56,966 blogs · [ { "id": "01a0d468-925b-73b6-be0f-ecfad04c24af", "title": "Python version of Semi-parametric option pricing based on underlying’s historical data (accepted at the osQF 2026 (ex R/Finance) conference)", "url": "https://thierrymoudiki.github.io/blog/2026/09/21/python/empirical-pricing", "published_at": "2026-09-21T00:00:00+00:00" }, { "id": "01a0d468-925b-73b6-be0f-ecfad0c14ff2", "title": "Semi-parametric option pricing based on underlying’s historical data (accepted at the osQF 2026 (ex R/Finance) conference)", "url": "https://thierrymoudiki.github.io/blog/2026/09/20/r/semi-parametric-pricing-osqf", "published_at": "2026-09-20T00:00:00+00:00" }, { "id": "01a0d468-925b-73b6-be0f-ecfad1b1788b", "title": "Model-agnostic prediction intervals in Python and R: does nnetsauce’s QuantileRegressor hold up?", "url": "https://thierrymoudiki.github.io/blog/2026/09/14/r/python/quantileregressor-benchmark", "published_at": "2026-09-14T00:00:00+00:00" }, { "id": "01a08c54-5714-736f-b5d8-fbc91c24068c", "title": "ahead (Time Series Forecasting with uncertainty quantification) gets a lot faster to install: most dependencies are now optional", "url": "https://thierrymoudiki.github.io/blog/2026/09/08/r/python/ahead-light", "published_at": "2026-09-08T00:00:00+00:00" }, { "id": "01a08c54-5714-736f-b5d8-fbc91cb682db", "title": "Skip the R/Python runtime: fast tabular dashboards with Observable Framework", "url": "https://thierrymoudiki.github.io/blog/2026/08/31/python/r/javascript/observable-framework", "published_at": "2026-08-31T00:00:00+00:00" }, { "id": "01a08c54-5714-736f-b5d8-fbc91d6807b4", "title": "PCARVFL vs CTGAN for synthetic tabular data generation on an insurance pricing dataset", "url": "https://thierrymoudiki.github.io/blog/2026/08/22/python/pcarvfl-vs-ctgan-insurance", "published_at": "2026-08-22T00:00:00+00:00" }, { "id": "01a08c54-5714-736f-b5d8-fbc91e59ebe1", "title": "‘Zero-Shot Probabilistic Stock Returns Forecasting with Pretrained RVFL Networks’ accepted at COPA 2026 (and to appear in the Proceedings of Machine Learning Research)", "url": "https://thierrymoudiki.github.io/blog/2026/08/15/r/metalearned-ridge2f", "published_at": "2026-08-15T00:00:00+00:00" }, { "id": "01a08c54-5714-736f-b5d8-fbc91f3406b3", "title": "‘PCARVFLSimulator’: a GAN-like tabular data synthesizer built from PCA scores, a Random Vector Functional-Link network, and residuals bootstrapping", "url": "https://thierrymoudiki.github.io/blog/2026/08/10/python/PCARVLsimulator", "published_at": "2026-08-10T00:00:00+00:00" }, { "id": "01a08c54-5714-736f-b5d8-fbc91f3b9717", "title": "‘garchf’: GARCH probabilistic forecasting with package ‘forecast’-style interface (and ‘rugarch’ under the hood)", "url": "https://thierrymoudiki.github.io/blog/2026/08/01/r/xgarchf", "published_at": "2026-08-01T00:00:00+00:00" }, { "id": "01a08c54-5714-736f-b5d8-fbc91f76bb46", "title": "GPopt for R: Bayesian and conformal optimization of black-box functions and hyperparameter tuning", "url": "https://thierrymoudiki.github.io/blog/2026/07/26/r/GPopt", "published_at": "2026-07-26T00:00:00+00:00" }, { "id": "01a08c54-5714-736f-b5d8-fbc91fcddad9", "title": "My last R posts: How conformalization helps weak models, fast conformal prediction with jackknife+ (and no refitting), and sklearn in R", "url": "https://thierrymoudiki.github.io/blog/2026/07/13/r/my-last-R-posts", "published_at": "2026-07-13T00:00:00+00:00" }, { "id": "01a08c54-5714-736f-b5d8-fbc91ff4d6cb", "title": "Natively Interpretable Boosting", "url": "https://thierrymoudiki.github.io/blog/2026/07/12/python/Natively-Interpretable-Boosting", "published_at": "2026-07-12T00:00:00+00:00" }, { "id": "01a08c54-5714-736f-b5d8-fbc920c84771", "title": "Fast conformal prediction (no refitting) for some Machine Learning models via closed-form jackknife plus", "url": "https://thierrymoudiki.github.io/blog/2026/06/27/r/python/jackknife-plus-smoothers", "published_at": "2026-06-27T00:00:00+00:00" } ] posts Claim your blog

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2026

Python version of Semi-parametric option pricing based on underlying’s historical data (accepted at the osQF 2026 (ex R/Finance) conference)original ↗

21 Sept 2026

Semi-parametric option pricing based on underlying’s historical data (accepted at the osQF 2026 (ex R/Finance) conference)original ↗

20 Sept 2026

Model-agnostic prediction intervals in Python and R: does nnetsauce’s QuantileRegressor hold up?original ↗

14 Sept 2026

ahead (Time Series Forecasting with uncertainty quantification) gets a lot faster to install: most dependencies are now optional original ↗

8 Sept 2026

Skip the R/Python runtime: fast tabular dashboards with Observable Framework original ↗

31 Aug 2026

PCARVFL vs CTGAN for synthetic tabular data generation on an insurance pricing dataset original ↗

22 Aug 2026

‘Zero-Shot Probabilistic Stock Returns Forecasting with Pretrained RVFL Networks’ accepted at COPA 2026 (and to appear in the Proceedings of Machine Learning Research)original ↗

15 Aug 2026

‘PCARVFLSimulator’: a GAN-like tabular data synthesizer built from PCA scores, a Random Vector Functional-Link network, and residuals bootstrapping original ↗

10 Aug 2026

‘garchf’: GARCH probabilistic forecasting with package ‘forecast’-style interface (and ‘rugarch’ under the hood)original ↗

1 Aug 2026

GPopt for R: Bayesian and conformal optimization of black-box functions and hyperparameter tuning original ↗

26 Jul 2026

My last R posts: How conformalization helps weak models, fast conformal prediction with jackknife+ (and no refitting), and sklearn in R original ↗

13 Jul 2026

Natively Interpretable Boosting original ↗

12 Jul 2026

Fast conformal prediction (no refitting) for some Machine Learning models via closed-form jackknife plus original ↗

27 Jun 2026