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MIS775 – DECISION MODELLING FOR BUSINESS ANALYTICS

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MIS775 – DECISION MODELLING FOR BUSINESS ANALYTICS

MIS775 – DECISION MODELLING FOR BUSINESS ANALYTICS

Subject Code – MIS775
Subject Name – Decision Modelling for Business Analytics
University Name – Deakin Business School, Australia

Decision Modelling for Business Analytics,  the purpose of this course is to provide an opportunity for students to enhance their knowledge and understanding to build complex decision models and use advanced quantitative modeling techniques to develop solutions to business problems.

Decision Optimization Techniques

Linear Programming

Linear programming is a special case of mathematical programming. Linear programming is the challenge of maximizing or minimizing a linear function under linear constraints.

Non-Linear Programming

Nonlinear programming is a mathematical technique for finding optimal solutions to optimization problems with nonlinear functions as the objective function or as some of the constraints.

About Deakin Business School

Deakin Business School, Australia provides major postgraduate courses in business programs like Masters of Business Administration, Master of Commerce, Master of International Business, Master of Marketing as well as Executive Development programs. The university also offers graduate and diploma programs to the students worldwide.

Assessment Details

Learning Outcomes

⦁ Use a decision model to conceptualize, formulate, and depict a business challenge.
⦁ Using digital tools, create business decision models
⦁ Apply decision-making tools such as optimization, stochastic modeling, and risk analysis to your decision-making.
⦁ Create and assess the usefulness of alternative solutions
⦁ Perform sensitivity analysis.
⦁ Gain a broad understanding of sophisticated business analytics modeling tools and approaches.

Investment Portfolio Optimization

The assignment has three main sections: Preliminary Work, Optimisation Models, and Report. The requirements of each section are detailed below.
This assignment is designed to let you explore and evaluate a number of approaches to investment portfolio optimization, using live real-world data.

Preliminary Work (4marks)

This assignment is designed to let you explore and evaluate a number of approaches to investment portfolio optimization, using live real-world data.

The chosen assets must satisfy the following general requirements:
• Each has 37 consecutive months of opening prices, up to and including 1 February 2022.
• They should be selected from the five industry categories (C1 to C5) listed in the table, namely Technology, Basic Materials, Financial, Healthcare, and Telecom & Utilities. You must choose only one asset from each of these five categories.
• For each of the 10 assets (i.e. the five given assets and the five you chose), calculate monthly returns, and average return, and then use standard deviation to find their risk.
• The 10 assets should span a reasonable range of volatilities/risk. For this reason, you might try several assets in a category before settling on one.
• Classify each of the 10 assets (i.e. the five given stocks and the five you chose) into one of three risk groups R1, R2, and R3, where R1 < R2 < R3. It is up to you to determine the basis for the risk classification, but you must have at least three assets in each risk group.
• Each asset must belong to one of the five industry categories and one of the three risk categories.

Optimization Models

Use three optimization techniques, which are:
Linear Programming (6marks)
Integer Linear Programming (6marks)
Non-Linear Programming (12marks)

Report (12marks)
The PowerPoint document should present all your results in a coherent and compelling manner. Each model should be accompanied by the following:
• A conceptual diagram of the model
• An algebraic formulation of the model
• The optimal solution
• Interpretation of sensitivity analyses output for Optimisation Approach 1. (Use Solver’s sensitivity analysis reports to comment on how changes to constraints might affect the optimum set of projects.)

Then, based on your assessment of the various approaches, briefly explain which approach you would prefer to use for selecting the optimal set of projects, and why. Include a summary table listing the details of each optimal set of projects.


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