workflow.run_evt_tail_risk

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Extreme Value Theory tail risk (Peaks-Over-Threshold): fits a Generalized Pareto Distribution to the losses beyond a high threshold via Grimshaw's (1993) profile-likelihood MLE, then extrapolates VaR/Expected Shortfall at the requested confidence, without assuming a normal distribution. Use when user asks "what's my tail VaR without assuming normality?" or "how fat is my loss tail, really?". Complements workflow.run_var_cvar (parametric, normal-distribution VaR/CVaR) for exactly the fat-tailed-return case that assumption understates. threshold_percentile (default 90) sets which percentile of the loss distribution (losses = -returns) becomes the threshold u; confidence must be deep enough into the fitted tail (1-confidence < the threshold's own exceedance rate) or the call throws. Returns: threshold, n_exceedances, exceedance_rate, xi (GPD shape: 0=exponential tail, >0=heavy/fat tail, <0=bounded tail; values <= -1 are excluded from the fit domain as a known non-regular/unbounded-likelihood case, Smith 1985), beta (GPD scale), xi_asymptotically_normal (false when xi<=-0.5: the fit is still valid but the usual MLE confidence-interval theory doesn't apply, per that same Smith 1985 result), var, es (null when xi>=1, where Expected Shortfall is mathematically undefined).