Option pricing using time series models as market price of risk
https://thierrymoudiki.github.io/blog/2026/02/01/r/Semi-parametric-MarketPriceofRisk-Theta
@teeeeeeeee.bsky.social
@teeeeeeeee.bsky.socialOption pricing using time series models as market price of risk
https://thierrymoudiki.github.io/blog/2026/02/01/r/Semi-parametric-MarketPriceofRisk-Theta
@teeeeeeeee.bsky.social`crossvalidation` and random search for calibrating support vector machines
https://thierrymoudiki.github.io/blog/2021/08/06/r/crossvalidation-svm-r
@teeeeeeeee.bsky.socialahead forecasting (v0.10.0): fast time series model calibration and Python plots
https://thierrymoudiki.github.io/blog/2024/02/26/python/r/julia/ahead-v0100
@teeeeeeeee.bsky.socialProgramming language-agnostic reserving using RidgeCV, LightGBM, XGBoost, and ExtraTrees Machine Learning models
https://thierrymoudiki.github.io/blog/2025/06/13/r/techtonique/mlreserving
@teeeeeeeee.bsky.socialR package development workflow (assuming you're using macOS or Linux)
https://thierrymoudiki.github.io/blog/2024/08/27/r/makefile-r-pkg
@teeeeeeeee.bsky.socialmlsauce's `v0.13.0`: taking into account inputs heterogeneity through clustering
https://thierrymoudiki.github.io/blog/2024/04/21/python/lsboost-clustering
@teeeeeeeee.bsky.socialGradient-Boosting and Boostrap aggregating anything (alert: high performance): Part5, easier install and Rust backend
https://thierrymoudiki.github.io/blog/2025/01/27/python/r/genbooster-rust
@teeeeeeeee.bsky.socialForecasting uncertainty: sequential split conformal prediction + Block bootstrap (web app)
https://thierrymoudiki.github.io/blog/2024/07/22/python/r/scp-bootstrap
@teeeeeeeee.bsky.socialOverfitting and scaling (on GPU T4) tests on nnetsauce.CustomRegressor
https://thierrymoudiki.github.io/blog/2026/01/29/python/Overfitting-CustomRegressor
@teeeeeeeee.bsky.social
@teeeeeeeee.bsky.socialJulia packaging at the command line
https://thierrymoudiki.github.io/blog/2023/12/04/julia/misc/julia-pkging
@teeeeeeeee.bsky.socialExtending the Theta forecasting method to GLMs, GAMs, GLMBOOST and attention: benchmarking on Tourism, M1, M3 and M4 competition data sets (28000 series)
https://thierrymoudiki.github.io/blog/2025/04/14/r/theta-M1-M3-M4
@teeeeeeeee.bsky.social
@teeeeeeeee.bsky.socialCalling =TECHTO_SURVIVAL for Survival Analysis in Excel is just a matter of copying and pasting
https://thierrymoudiki.github.io/blog/2025/07/04/r/python/techto-survival
@teeeeeeeee.bsky.socialA lightweight interface to scikit-learn in R Pt.2: probabilistic time series forecasting in conjunction with ahead::dynrmf
https://thierrymoudiki.github.io/blog/2025/04/20/r/tisthemachinelearner-time-series
@teeeeeeeee.bsky.socialA glimpse into my PhD journey
https://thierrymoudiki.github.io/blog/2020/10/23/misc/my-phd-journey
@teeeeeeeee.bsky.socialGradient-Boosting anything (alert: high performance): Part4, Time series forecasting
https://thierrymoudiki.github.io/blog/2024/11/10/python/r/quasirandomizednn/genboosting-mts
@teeeeeeeee.bsky.socialProbabilistic Time Series Forecasting (predictive simulations) in Microsoft Excel using Python, xlwings lite and www.techtonique.net
https://thierrymoudiki.github.io/blog/2025/03/28/python/xlwings-lite-techtonique
@teeeeeeeee.bsky.socialProbabilistic Machine Learning (for longitudinal data) Reserving (work in progress)
https://thierrymoudiki.github.io/blog/2025/06/04/python/ml-reserve
@teeeeeeeee.bsky.socialModel calibration with `crossval`
https://thierrymoudiki.github.io/blog/2019/10/04/r/crossval-1
