Transparent and Efficient Financial Analysis

👑 Multivariate exploratory data analysis in Python — PCA, CA, MCA, MFA, FAMD, GPA

GPU-accelerated Factors analysis library and Backtester

多因子指数增强策略/多因子全流程实现

A Python module to perform exploratory & confirmatory factor analyses.

psychometrics package, including MIRT(multidimension item response theory), IRT(item response theory),GRM(grade response theory),CAT(computerized adaptive testing), CDM(cognitive diagnostic model), FA(factor analysis), SEM(Structural Equation Modeling) .

Fast, linear version of CorEx for covariance estimation, dimensionality reduction, and subspace clustering with very under-sampled, high-dimensional data

Scalable Ultra-Sparse Bayesian PCA

Factor Analysis Kit

Deep learning-based estimation and inference for item response theory models.

Alpha研究平台

Several examples of multivariate techniques implemented in R, Python, and SAS. Multivariate concrete dataset retrieved from https://archive.ics.uci.edu/ml/datasets/Concrete+Slump+Test. Credit to Professor I-Cheng Yeh.

The code for Generative Locally Linear Embedding (GLLE).

Sparse Bayesian Multidimensional Item Response Theory

Correspondence Analysis with python

Principle Component Analysis (PCA) with varimax rotation.

Python package for plug and play dimensionality reduction techniques and data visualization in 2D or 3D.

mirror of the MeDIL Python package for causal modeling

Python implementation of a complex-valued version of the expectation-maximization (EM) algorithm for fitting Mixture of Factor Analyzers (MFA).

Return On Invested Capital - This repository contains files that demonstrate Quantitative systematic investment strategy using Return On Invested Capital as a single factor strategy.