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FRM Part II Updated
How does an Expected Shortfall constraint work in portfolio optimization?
An Expected Shortfall constraint limits the average loss in the selected tail of the scenario loss distribution...
What is the intuition behind expectiles as a risk measure?
Expectiles act like asymmetric means, using heavier penalties on one side of the distribution to capture tail severity...
Is overlapping data a problem in VaR backtesting?
Overlapping calibration windows are normal, but overlapping realized loss horizons can distort VaR backtest inference...
How does a copula help calculate portfolio VaR?
A copula models dependence between risk drivers, then portfolio VaR is read from the aggregated loss distribution...
What should a VaR framework actually do if a pricing library already exists?
A pricing library values instruments, while a VaR framework manages scenarios, mapping, aggregation, reporting, and controls...
Should a portfolio construction process use VaR, CVaR, or variance as its risk measure?
VaR, CVaR, and variance answer different risk questions, so the right choice depends on portfolio shape and investor preferences...
Why is VaR or CVaR on high-frequency returns tricky?
High-frequency VaR can be distorted by microstructure noise, tick effects, liquidity, and dependence between observations...
What does the Kupiec proportion-of-failures test check in VaR backtesting?
The Kupiec test checks whether the total VaR exception count matches the expected breach rate for the confidence level...
What makes CDS spread scenarios harder than ordinary equity return scenarios?
CDS spread scenarios are hard because credit data can be sparse, sticky, and heavily affected by changing issuer fundamentals...
Should VaR for a portfolio of funds use look-through holdings or fund-level returns?
Fund-level VaR captures realized fund behavior, while look-through VaR captures current underlying exposure when data is reliable...
Can Extreme Value Theory be used for a portfolio that contains options?
EVT can be used with option portfolios, but the tail model must respect nonlinear risk drivers and revaluation...
What are the main approaches to stress testing a portfolio?
Stress testing explores severe but plausible scenarios through historical replays, factor shocks, and reverse stress tests...
Why is CVaR usually easier than VaR to use in portfolio optimization?
CVaR is often easier to optimize because it averages tail losses instead of focusing only on a cutoff quantile...
What are good examples of non-financial risk and contingency planning in a trading or risk function?
Non-financial risk becomes concrete when you connect system or process failures to fallback actions and ownership...
Is risk parity just inverse-vol weighting, or is there more to it?
Inverse-vol weights can approximate risk parity, but real parity comes from equal risk contributions under covariance...
How do I size a liquidity buffer for a strategy that is short gamma and short vega?
A liquidity buffer for short gamma and vega should be sized from stressed paths, not calm-day averages...
How can climate change risk be translated into something measurable for a portfolio?
Climate risk becomes measurable when you convert it into familiar financial channels and then stress those channels with scenarios...
How do macro funds think about risk when positions span rates, FX, equities, and credit at the same time?
Macro funds often manage risk through factors and scenarios because different trades can load on the same macro theme...
How do you apply risk management to an ML trading system without completely overriding it?
ML trading systems need layered risk controls that define a safe operating space without replacing the signal engine itself...
How should I think about cross-sectional versus time-series factor models?
Time-series factor models estimate asset loadings over time, while cross-sectional models infer factor returns across assets at a point in time...
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