FINM7405 Financial Risk Management
The Complete Exam Bible · S2 2026FINM7405 Overview
- UQ postgraduate finance
- Semester 2 2026
- Calculation and short answer final
FINM7405 Financial Risk Management develops a connected method for identifying an exposure, measuring its distribution and choosing a control that reduces the right loss channel. The course starts by separating measurable risk from uncertainty, because a model only helps when its probabilities and assumptions can be defended.
- Assessed by Two exams, an individual assignment and a team trading game
- Hardest step Choosing a model whose assumptions match the exposure
- How to prepare Recompute the worked methods and explain every residual risk
What you get in the full FINM7405 Exam Bible
- 6 chapters, 29 pages — every examinable topic
- 18 original practice questions, each with a model answer in the Final Exam format
- 6 worked examples, solved the way FINM7405 marks
- 9 computed figures, redrawn from the course’s own numbers
- Exam-morning plan for the Final Exam (35%) — what to revise last, where marks are lost
Free on this page: assessment table, chapter map, one worked example, key terms, FAQ. The rest is in the full exam bible.
How FINM7405 is assessed
| Component | Weight | Format |
|---|---|---|
| Mid-Semester Exam | 25% | Saturday; covers the first four or five weeks depending on the scheduled date; 30 multiple-choice questions |
| Individual Assignment | 25% | Two sections: applied risk-management system work using Excel, then research and critique using writing and data |
| Trading Game | 15% | Three team workshops, each worth five marks, meeting risk and return targets |
| Final Exam | 35% | Final exam period; all course content with emphasis on weeks not covered mid-semester; calculations and short answers |
The Semester 2 lecture publishes all four weights, which total 100%. It does not publish final duration, permitted materials or a hurdle rule in the available course materials.
What other students are asking about FINM7405
- Where can I find lecture notes or study guides for FINM7405 at UQ?
- The FINM7405 study guide in AskSia Library covers Financial Risk Management in 6 chapters, with the assessment table, a chapter-by-chapter topic map, key terms and a worked example, free to read on this page.
- Is there a final exam in FINM7405, and how much is it worth?
- Yes. In the offering this AskSia Library guide is built from, Final Exam carries 35% of the FINM7405 mark; the full split is Mid-Semester Exam 25%, Individual Assignment 25%, Trading Game 15%, Final Exam 35%.
- What does FINM7405 cover on volatility, correlation and tail risk?
- In AskSia Library's FINM7405 guide, the Volatility, Correlation and Tail Risk chapter explains variance, GARCH memory, dependence breakdown and fat tails.
- What does FINM7405 cover on var, expected shortfall and stress tests?
- In AskSia Library's FINM7405 guide, the VaR, Expected Shortfall and Stress Tests chapter explains thresholds, tail severity, simulation, backtesting and scenarios.
- What does FINM7405 cover on interest rate and fixed-income risk?
- In AskSia Library's FINM7405 guide, the Interest Rate and Fixed-Income Risk chapter explains bond sensitivity, duration, convexity, spreads and immunisation.
What FINM7405 covers
Six source topics build one risk toolkit from classification and volatility to tail loss, fixed income, options and derivative hedging.
Risk, Uncertainty and Risk Management
Classification, exposure chains, controls and residual riskRisk management begins by separating exposures whose probabilities can be estimated from uncertainty that resists stable probability estimates.
- Risk versus uncertainty
- Identification, quantification and mitigation
- Market, credit, liquidity and operational risk
- Exposure, trigger, amplifier and loss chains
- Controls, incentives and residual risk
Volatility, Correlation and Tail Risk
Variance, GARCH memory, dependence breakdown and fat tailsVolatility measures return dispersion, but financial risk changes through time and concentrates in the tails.
- Variance and standard deviation
- Historical and implied volatility
- ARCH and GARCH conditional variance
- Correlation and portfolio diversification
- Skewness, kurtosis and fat tails
VaR, Expected Shortfall and Stress Tests
Thresholds, tail severity, simulation, backtesting and scenariosValue-at-Risk compresses a loss distribution into a threshold at a stated confidence level and horizon. Expected Shortfall answers the next question by averaging losses beyond that cut.
- VaR as a loss quantile
- Parametric VaR calculation
- Historical and Monte Carlo simulation
- Expected Shortfall and tail severity
- Backtesting and stress testing
Interest Rate and Fixed-Income Risk
Bond sensitivity, duration, convexity, spreads and immunisationFixed bond cash flows change in value when the rates used to discount them change. This chapter develops the inverse price-yield relationship and the sensitivity measures used to control it.
- Bond pricing and the price-yield curve
- Macaulay and modified duration
- DV01 and portfolio duration
- Convexity and key-rate duration
- Spread risk and immunisation
Options Pricing and Greeks
Payoffs, parity, Black-Scholes, trees, Greeks and hedgingOptions create nonlinear rights whose terminal payoff must be distinguished from current price and investor profit. This chapter begins with call and put payoffs, moneyness, bounds and put-call parity.
- Call and put payoff geometry
- Put-call parity and arbitrage bounds
- Black-Scholes and risk-neutral pricing
- Delta, gamma, theta, vega and rho
- Binomial trees, strategies and option VaR
Forwards, Futures and Swaps
Carry pricing, margin, futures hedges and swap durationDerivative hedging begins with replication and direction. A forward delivery price follows from spot and carry rather than a forecast of the terminal asset price.
- Forward contracts and carry pricing
- Futures margin and daily settlement
- Commodity and basis hedging
- Treasury futures and duration targeting
- Swap valuation and swap duration
It then builds the statistical toolkit: variance and volatility, ARCH and GARCH memory, correlation and portfolio risk, skewness, kurtosis and fat tails.
The market risk block turns those inputs into decision measures. Value-at-Risk locates a loss threshold at a stated confidence and horizon, while Expected Shortfall measures average severity beyond that threshold.
Historical simulation, Monte Carlo methods, backtesting and stress testing show why a single number is not enough. Each method is useful, but each has a different blind spot.
Fixed-income analysis applies the same logic to rates and spreads through bond pricing, duration, DV01, convexity, key-rate exposure and immunisation.
Options then add nonlinear payoffs, put-call parity, Black-Scholes pricing, binomial trees and the Greeks. The final block uses forwards, futures and swaps to price carry and reshape market or duration exposure without selling the underlying portfolio.
The published Semester 2 assessment includes a mid-semester exam, an individual assignment, a team trading game and a final exam.
The final combines calculations with short answers, so preparation must join accurate working to clear interpretation. This guide therefore shows every numerical step, checks direction and scale, and closes each method with the residual basis, liquidity, counterparty or model risk that remains after the headline hedge.
Worked example · free
From daily volatility to dollar VaR
The marks used here partition the VaR reasoning and are not a published university assessment scheme.
- +1Combine mean and the left-tail score: 0.04% + (-2.326 x 1.30%) = -2.9838%.
- +1Quote VaR as a positive loss threshold: 2.9838%.
- +1Multiply by position value: 0.029838 x $12,000,000 = $358,056.
- +1State the coordinates: one-day horizon and 99% model confidence.
- +1Explain that losses beyond $358,056 remain possible and require ES and stress tests.
Key terms
- Value-at-Risk
- A positive loss threshold at a stated confidence level and horizon under a specified model.
- Expected Shortfall
- The average loss in the tail beyond a selected VaR threshold.
- Conditional Volatility
- A volatility estimate that changes with current information and recent shocks.
- GARCH
- A conditional variance model that combines a new squared shock with lagged variance.
- Correlation
- A standardised measure of linear co-movement used to combine asset risks.
- Fat Tail
- A distributional tail that places more probability on extreme observations than a normal model.
- Modified Duration
- The first-order percentage sensitivity of a bond price to a small yield change.
- Convexity
- The curvature correction that improves a duration estimate for larger yield movements.
- DV01
- The approximate currency change in bond value for a one-basis-point yield movement.
- Delta
- The first-order sensitivity of option value to the underlying asset price.
- Gamma
- The rate at which option delta changes as the underlying price moves.
- Basis Risk
- The residual exposure created when a hedge instrument and the underlying position do not move identically.
FINM7405 FAQ
How is the course assessed?
The published Semester 2 breakdown is a 25% Mid-Semester Exam, 25% Individual Assignment, 15% Trading Game and 35% Final Exam. The four numeric weights total 100%. The available materials do not publish a hurdle rule, so check current operational instructions on Learn.UQ.
What does the final exam cover?
The lecture says the final examines all course content and places more emphasis on weeks not covered by the mid-semester exam. It combines calculation and short-answer questions. Duration and permitted materials are not stated in the available course materials, so verify them on Learn.UQ.
How demanding is the course?
The challenge comes from joining mathematical working to model judgement. A correct VaR, duration or option value is incomplete if the answer omits horizon, sign, assumptions or residual risk. Practice recomputing examples and explaining why each method can fail under stressed conditions.
What is the difference between VaR and Expected Shortfall?
VaR identifies the loss threshold at a chosen confidence and horizon. Expected Shortfall averages the losses beyond that threshold, so it says more about tail severity. Two portfolios can share a VaR while carrying very different losses once the threshold is crossed.
Why are duration and convexity both needed?
Modified duration gives a linear first-order estimate of bond price sensitivity to yield. The actual price-yield relationship is curved, so convexity adds a second-order correction that becomes more important as the yield shock grows. Neither measure alone covers spread or curve-shape risk.
How should I choose between futures and swaps for a hedge?
Start with the risk driver, horizon and cash-flow constraints. Futures are liquid and standardised but settle daily and create basis and margin risk. Swaps can match longer custom duration exposures but add counterparty, collateral and curve risks. Check that the hedge direction opposes the original exposure.
Questions students ask in each FINM7405 chapter
- Why does the risk and uncertainty distinction matter?
- It determines the response. Estimable risk can support pricing, limits and hedges, while genuine uncertainty needs scenarios, resilience and governance. A precise number does not remove uncertainty when the probability model itself is unstable. Chapter 01 · Risk, Uncertainty and Risk Management
- Why does GARCH remember a shock?
- The new squared shock enters through alpha, while beta carries the previous conditional variance into the new forecast. When alpha plus beta is close to one, the effect fades slowly rather than disappearing after one calm day. Chapter 02 · Volatility, Correlation and Tail Risk
- Is VaR the maximum possible loss?
- No. VaR marks a quantile where the bad tail begins. It does not bound the losses beyond that point. Expected Shortfall and stress tests are needed to describe severity and coherent scenarios inside the tail. Chapter 03 · VaR, Expected Shortfall and Stress Tests
- Why do bond prices fall when yields rise?
- The contractual cash flows are discounted at the higher required yield, reducing their present value. The inverse relationship is strongest for long-duration cash flows because more of their value arrives farther in the future. Chapter 04 · Interest Rate and Fixed-Income Risk
- What is the difference between option payoff and profit?
- Payoff is the contract value at maturity, such as max(S minus K, 0) for a call. Profit also deducts the premium and financing. An in-the-money option can still produce a trading loss if the payoff does not cover the premium. Chapter 05 · Options Pricing and Greeks
- Why is forward price not a forecast?
- The no-arbitrage forward price comes from spot, financing and any income, storage cost or convenience yield. It is the price that prevents cash-and-carry arbitrage, not a claim about the most likely terminal spot. Chapter 06 · Forwards, Futures and Swaps
How to study for the exam
Build one calculation and one interpretation routine for each block. For volatility, move from variance units to volatility only after the conditional or portfolio calculation is complete. For VaR, write confidence, horizon and the positive-loss sign convention beside the result, then compare the threshold with Expected Shortfall and a stress scenario.
For bonds, state the direction of the yield move before applying duration and convexity, and separate risk-free rate exposure from spread risk. For options, draw terminal payoff, distinguish payoff from profit, and treat delta as a local hedge that gamma can change. For forwards, futures and swaps, derive direction from the underlying cash exposure and rebuild target dollar duration as an independent check.
Use the tutorial problems as method practice, but change the numbers and solve from a blank page. Finish every answer by naming the residual risk: basis, liquidity, counterparty, model, curve-shape or jump exposure. That final sentence is where a calculation becomes a risk-management recommendation.
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