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FRM Updated
What's the difference between a credit-linked note (CLN) and a total return swap (TRS), and when would a bank use each?
Both CLNs and TRS transfer credit exposure, but they differ fundamentally. A CLN is funded — the investor puts up cash and receives higher yield with principal at risk. A TRS is unfunded — transferring full economic exposure including price changes.
What is risk factor mapping and how is it used to measure portfolio market risk?
Risk factor mapping is the process of expressing every position in a portfolio as a function of a manageable set of underlying market risk factors. This dimensionality reduction is necessary before computing VaR because modeling every individual security directly is computationally infeasible.
How do external loss data consortia like ORX work?
The Operational Riskdata eXchange (ORX) is the largest global banking consortium for pooling operational loss data, with over 100 member banks sharing anonymized loss events...
How should a pension plan set asset allocation given its liabilities?
LDI allocation scales liability-hedging vs return-seeking with funded ratio, using a glide path anchored in sponsor risk tolerance.
What LGD floors does Basel III final impose and how do they vary?
Basel III final imposes LGD floors: secured corp 20-25%, unsecured corp 25%, retail mortgage 5%, QRRE 50%. Prevents overly optimistic internal estimates. Larchwood's CRE loan LGD flooring raises RWA 66%...
What is ring-fencing in banking, and how does structural separation improve resolvability?
Ring-fencing legally separates retail banking from investment banking within a banking group, creating a firewall so that losses in trading and wholesale activities cannot threaten essential retail services. The UK implemented full structural ring-fencing in 2019.
What is a resolution stay, and how does the ISDA Resolution Stay Protocol prevent disorderly unwinds during bank resolution?
A resolution stay temporarily suspends counterparties' rights to terminate derivatives and other financial contracts when a bank enters resolution. The ISDA Resolution Stay Protocol extends this cross-border by having parties contractually agree to recognize foreign resolution actions.
How do historical and hypothetical scenario analyses differ, and how should a risk manager design effective stress tests?
Scenario analysis evaluates portfolio performance under specific adverse conditions, either drawn from historical events or constructed from hypothetical narratives. A structured five-step framework helps risk managers design internally consistent and actionable stress tests.
How do risk factor sensitivities like DV01, delta, and vega help a risk manager understand portfolio exposures?
Risk factor sensitivities like DV01, delta, and vega measure how portfolio value changes for small moves in individual risk factors. They are actionable, decomposable, and transparent building blocks that complement VaR for day-to-day risk management.
How does the FRTB Standardized Approach for market risk work?
The FRTB Standardized Approach is a sensitivity-based method with three components: the Sensitivities-Based Method (delta, vega, curvature across seven risk classes), the Default Risk Charge, and the Residual Risk Add-On. It uses three correlation scenarios to capture correlation instability.
Why do we model operational loss severity with a lognormal distribution?
The lognormal distribution is preferred for loss severity modeling because it's always positive, right-skewed, and captures the multiplicative nature of operational losses. Most losses are small, but the long right tail accommodates the occasional massive outlier.
How does the FRTB define the boundary between the trading book and banking book, and why was it redesigned?
The trading book/banking book boundary is one of the most fundamental concepts in bank capital regulation, and the FRTB redesigned it to close a major regulatory arbitrage that existed under Basel II/II.5.
How do you forecast volatility multiple steps ahead using a GARCH(1,1) model?
Multi-step forecasting with GARCH(1,1) is a critical skill for FRM because risk managers need volatility estimates over holding periods longer than one day. The key formula shows the forecast converging to the long-run variance.
How do regulators and banks validate market risk models through backtesting?
Backtesting validates VaR models by comparing exceptions (VaR breaches) to the expected rate. The Basel traffic light framework uses exception counts, while formal tests like Kupiec's POF and Christoffersen's conditional coverage assess both frequency and independence.
How does securitization create moral hazard, and what risk retention rules try to fix it?
Securitization creates moral hazard by separating origination from risk-bearing, reducing incentives for careful underwriting. Post-crisis regulations require 5% risk retention and enhanced disclosure, but concerns about sufficiency and regulatory arbitrage remain.
How does Cholesky decomposition generate correlated random variables for Monte Carlo simulation?
Cholesky decomposition converts independent random variables into correlated ones by factoring the correlation matrix into C = L x L-transpose. Multiplying independent normals by L produces correlated variables with the exact desired correlation structure.
Can someone walk through securitization from start to finish — origination, SPV, tranching, and waterfall?
Securitization transforms illiquid assets into tradable securities through a chain of origination, SPV creation for bankruptcy remoteness, tranching into different risk layers, and a strict cash flow waterfall that determines payment priority.
How do you use Greeks for risk management of an options portfolio?
Greeks-based risk management involves aggregating option sensitivities across the entire portfolio to understand and control exposure to each risk dimension. Portfolio Greeks are computed by summing position-level Greeks, and banks set limits on each to control directional, convexity, volatility, and time decay risks.
How do financial institutions measure and manage cyber risk, and why is it so hard to quantify?
Cyber risk is uniquely challenging to quantify because of limited loss data, extreme severity distributions, rapidly evolving threats, and systemic interconnections. Financial institutions use scenario analysis, factor-based models, and frameworks like FAIR to estimate losses, while managing risk through the identify-protect-detect-respond-recover cycle.
What are the standards for collecting internal operational loss data?
Internal Loss Data (ILD) collection is the foundational element of operational risk management. Basel and national regulators specify minimum standards while banks add enhancements...
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