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data-cleans

This repo has code to do primary data cleaning for Compustat / Crsp from WRDS

data-driven-finance-ii-2023-722-binder

deap

Distributed Evolutionary Algorithms in Python

deep-learning-for-image-processing

deep learning for image processing including classification and object-detection etc.

deep-learning-in-asset-pricing

https://arxiv.org/abs/1805.01104

deep-learning-papers-reading-roadmap

Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!

deep_learning_asset_pricing

deeplob-deep-convolutional-neural-networks-for-limit-order-books

This jupyter notebook is used to demonstrate our recent work, "DeepLOB: Deep Convolutional Neural Networks for Limit Order Books", published in IEEE Transactions on Singal Processing. We use FI-2010 dataset and present how model architecture is constructed here. The FI-2010 is publicly avilable and interested readers can check out their paper.

demand_asset_pricing

did

Keeping track of what is going on with the latest DiD innovations.

did_codes

This repo contains the codes for Baker, Larcker, Wang - "How Much Should We Trust Staggered Difference-in-Differences Estimates?"

did_imputation

Event studies: robust and efficient estimation, testing, and plotting

did_slides

diffndiff

dlsa-public

Deep Learning Statistical Arbitrage

dlwpt-code

Code for the book Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann.

dscourses21

ECON 5253: Data Science for Economists, University of Oklahoma (Spring 2021)

dse2019

Teaching materials from DSE2019 summer school at Chicago Booth

ec240a

Course materials for Ec240a "Econometrics" at UC Berkeley.

ec607s20

Causally oriented doctoral econometrics course at UO, taught by Ed Rubin

ec708-phd-econometrics-i

TA session materials (Spring 2020)

econ220e-final-project

Final project for Econ 220E at UCSD, replicates results from Feng, Giglio, Xiu (2020) Journal of Finance in R

econ35101

Public repository for UChicago's Econ 35101 "International Macroeconomics and Trade" PhD class

econ546_2018

Course Materials for ECON546 in winter of 2018

econml

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 inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

econometrics

Econometrics lecture notes with examples using the Julia language

econometricslabs

Collection of in-class labs in R for introductory econometrics class

econtools

Econometrics and data manipulation functions.

empirical-asset-pricing

empirical-asset-pricing-a-2021

This repo contains mainly codes for homework from PhD course at INSEAD