Giter Club home page Giter Club logo

replicationcrisis's Introduction

Overview

This repository contains the code used for the paper Is There a Replication Crisis in Finance? by Jensen, Kelly and Pedersen (2023). Please cite this paper if you are using the code or data:

@article{JensenKellyPedersen2023,
	author = {Jensen, Theis Ingerslev and Kelly, Bryan and Pedersen, Lasse Heje},
	title = {Is There a Replication Crisis in Finance?},
	journal = {The Journal of Finance},
	volume = {78},
	number = {5},
	pages = {2465-2518},
	year = {2023}
}

Follow this link for a detailed documentation of the data sets.

The code consists of the following two self-contained components:

  • GlobalFactors is a folder with code that creates data sets of global stock returns, stock characteristics, and global long-short factors. Note that the long-short factors can also be downloaded directly, both the factor returns used in the paper (here) and the latest version of the factor returns (see weblink below). In addition, we keep a folder with the latest versions of the factor returns and additional data such as the underlying portfolios, market returns, and industry returns (link).

  • Analysis is a folder that contains the analysis in the paper, including all figures and tables. This folder takes the global factors as input (either the ones that can be downloaded or the ones that you construct yourself).

See also the website https://JKPfactors.com/, where the most recent long-short factors can be downloaded using a simple drop-down menu.

replicationcrisis's People

Contributors

faheemalmas avatar kellybry avatar lhpedersen avatar mk0417 avatar theisij avatar tyler-147 avatar

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

replicationcrisis's Issues

Mispricing Score Interpretation

Hi,

I am wondering about the ranking of the mispricing scores. In the documentation of Stambaugh, Yu, Yuan, their mispricing score has the following interpretation:

According to this measure, the stocks with the highest values of MISP are the most “overpriced,” and those with the lowest values are the most “underpriced.”

As I am a novice to SAS programming I cannot answer the following question by looking at the source code: Is the mispricing measure you provide sorted in the same way, i.e., should stocks with a high mispricing measure have lower next month returns ? From what I understand, you sign the variables according to the findings in the literature, and the sort descending, which would yield the opposite interpretation, i.e., a high mispricing measure is associated with higher (not lower) next month returns.

Thanks for a clarification and best regards!

Code generates no data in output folder

Thank you for sharing your project.
I encountered some issues running your code on SAS Studio (3.81 Basic Edition). After running the code the output folder contains only empty zip files. I would appreciate your help. Thanks in advance.

I will share LOGs if the current run is completed because I didn't save the LOGs from the last run

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.