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docs(notebooks): stochastic volatility port - #49
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…red NUTS, checked by a particle filter
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PyMC's stochastic volatility model on the last 300 days of its S&P 500 data (MIT, vendored as notebooks/data/sp500.csv). The path is written non-centred (z_t ~ N(0,1), v_t = v_(t−1) + step·z_t): the centred version funnelled NUTS (step R-hat 1.11, ESS 28); non-centred gives R-hat ≈ 1.01, ESS ≈ 440 for the step. Hand-written gradient (incl. digamma for ν), checked against finite differences. Cross-check: on the last day smoothing = filtering, and a particle filter (1000 particles, same model with sites, parameters at their posterior means) agrees with NUTS (0.00261 ± 0.00108 vs 0.00259 ± 0.00111). Adds ~3.5 min to the render.