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FRM Updated
How does the EWMA volatility model work and how do I choose the lambda parameter?
The EWMA volatility model estimates today's variance as a weighted average of yesterday's variance and yesterday's squared return, with lambda controlling the decay rate. RiskMetrics standardized lambda at 0.94 for daily data, giving an effective window of about 17 days.
How do Eurodollar futures differ from Treasury futures when hedging interest rate exposure?
Eurodollar futures are based on the 3-month SOFR rate and hedge short-term funding costs, while Treasury bond futures deliver actual bonds and hedge longer-duration portfolios. The key distinction involves settlement mechanics, duration exposure, and convexity bias.
Under FRTB, how does a bank decide between the Standardized Approach and Internal Models Approach for market risk capital?
Under FRTB, the choice between Standardized and Internal Models Approach is made at the trading desk level. Each desk must pass regulatory approval, P&L attribution testing, and backtesting to qualify for IMA. Desks that fail any gate must use the Standardized Approach.
What is wrong-way risk in counterparty credit, and why does it make standard CVA models underestimate losses?
Wrong-way risk occurs when your exposure to a counterparty increases at the same time their credit quality deteriorates. This positive correlation means standard CVA models that assume independence between exposure and default probability will systematically underestimate losses.
How do you calculate Expected Loss from PD, LGD, and EAD, and why does each component matter separately?
Understanding the three pillars of expected loss is essential for FRM Part II credit risk. Banks estimate PD, LGD, and EAD independently because each is driven by different factors: PD reflects borrower creditworthiness, LGD depends on collateral and seniority, and EAD accounts for potential drawdowns on revolving facilities.
What is the modern university endowment asset allocation?
Modern large endowments maintain 60%+ alternatives with diversified private equity, real assets, venture, and a liquidity sleeve.
How do fat-tailed distributions differ from the normal distribution, and why does it matter for risk measurement?
Real financial returns have fat tails, meaning the normal distribution systematically underestimates extreme event probabilities. A loss that should occur once in 741 days under normal assumptions may actually happen once every 50-100 days. Understanding excess kurtosis and leptokurtic distributions is essential for accurate VaR calculation.
How do delta and gamma interact in options hedging, and why is gamma risk dangerous?
Delta measures the change in option price for a $1 move in the underlying, while gamma measures how quickly delta itself changes. Gamma risk is dangerous because short gamma positions become increasingly difficult to hedge as the underlying moves — especially near expiration when ATM gamma spikes.
How exactly do futures margin calls work, and what happens if I can't meet one?
Great question — futures margin mechanics are fundamental to FRM Part I and show up frequently on the exam. When you open a futures position, the clearinghouse requires you to post an initial margin as a performance bond. Each trading day, your position is marked to market, and a margin call occurs when your account falls below the maintenance margin level.
What constitutes a strong risk culture and how can you actually measure it?
Risk culture is the set of norms, attitudes, and behaviors within an organization that shapes how risk is identified, discussed, and acted upon. The FSB identifies four pillars: tone from the top, accountability, effective challenge, and incentive alignment.
How do banks conduct liquidity stress tests and what scenarios do they typically model?
Liquidity stress testing simulates severe but plausible funding disruptions to determine whether the bank can survive without external support. Banks typically model three scenarios: idiosyncratic stress, market-wide stress, and a combined scenario, each with different assumptions about deposit runoff, wholesale funding rollover, and asset liquidation discounts.
How does scenario analysis work for operational risk, and how do banks combine it with historical data?
Scenario analysis bridges the gap between historical loss data and the need to capitalize against catastrophic operational failures. Banks run structured expert workshops to estimate frequency and severity of plausible but severe events, then calibrate these against internal and external loss data.
Why does Basel III include a leverage ratio when we already have risk-weighted capital ratios?
The leverage ratio exists precisely because risk-weighted ratios can be gamed or miscalibrated. Before the 2008 crisis, many banks showed healthy CET1/RWA ratios while running actual leverage of 30:1 or higher by loading up on assets with low risk weights.
What is the TNFD framework, and how does nature-related financial risk extend beyond climate risk?
The TNFD framework addresses nature-related financial risks beyond climate, including biodiversity loss, ecosystem degradation, and resource depletion. Using the LEAP approach, organizations map nature interfaces, assess dependencies and impacts, and prepare disclosures across governance, strategy, risk management, and metrics.
What is incremental VaR, and how does it differ from marginal VaR when sizing a discrete new trade?
Incremental VaR measures the exact change in portfolio VaR from adding a discrete trade, calculated as VaR(portfolio + trade) minus VaR(portfolio). Unlike marginal VaR, which is a local derivative approximation, incremental VaR captures the full nonlinear impact of realistic position sizes.
How does the CCP loss allocation waterfall work when a clearing member defaults, and what happens if losses exceed the default fund?
The CCP loss allocation waterfall absorbs losses sequentially: first the defaulter's margin and default fund contribution, then the CCP's own equity, then non-defaulting members' contributions, then assessment powers. If all layers are exhausted, the CCP may haircut variation margin gains or tear up contracts.
What is TVA (Total Valuation Adjustment), and how does a dealer aggregate all XVA components into a single pricing framework?
TVA aggregates all XVA components (CVA, DVA, FVA, MVA, KVA, ColVA) into a single pricing adjustment. The all-in derivative price equals the risk-free mid-market value minus TVA, but aggregation requires unified simulation to capture correlations and avoid double-counting.
Why do Eurodollar futures rates need a convexity adjustment when used to build a forward rate curve, and how is it calculated?
Eurodollar futures rates exceed true forward rates because daily margining creates a correlation between P&L and reinvestment rates that favors the short. The convexity adjustment, approximately 0.5 x sigma-squared x T1 x T2, corrects this bias and grows quadratically with maturity.
How do you construct a cross-hedge using T-note futures for a corporate bond portfolio, and what are the main sources of basis risk?
Cross-hedging corporate bonds with T-note futures requires a yield beta adjustment because corporate yields move more (or less) than Treasuries. The beta-adjusted hedge ratio captures the historical relationship, but residual basis risk from credit spread changes remains unhedgeable with Treasuries alone.
What are the key terms in a Credit Support Annex (CSA), and how do they shape the collateral exchange process between derivatives counterparties?
The CSA defines threshold (exposure level before collateral is required), minimum transfer amount, eligible collateral types, haircuts, and valuation frequency. These parameters collectively determine when margin calls are triggered and how much collateral must be exchanged.
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