an overall mark and intext/overall comments.

 

請加QQ:99515681 或郵箱:99515681@qq.com   WX:codehelp

 

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