FNCE90056 Investment Management
The Complete Exam Bible · S2 2026FNCE90056 Overview
- 12.5 credit points
- Graduate coursework
- Semester 2, 2026
- Parkville on-campus study
Investment management decisions depend on the object being priced, the risk measure being used and the benchmark that makes performance meaningful. This guide follows the raw mathematical teaching evidence from risk and utility through portfolio construction and CAPM evaluation.
- Risk object Separate expected return, variance, covariance and systematic exposure.
- Portfolio logic Show how weights and co-movement create the portfolio result.
- Pricing test Compare observed expected return with the CAPM benchmark before interpreting alpha.
- Exam plan Practise closed-book calculations with a compact reference sheet.
How FNCE90056 is assessed
| Component | Weight | Format |
|---|---|---|
| 10 x weekly online quizzes | 10% | Individual submissions, one percent each |
| Mid-semester exam (1.5 hours) | 35% | In-person closed-book multiple-choice exam |
| Final exam (2 hours) | 55% | Assessment-period exam |
The subject guide states that the mid-semester exam is closed-book and permits one double-sided A4 reference sheet. Final-exam details are marked TBC; confirm them in the subject LMS.
Assessment structure
Weights follow the current subject assessment source. Use the table above for exact task names and formats.
Investment reasoning maps
What FNCE90056 covers
Investment management decisions depend on the object being priced, the risk measure being used and the benchmark that makes performance meaningful. This guide follows the raw mathematical teaching evidence from risk and utility through portfolio construction and CAPM evaluation.
Return, Risk and Investor Utility
Compute state-contingent return moments and use risk aversion to compare complete investment opportunities02Capital Allocation and the Sharpe Ratio
Combine a risk-free asset with a risky portfolio and interpret the capital allocation line as a reward-to-risk trade-off03Portfolio Variance and Diversification
Trace how weights, variances and covariances determine portfolio risk and the minimum-variance opportunity set04CAPM, Beta and the Security Market Line
Connect covariance with the market to beta and use the security market line as an equilibrium expected-return benchmark05Alpha and Performance Evaluation
Calculate pricing error and distinguish benchmark-relative performance from raw return or total riskThis 12.5 credit points subject currently assesses students through 10 x weekly online quizzes (10%), Mid-semester exam (1.5 hours) (35%), Final exam (2 hours) (55%). These published weights guide preparation, while the subject LMS controls current instructions and administration.
Return, Risk and Investor Utility develops a distinct route: Compute state-contingent return moments and use risk aversion to compare complete investment opportunities. Begin with expected return, meaning The probability-weighted average return across possible states. Then separate variance: The probability-weighted squared dispersion of returns around expected return.
Apply both to this problem: Compare two risky funds for investors with different risk aversion after computing expected return, variance and utility under the same state probabilities. Keep the conclusion within this control: Utility rankings depend on the stated preference model and inputs; they are not universal measures of investment quality.
Capital Allocation and the Sharpe Ratio develops a distinct route: Combine a risk-free asset with a risky portfolio and interpret the capital allocation line as a reward-to-risk trade-off. Begin with risk-free rate, meaning The return on the asset treated as having no return uncertainty over the decision horizon.
Then separate capital allocation line: The expected-return and standard-deviation combinations available from a risk-free asset and a chosen risky portfolio. Apply both to this problem: Choose between two risky portfolios by deriving each capital allocation line, then select a complete portfolio for a stated risk preference.
Keep the conclusion within this control: The Sharpe ratio compares total volatility; it does not isolate systematic risk or prove that a realised return reflects skill. Portfolio Variance and Diversification develops a distinct route: Trace how weights, variances and covariances determine portfolio risk and the minimum-variance opportunity set.
Begin with covariance, meaning A measure of the linear co-movement between two asset returns. Then separate portfolio variance: The weighted combination of asset variances and pairwise covariances. Apply both to this problem: Recompute a two-asset portfolio after changing correlation while holding individual expected returns and volatilities fixed.
Keep the conclusion within this control: Diversification changes portfolio risk through covariance; averaging standalone volatilities is not a valid calculation. CAPM, Beta and the Security Market Line develops a distinct route: Connect covariance with the market to beta and use the security market line as an equilibrium expected-return benchmark.
Begin with systematic risk, meaning Return risk associated with market-wide movements that diversification does not remove. Then separate beta: An asset's covariance with the market scaled by market variance. Apply both to this problem: Estimate the CAPM required return for two securities, compare it with each expected return and explain the pricing signal.
Keep the conclusion within this control: CAPM prices beta risk under its assumptions; total volatility alone does not determine the benchmark expected return. Alpha and Performance Evaluation develops a distinct route: Calculate pricing error and distinguish benchmark-relative performance from raw return or total risk.
Begin with capm alpha, meaning Expected return in excess of the return implied by the CAPM for the asset's beta. Then separate pricing error: The difference between an expected return and the return predicted by a pricing model. Apply both to this problem: Two managers earn different raw returns and carry different betas; calculate alpha and decide what can and cannot be inferred about performance.
Keep the conclusion within this control: Positive estimated alpha is model- and sample-dependent; it is not automatically evidence of persistent skill. Use the official assessment structure as a planning map. For every task, identify the required product, audience, evidence and operational instructions in the subject LMS before allocating effort. A weight does not reveal the complete task scope or marking basis.
A reliable study cycle retrieves definitions without notes, applies them to an unfamiliar case, compares a credible alternative under the same criteria and records the first point where evidence stops supporting the conclusion. Finish each practice answer with a responsible actor, action and review trigger. When revising, change one assumption at a time.
Recompute or retrace only the affected steps, preserve direction words and units, and explain why the result remains, narrows or reverses. This makes transfer visible and exposes memorised rules that are being used outside their conditions.
Integrate expected return with variance
- 1Define expected return and the decision boundary.
- 1Connect the evidence to variance through a stated mechanism.
- 1Use risk aversion to test a credible alternative.
- 1State the qualified conclusion and review condition.
Key terms
- Expected return
- The probability-weighted average return across possible states.
- Variance
- The probability-weighted squared dispersion of returns around expected return.
- Risk aversion
- A preference for a less risky prospect when expected return is held constant.
- Mean-variance utility
- A preference score combining expected return with a penalty for variance scaled by risk aversion.
- Risk-free rate
- The return on the asset treated as having no return uncertainty over the decision horizon.
- Capital allocation line
- The expected-return and standard-deviation combinations available from a risk-free asset and a chosen risky portfolio.
- Sharpe ratio
- Expected excess return per unit of total return volatility.
- Complete portfolio
- The investor's final combination of the risk-free asset and risky portfolio.
- Covariance
- A measure of the linear co-movement between two asset returns.
FNCE90056 FAQ
Before selecting an investment, which assumption governs the use of expected return?
Use expected return to define the starting object, select material evidence and explain the mechanism before recommending an action. Compare an alternative under the same criteria and preserve this chapter limit: Utility rankings depend on the stated preference model and inputs; they are not universal measures of investment quality.
Before selecting an investment, which assumption governs the use of risk-free rate?
Use risk-free rate to define the starting object, select material evidence and explain the mechanism before recommending an action. Compare an alternative under the same criteria and preserve this chapter limit: The Sharpe ratio compares total volatility; it does not isolate systematic risk or prove that a realised return reflects skill.
Before selecting an investment, which assumption governs the use of covariance?
Use covariance to define the starting object, select material evidence and explain the mechanism before recommending an action. Compare an alternative under the same criteria and preserve this chapter limit: Diversification changes portfolio risk through covariance; averaging standalone volatilities is not a valid calculation.
Before selecting an investment, which assumption governs the use of systematic risk?
Use systematic risk to define the starting object, select material evidence and explain the mechanism before recommending an action. Compare an alternative under the same criteria and preserve this chapter limit: CAPM prices beta risk under its assumptions; total volatility alone does not determine the benchmark expected return.
Before selecting an investment, which assumption governs the use of capm alpha?
Use capm alpha to define the starting object, select material evidence and explain the mechanism before recommending an action. Compare an alternative under the same criteria and preserve this chapter limit: Positive estimated alpha is model- and sample-dependent; it is not automatically evidence of persistent skill.
How should closed-book calculation practice be divided across the assessments?
Rehearse the weekly quiz techniques, then allocate deeper timed work to the mid-semester and final examinations in proportion to their published weights. Recompute changed inputs and verify every formula condition without notes.
Where does an investment comparison become invalid after an input changes?
Stop at the first altered input, identify the formulas and benchmarks that depend on it, and recompute only those steps. Preserve units and direction before interpreting the changed portfolio or pricing result.
How to study for the exam
Use spaced retrieval for definitions, interleave chapters through changed cases, keep an error ledger for unsupported mechanisms and finish each session by rewriting one conclusion after changing a key assumption.
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