data segmentation and forecasting for VAR-driven factor models
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Updated
Jul 3, 2023 - R
data segmentation and forecasting for VAR-driven factor models
This is a tentative pytorch implementation of the paper "Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders"
Factor Modeling
Package to build universes for factor pricing model
This thesis investigates the relationship between employee sentiment, proxied by Glassdoor reviews and ratings, and excessive returns on corresponding bonds. While sentiment analysis is well studied for probing into how companies are perceived by investors or the general public, it is a novel idea to exploit sentiment of employees, which enables…
Replication Study on Idiosyncratic Momentum Strategy
Data Science Project: Replication of "Forest Through the Trees: Building Cross-Sections of Stock Returns" - creation of assets to test validity of factor models with Python
Regularized estimation of high-dimensional FAVAR models
Repository for the AugmentedPCA Python package.
Unsupervised learning coupled with applied factor analysis to the five-factor model (FFM), a taxonomy for personality traits used to describe the human personality and psyche, via descriptors of common language and not on neuropsychological experiments. Used kmeans clustering and feature scaling (min-max normalization).
This repository shows the application of PCA technique for risk factor modelling of financial securities.
Package to build risk model for factor pricing model
Covariance Matrix Estimation via Factor Models
Attribution and optimisation using a multi-factor equity risk model.
PyTorch implementation of FactorVAE
Build a statistical risk model using PCA. Optimize the portfolio using the risk model and factors using multiple optimization formulations.
A curated list of awesome algorithmic trading frameworks, libraries, software and resources
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