Murdoch BUS329 Investment Analysis Group Assignment TS 2026: Single Index Model and Risk Decomposition, Singapore

BUS329 Investment Analysis Group Assignment, TS 2026 (Murdoch University, Singapore)

In this Murdoch University BUS329 assignment for the TS 2026 session in Singapore, each group member takes one listed company and estimates its single index model using five years of monthly returns. You then decompose total risk into systematic and firm-specific parts, compare results across the group, and write a structured report that critically explains what the betas and risk shares mean for investors.

What You Are Expected to Do

1. Regression Estimation

Run an Ordinary Least Squares (OLS) regression on your monthly returns using the Single Index Model:

R_i,t = α_i + β_iR_m,t + e_i,t

• R_i,t = return of firm i at time t (dependent variable)
• R_m,t = return of the market index at time t (independent variable)
• α_i = intercept
• β_i = slope coefficient (market beta)
• e_i,t = residual / firm-specific error term at time t

2. Risk Decomposition

Using the regression output, decompose the total variance of the stock into its two parts: σ²_i = β²_iσ²_m + σ²(e_i).

• Calculate total stock return variance (σ²_i) and total market index variance (σ²_m).
• Compute systematic risk (β²_iσ²_m).
• Compute unsystematic / firm-specific risk (residual variance σ²(e_i)).
• Verify that the ratio of systematic risk to total risk equals R².

3. Results and Critical Analysis

• Beta analysis: is the stock defensive (β < 1), aggressive (β > 1) or neutral (β = 1)? Does this match the fundamentals and cyclicality of the firm’s industry?
• Alpha and statistical significance: what is the estimate of α, and is it significantly different from zero (p-value / t-statistic)? What does this imply about excess performance relative to the market over the sample period?
• Risk breakdown: what percentage of variance is explained by market movements (R²) and what percentage by firm-specific events (1 − R²)? Identify 2 to 3 major company-specific news events in the 5-year sample (earnings announcements, regulatory shifts, CEO changes) that explain large spikes in the residuals.
• Portfolio context: how can an investor eliminate the firm-specific risk identified in your model?

Structure of the Report

1. Executive summary (group, max 300 words): overview of the company, proxy index, period and headline findings.
2. Introduction (group, max 300 words): purpose, the selected firms, the analytical approach (intra-firm analysis then inter-firm comparison) and report structure.
3. Methodology (group): data sources and formulas used.
4. Regression and risk findings (individual): regression tables, α, β, R², variance decomposition percentages, and a scatter plot of market return (x-axis) against stock return (y-axis) with the fitted characteristic line.
5. Discussion and qualitative evaluation (individual, max 300 words per student): link the statistical outputs to macroeconomic factors and firm-level events, with emphasis on firm-specific risk (residual plot) and 2 to 3 news events that match residual spikes.
6. Inter-firm comparison (group, max 500 words): compare β, α and the systematic versus firm-specific risk split across the selected firms, how they behave together in a portfolio, and how diversification removes firm-specific risk.
7. Conclusion (group, max 300 words): key empirical results and actionable takeaways for a portfolio manager.

Other Guidelines

• Total word limit 2,300 (excluding cover page, tables, figures, references and the Excel workings file).
• Word document, Times New Roman 12 pt, 1.5 line spacing, 2.54 cm margins; APA 7th edition or Chicago referencing; university assignment cover sheet.
• Submit an Excel/Google Sheets file (raw monthly prices, percentage returns, OLS output and risk decomposition, clearly labelled), the written report and the group project plan from the LMS.
• AI may be used only to understand terminology, find and summarise research papers or format references; drafting or polishing text with generative AI is treated as academic misconduct.

Get Expert Help with BUS329 Investment Analysis

Get the data right first: use the same market index and the same period for every firm, compute excess returns correctly and report the regression output in a clean table. In the discussion, link each beta and R-squared to the company’s industry and business model, and be careful with the brief’s rules on generative AI, which only allow limited uses.

Our finance and management assignment help supports the regression and analysis, and our submit your assignment page lets you share the brief for a quick quote. See also the Murdoch Social and New Media report brief.