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FRM Part I Updated
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.
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.
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.
How does the Three Lines of Defense model work in risk management?
The Three Lines of Defense (3LoD) is the dominant governance model for organizing risk management responsibilities. The first line (business units) owns risks, the second line (risk management and compliance) provides oversight, and the third line (internal audit) provides independent assurance.
How do you decompose portfolio VaR by risk factor using a multi-factor model?
Factor-based VaR decomposition attributes portfolio risk to underlying systematic risk factors like equity, interest rates, and credit spreads. Using multi-factor models, each factor's contribution to total VaR is computed through the factor loading and covariance structure.
How was the ISDA fallback spread adjustment calculated when LIBOR ceased, and why was a spread needed at all?
The ISDA fallback spread adjustment compensates for the structural difference between LIBOR (unsecured term rate) and SOFR (secured overnight rate). It was calculated as the 5-year historical median of the daily LIBOR-SOFR spread, fixed as of March 5, 2021.
How does a quanto option eliminate currency risk, and what adjustment is made to the drift rate in pricing?
A quanto option eliminates currency risk by fixing the exchange rate at inception. Pricing requires a drift adjustment — reducing the foreign asset's drift by rho x sigma_S x sigma_X — which accounts for the correlation between the asset and the exchange rate.
What is a spark spread, how is it calculated, and why is it important for power generation risk management?
The spark spread measures the gross profit margin for a gas-fired power plant by comparing electricity revenue to gas fuel cost. It equals the electricity price minus the product of the plant's heat rate and the gas price.
How does seasonality in natural gas create predictable patterns in the futures curve, and what risks does this create for hedgers?
Natural gas is one of the most seasonal commodity markets due to heating demand in winter and relatively steady production. The futures curve typically shows winter premiums reflecting storage economics, and the spread must cover storage, financing, and operational costs.
How do you use DV01 to hedge interest rate risk with swaps?
DV01 (Dollar Value of a Basis Point) measures how much the value of a position changes when interest rates shift by 1 basis point. For hedging with interest rate swaps, the goal is to match the DV01 of your exposure with the DV01 of the swap so that the combined position has near-zero rate sensitivity.
What is the difference between the premium leg and the protection leg of a CDS, and how do they determine the CDS spread?
A credit default swap has two legs, and understanding both is essential for FRM Part I credit risk questions. The premium leg is paid by the protection buyer as periodic spread payments, while the protection leg is the contingent payout on default.
What is kernel density estimation and when should I use it instead of assuming a parametric distribution for risk modeling?
Kernel density estimation (KDE) is a non-parametric technique that estimates the probability density function by placing a smooth kernel at each observed data point and summing them. Unlike parametric methods, KDE lets the data determine the distribution shape.
How do catastrophe bonds work, and what are the different trigger types investors need to understand?
Catastrophe bonds (cat bonds) are insurance-linked securities that transfer catastrophic event risk from an insurer or reinsurer to capital market investors. If a qualifying catastrophe occurs, investors lose some or all of their principal, which goes to the sponsor to cover losses.
What is maximum likelihood estimation (MLE) and how is it used in risk modeling?
Maximum Likelihood Estimation (MLE) finds parameter values that maximize the probability of observing the actual data. Unlike OLS which minimizes squared errors, MLE works by maximizing a likelihood function under a distributional assumption.
How do conversion factors work in Treasury bond futures, and why does the cheapest-to-deliver bond matter so much?
Treasury bond futures are unique because the short side can deliver any eligible bond (maturity 15+ years) against the contract. Since bonds have different coupons and maturities, the exchange uses conversion factors (CF) to normalize them.
How does Bayesian estimation work and how is it used in risk management?
Bayesian estimation updates a prior belief about a parameter with observed data to produce a posterior distribution: Posterior ∝ Likelihood × Prior. It is especially valuable in risk management when data is limited (low-default portfolios) or expert judgment is available.
How do weather derivatives work and who uses them?
Weather derivatives have payoffs tied to measurable weather variables like temperature (HDD/CDD). Energy companies, agriculture, and retailers use them to hedge revenue sensitivity to weather. They settle based on official weather station data with no physical delivery.
How does Extreme Value Theory (POT method) improve VaR estimation in the tails?
Extreme Value Theory's Peaks-Over-Threshold method fits a Generalized Pareto Distribution to losses exceeding a high threshold, providing much more accurate tail risk estimates than the normal distribution. For 99% VaR, EVT typically produces estimates 20-40% higher.
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