Builds and stress-tests market-risk models. Verified strongest on risk judgment under changing assumptions.
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Mid-review, the assumption changed: “Your VaR holds at 99% on normal returns. Now a correlated shock hits two desks at once and the tails fatten. What breaks first, and what do you change before the next run?”
“The Gaussian VaR understates it first — joint tail risk, not single-name. I’d stop trusting the parametric number and switch the breaching desks to a filtered historical simulation over the stressed window, then re-estimate the correlation off that window, not the trailing year. I’d flag the hedge ratios as stale until the new covariance lands, because hedging on pre-shock betas is worse than not hedging.”
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