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asgl

A regression solver for linear and quantile regression models and lasso based penalizations'

atom

:atom: The hackable text editor

awesome-machine-learning

A curated list of awesome Machine Learning frameworks, libraries and software.

barra_cne6

Barra CNE6 因子构建

barra_risk

A risk evaluation program that follows BARRA's CNE6 and USE4 risk model to predict the risk and distribution of factors in a portfolio. Created by Rosemary He Sept. 2019, under Zhiqiang Zhang.

brinson-attribution

以wind为数据源的基金单期brinson业绩归因

central-bank-nlp

Resources for using NLP on central bank communications

centralbanking-nlp

In this repository, I will apply NLP techniques to central banks speeches.

cvxpy

A Python-embedded modeling language for convex optimization problems.

deep-learning-with-python-notebooks

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

empca

Principal Component Analysis (PCA) for Missing and/or Noisy Data

feature-importance-neural-networks

Variance-based Feature Importance in Neural Networks

featureimportancedl

flow-forecast

Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).

handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

handson-ml3

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

hmmlearn

Hidden Markov Models in Python, with scikit-learn like API

home-credit-default-risk

LightGBM, XGboost, Random Forest, Stacking, Feature Selection (PCA, correlation, feature importance)

impyute

Data imputations library to preprocess datasets with missing data

latex-templates

TeX templates for academic journal, presentation, problem set, and cheat sheet

meta-weight-net

NeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting (Pytorch implementation for noisy labels).

meta-weight-net_code-optimization

A new code framework that uses pytorch to implement meta-learning, and takes Meta-Weight-Net as an example.

pricing-convertible-bonds-

project_europa

A final project to research the European Central bank's green economy supports by using NLP

qlib

Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technologies in quantitative investment. With Qlib, you can easily try your ideas to create better Quant investment strategies. An increasing number of SOTA Quant research works/papers are released in Qlib.

randomforestfeatureselection

A modification in the traditional random forest feature selection method which uses less memory usually for instances where dataset is not loadable in the memory.

replicationcrisis

Code for "Is There a Replication Crisis in Finance" by Jensen, Kelly and Pedersen (2022)

research_public

Quantitative research and educational materials

scalecast

The practitioner's forecasting library

seqlearn

Sequence learning toolkit for Python