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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...
What drives funding risk in a defined benefit pension plan?
Funded ratio moves with asset returns, liability discount changes, and actuarial experience — driving sponsor contribution volatility.
What is the regulatory PD floor and how does it affect bank capital?
Basel III final imposes 0.03% PD floor for most IRB portfolios. Prevents model uncertainty and level-plays with standardized. Hartwell's AAA modeled at 0.012% gets floored, raising RWA 60%...
What are the Basel Accords, and how do Basel I, II, and III differ in their approach to bank capital requirements?
The Basel Accords evolved from simple risk-weight categories (Basel I) to a three-pillar framework with internal models (Basel II) to post-crisis reforms with higher capital quality, liquidity requirements, and countercyclical buffers (Basel III). Each iteration addressed shortcomings revealed by financial crises.
How should digital assets like cryptocurrencies be evaluated as an alternative investment class?
Digital assets don't fit neatly into traditional categories. Institutional evaluation focuses on their diversification benefit, extreme volatility requiring small allocations, and unique valuation challenges since traditional DCF doesn't apply to most crypto assets.
How do AIC and BIC help with model selection, and why can't I just use R-squared?
R-squared always increases with more variables, rewarding overfitting. AIC and BIC add penalty terms for model complexity — AIC penalizes moderately for better predictions, BIC penalizes heavily for a more parsimonious model.
How do you value a target company in an M&A transaction? What are the right multiples to use?
M&A valuation uses three primary methods: comparable company analysis, comparable transaction analysis, and DCF. Practitioners triangulate across all three and explicitly model synergies, applying probability-weighted achievement rates.
How do you trade volatility directly? I keep hearing about straddles and the 'vol surface' but need clarity.
Volatility trading means profiting from changes in implied volatility or from realized volatility differing from what the market expects, regardless of direction. Core strategies include straddles, strangles, and skew trades.
YTM vs. current yield — what's the actual difference and when does each matter?
Great question — these two yield measures serve different purposes and confusing them is a common exam trap. Current yield captures only income, while YTM is the total return measure including capital gain/loss and reinvestment income.
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