📈This repo contains detailed notes and multiple projects implemented in Python related to AI and Finance. Follow the blog here: https://purvasingh.medium.com

Portfolio Construction Functions under the Basic Mean_Variance Model, the Factor Model and the Black_Litterman Model.

R package for fitting high-dimensional multivariate linear mixed effect models

Implements different approaches to tactical and strategic asset allocation

Work with trained factor models in Python

DRIP Asset Allocation is a collection of model libraries for MPT framework, Black Litterman Strategy Incorporator, Holdings Constraint, and Transaction Costs.

Repository for the AugmentedPCA Python package.

Implementation of the FNETS methodology proposed in Barigozzi, Cho and Owens (2024) for network estimation and forecasting of high-dimensional time series

ESG investment portfolio system

Julia package for simulating and estimating multi-level/hierarchical dynamic factor models (HDFMs).

An R package for Factor Model Asset Pricing

R codes and dataset for the estimation of the high-dimensional state space model proposed in the paper "A dynamic factor model approach to incorporate Big Data in state space models for official statistics" with Franz Palm, Stephan Smeekes and Jan van den Brakel.

A repo to explore quantitative finance models, libraries and tooling.

A toolkit for asset pricing research

Code for implementing Factor Analysis with BLEssing of dimensionality (FABLE).

Jupyter notebooks implementing Finance projects

Estimation and inference for factor models in Asset Pricing.

Estimating CAPM Betas of an equally weighted portfolio of Apple and Google from 2016 to 2021

Penalized regression for multiple types of many features with missing data using expectation-maximization (EM) algorithm.

This is the code for our publication Inferring Latent States in a Network Influenced by Neighbor Activities: An Undirected Generative Approach, IEEE International Conference on Acoustics, Speech and Signal Processing, New Orleans, LA, 2017