Pinned Repositories
10K-MDA-Section
Extract the Management Discussion and Analyses (MD&A) section from 10K Financial Statements
analyst-forecast-errors
A new approach to predicting analyst forecast errors: Do investors overweight analyst forecasts?https://www.sciencedirect.com/science/article/pii/S0304405X13000329
anlp19
Course repo for Applied Natural Language Processing (Spring 2019)
CF-Paper-replication
Replication of Philippon and Guitierrez (2017), “Investment less Growth: An Empirical Investigation”
CHIIA
COMP8715 Group Project: CHIIA-NLP project is to identify the relevant data for CHIIA database by using natural language processing and machine learning models which calculate the likelihood between the data extracted from Factiva and the relevant datasets. Our project will automatically search for the most obvious relevant data, and save them to CHIIA database.
coblog
how co-attention affect beta
codechella
Data, Code and other material for CodeChella concert
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.
Empirical-Method-in-Finance
Winter 2020 Course description: Econometric and statistical techniques commonly used in quantitative finance. Use of estimation application software in exercises to estimate volatility, correlations, stability, regressions, and statistical inference using financial time series. Topic 1: Time series properties of stock market returns and prices Class intro: Forecasting and Finance The random walk hypothesis Stationarity Time-varying volatility and General Least Squares Robust standard errors and OLS Topic 2: Time-dependence and predictability ARMA models The likelihood function, exact and conditional likelihood estimation Predictive regressions, autocorrelation robust standard errors The Campbell-Shiller decomposition Present value restrictions Multivariate analysis: Vector Autoregression (VAR) models, the Kalman Filter Topic 3: Heteroscedasticity Time-varying volatility in the data Realized Variance ARCH and GARCH models, application to Value-at-Risk Topic 4: Time series properties of the cross-section of stock returns Single- and multifactor models Economic factors: Models and data exploration Statistical factors: Principal Components Analysis Fama-MacBeth regressions and characteristics-based factors
sec-edgar
Download all companies periodic reports, filings and forms from EDGAR database.
DijunLiu1995's Repositories
DijunLiu1995/10K-MDA-Section
Extract the Management Discussion and Analyses (MD&A) section from 10K Financial Statements
DijunLiu1995/Factiva_sentiment_analysis
Program for analyzing the tone of news messages for a course project
DijunLiu1995/MD-A-10-K-data
MD&A sections from 10-Ks; 2002-2018
DijunLiu1995/factiva-pipelines-python
Python package to read, transform, enrich and load news data. Patterns can be found in the Dow Jones Developer Portal.
DijunLiu1995/factiva-pypckgs-sample
Jupyter notebooks that guide through the use of the Factiva Python packages.
DijunLiu1995/sas-1
A collection of SAS Macros that I use and update regularly.
DijunLiu1995/Python-tutorials_timeseries_for_finance
Python modules for time-series analysis and empirical asset pricing.
DijunLiu1995/famafrench
Python package designed to construct and replicate datasets from Ken French's online library by accessing WRDS remotely through its cloud server "wrds-cloud".
DijunLiu1995/Python-tutorials_remote_data_access
Resources for connecting remotely to various economic and financial data libraries.
DijunLiu1995/CSR_Earnings
CSR and Earnings
DijunLiu1995/value_investing_research
Compilation of CRSP Database and IBES using R
DijunLiu1995/rstats-ed
List of courses teaching R
DijunLiu1995/matplotlib
matplotlib: plotting with Python
DijunLiu1995/firm-characteristics-calculation
Python codes to create firm characteristics and returns pulling from Compustat, CRSP, and IBES through WRDS
DijunLiu1995/python-guide
Python best practices guidebook, written for humans.
DijunLiu1995/Mooc
DijunLiu1995/Intangible-capital-stocks
Parameters for intangible capital accumulation and data on intangible stocks (Ewens, Peters and Wang (2020))
DijunLiu1995/ThesisCode
This is the Python code implementation of my Master thesis. The code outline is in "Code Outline.png". The thesis paper is in "Master Thesis_Gia Phat Tram.pdf". Unfortunately, the data couldn't be shared publicly.
DijunLiu1995/hello-world
It is done following guide
DijunLiu1995/Value_Investing_IBES_CRSP_Pull
Open Source for WRDS IBES/CRSP
DijunLiu1995/PythonDataScienceHandbook
Python Data Science Handbook: full text in Jupyter Notebooks
DijunLiu1995/Empirical-finance
A tutorial of empirical finance (It will be not updated)
DijunLiu1995/webscript_factiva
DijunLiu1995/UiOBigData
Oslo Summer School in Comparative Social Science Studies 2019 Collecting and Analyzing Big Data
DijunLiu1995/ml-tutorial
Introduction to ML packages for the 6.86x course
DijunLiu1995/news_extract
Python module to extract articles from NexisUni and Factiva.
DijunLiu1995/anlp19
Course repo for Applied Natural Language Processing (Spring 2019)
DijunLiu1995/CF-Paper-replication
Replication of Philippon and Guitierrez (2017), “Investment less Growth: An Empirical Investigation”
DijunLiu1995/computational-text-analysis-spring-2019
Computational text analysis for Spring 2019 by Caroline Le Pennec-Caldichoury
DijunLiu1995/Scraptiva
A simple web scraping tool to get articles from Dow Jones Factiva