Investment Research for Everyone, Everywhere.

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AKShare is an elegant and simple financial data interface library for Python, built for human beings! 开源财经数据接口库

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal …

Transparent and Efficient Financial Analysis

A collaboratively curated list of awesome Open-Source Intelligence (OSINT) Resources

A curated collection of links for economists

Notebooks for financial economics. Keywords: Jupyter notebook pandas Federal Reserve FRED Ferbus GDP CPI PCE inflation unemployment wage income debt Case-Shiller housing asset portfolio equities SPX bonds TIPS rates currency FX euro EUR USD JPY yen XAU gold Brent WTI oil Holt-Winters time-series forecasting statistics econometrics

Solve and estimate Dynamic Stochastic General Equilibrium models (including the New York Fed DSGE)

This repository hosts the code behind the online book, Coding for Economists.

Replication of tables and figures from "Mostly Harmless Econometrics" in Stata, R, Python and Julia.

Sharing Updatable Models (SUM) on Blockchain

Heterogenous Agents Resources & toolKit

张俊的读书笔记

Tutorials of econometrics featuring Python programming. This is a crash course for reviewing the most important concepts and techniques of basic econometrics, the theories are presented lightly without hustles of derivation and Python codes are straightforward.

GCAM -- The Global Change Analysis Model

A collection of methods for solving Finance/Accounting equations, implemented in C#.

Online research made easy

The only open-source toolkit that can download EDGAR financial reports and extract textual data from specific item sections into nice and clean JSON files.

Fast Estimation of Linear Models with IV and High Dimensional Categorical Variables