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What is reverse stress testing and how does it differ from conventional stress testing?
Reverse stress testing works backwards from a catastrophic outcome — like the firm becoming non-viable — to identify which scenarios could cause it. Unlike conventional stress tests that apply predefined scenarios, reverse stress tests reveal hidden vulnerabilities by forcing institutions to identify their actual breaking points.
How does a synthetic CDO work, and why does credit correlation dramatically affect tranche pricing?
A synthetic CDO creates tranched credit exposure using a portfolio of credit default swaps rather than physical bonds. Credit correlation dramatically affects tranche pricing because it determines whether defaults occur independently or in clusters.
How does survival analysis model the timing of credit defaults, and what is the hazard rate?
Survival analysis models the time until default rather than just predicting a binary outcome. The hazard function represents the instantaneous default rate at time t conditional on survival to that point, and the survival function gives the probability of not defaulting beyond time t.
How does seasonality in commodity markets affect futures pricing and the shape of the forward curve?
Seasonality is one of the most tangible drivers of commodity forward curve shape because physical supply and demand follow predictable calendar patterns. The cost-of-carry model connects seasonal convenience yield shifts to observable contango and backwardation patterns in futures curves.
What is incremental VaR and how is it used for position sizing decisions?
Incremental VaR measures the change in portfolio VaR when a position is added or removed: IVaR = VaR(with) - VaR(without). It can be positive (increases risk) or negative (hedges). It's the primary metric for pre-trade risk assessment and position sizing.
How do netting agreements reduce credit exposure and what is close-out netting?
Close-out netting under ISDA Master Agreements allows all transactions with a counterparty to be terminated and marked to market upon default, with positive and negative values netted into a single amount. This typically reduces exposure by 80-90%.
How does bootstrapping work for statistical inference in risk management?
Bootstrapping creates thousands of simulated samples by drawing with replacement from the original data, allowing estimation of sampling distributions without distributional assumptions. It is especially useful for non-standard statistics like VaR confidence intervals.
What is the TBA market and how does it work for mortgage-backed securities?
TBA (To Be Announced) is the primary trading mechanism for agency MBS, where six parameters are agreed upon at trade but the specific mortgage pool is announced 48 hours before settlement. This market enables originators to hedge pipeline risk by forward-selling MBS.
How do credit transition matrices work and how are they used in portfolio credit risk?
A credit transition matrix shows the probability that an obligor rated in a given category at the start of a period will migrate to any other rating category or default by the end of the period. Each row represents the starting rating and each column represents the ending rating.
How do you calculate Expected Shortfall and why is it replacing VaR in Basel regulations?
Expected Shortfall is the average loss in the tail beyond VaR, answering 'how bad do losses get when things go wrong.' ES is a coherent risk measure (satisfying subadditivity), while VaR is not. FRTB replaced 99% VaR with 97.5% ES as the regulatory standard for market risk capital.
What's the difference between CreditMetrics and CreditRisk+ for modeling credit portfolio risk?
CreditMetrics models credit rating migrations and default using correlated asset returns and Monte Carlo simulation, while CreditRisk+ models only defaults using a Poisson process with sector factors and closed-form solutions. CreditMetrics captures spread risk from downgrades; CreditRisk+ is computationally faster but limited to default losses.
What's the difference between Gaussian and Student-t copulas, and why does tail dependence matter?
Copulas separate marginal distributions from dependence structure. The Gaussian copula has zero tail dependence regardless of correlation, meaning it underestimates the probability of simultaneous extreme events. The Student-t copula captures positive tail dependence, making it better for modeling crisis scenarios.
How do you value a fixed-for-fixed currency swap mid-life with a worked example?
Valuing a currency swap mid-life means treating each leg as a separate bond, discounting at the appropriate currency's rate, then converting to a common currency using the current spot rate. The difference gives the swap's mark-to-market value.
How are operational risk loss events classified under Basel, and what are the seven event types?
Basel defines seven operational risk loss event types: internal fraud, external fraud, employment practices, clients/products/business practices, physical asset damage, system failures, and execution/delivery errors. The key differentiator between categories is whether there was intent (fraud) vs. error (process failure).
Can someone explain CVA (Credit Valuation Adjustment) intuitively and show how it's calculated?
CVA is indeed one of the more challenging FRM Part II topics, but it becomes intuitive once you see the logic. Imagine you enter a swap and the counterparty defaults while the swap has positive value to you — CVA is the expected present value of that potential loss, calculated by summing LGD times expected exposure times marginal default probability across time periods.
How do endowment funds manage tail risk?
Post-2008 endowments use liquidity budgets, stress-tested capital call schedules, spending smoothing, and tail-risk hedging overlays.
What is the difference between OTC and exchange-traded derivatives, and how does clearing work for each?
Understanding OTC vs exchange-traded derivatives is fundamental to FRM Part I. Exchange-traded derivatives use central counterparties for daily margining, while OTC derivatives can be bilateral or centrally cleared. Post-2008 reforms now mandate central clearing for standardized OTC contracts, dramatically reducing systemic counterparty risk.
How do you calculate the settlement amount on a Forward Rate Agreement (FRA)?
FRA settlement is a classic FRM Part I topic that tests whether you understand present value mechanics in money markets. A Forward Rate Agreement is an OTC contract where two parties agree on an interest rate for a future period, and settlement is discounted because it occurs at the beginning of the reference period.
Can someone explain the main hedge fund strategies — long/short equity, event-driven, and relative value — with concrete examples?
The three major hedge fund strategies differ in their return sources: long/short equity profits from stock selection, event-driven strategies profit from corporate events like mergers and bankruptcies, and relative value strategies exploit pricing discrepancies between related securities.
How do you test for a unit root and what does the Dickey-Fuller test actually tell you?
The Dickey-Fuller test detects unit roots by testing whether the AR(1) coefficient equals 1. Crucially, it uses special critical values more negative than standard t-values because the test statistic follows a non-standard distribution under the null.
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