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Why is time-scaling Cornish-Fisher VaR more delicate than scaling normal VaR?
Cornish-Fisher VaR is harder to scale because skewness and kurtosis do not behave like volatility under naive time scaling...
What is the simplest way to remember VaR and CVaR formulas across distributions?
VaR is a distribution quantile, while CVaR is the average loss beyond that quantile under the chosen tail convention...
What common mistakes show up in a Monte Carlo VaR implementation?
Monte Carlo VaR can fail through inconsistent returns, bad dependence inputs, and weak portfolio revaluation...
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...
What are the core steps in a Monte Carlo VaR calculation?
Monte Carlo VaR builds a loss distribution by simulating scenarios, revaluing the portfolio, and reading a tail percentile...
When estimating tail risk, should I fit the whole return distribution or only the tail?
Tail risk estimation balances stable full-sample fitting against focused but noisier tail-only modeling...
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...
How do historical, variance-covariance, and Monte Carlo VaR differ?
The three VaR methods differ by how they build the loss distribution: history, assumptions, or simulation...
Can I annualize Expected Shortfall with square-root-of-time the same way I annualize volatility?
Expected Shortfall does not scale as cleanly as volatility, so annualization depends heavily on distribution assumptions...
Why do desks still use Black-Scholes greeks for risk management when better models exist?
Black-Scholes greeks remain popular because they are a common operational risk language even when richer models are used elsewhere...
What is the intuition behind spectral risk measures, and why does Expected Shortfall fit in that family?
Spectral risk measures work by assigning weights to tail quantiles, and Expected Shortfall is one important member of that family...
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 should I think about modelling instruments when interest rates can be negative?
Negative rates matter because they break hidden positivity assumptions in many familiar pricing models...
How do I quantify unsystematic risk instead of just saying it gets diversified away?
Unsystematic risk is often measured through the residual variance left after factor or market exposure has been explained...
Why is VaR for two dependent lognormal exposures harder than adding the individual VaRs?
Portfolio VaR must come from the tail of the combined loss distribution, not from adding stand-alone VaRs...
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...
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