Rolling Statistics and Regression Functions for Quantitative Research

Summary

This platform update describes additions to an expression engine for quantitative analysis. The new rolling functions calculate sums, means, standard deviations, variances, skewness, and kurtosis over a specified lookback while handling missing values. It also introduces rolling regression outputs: residuals, coefficients, and intercepts, with the possibility of using multiple explanatory series. These functions can support feature construction, statistical analysis, and regression-based research workflows.

The notice also records a correction to the inputs for a Williams %R function, plus file-reading and sorting-module updates. It mentions a new commodity futures long-short strategy based on momentum, but provides no strategy rules, portfolio construction details, or performance results. The material is a feature announcement rather than a research study: it defines available capabilities but does not explain implementation conventions, missing-value behavior in detail, or validate any trading signal built with them.

Key ideas

• The update adds rolling descriptive statistics that accommodate missing observations.
• Rolling regression functions return residuals, coefficients, and intercepts and can accept multiple predictors.
• The Williams %R function's required inputs were corrected.
• A commodity futures momentum long-short strategy is mentioned without rules or performance evidence.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.