Run My Code

RunMyCode enables scientists

to openly share the code and data that underlie their research publications

This service is based on the innovative concept of a companion
website associated with a scientific publication.

Users

Users can access the code and data used by researchers.
Researchers

Researchers can share the code and data used in a scientific paper. This increases transparency and reproducibility.
Journals

Journals' editors can invite the authors who publish in their journals to share their code and data on RunMyCode.

Companion websites

Comparing (Empirical-Gramian-Based) Model Order Reduction Algorithms

Working Paper (2020)

Himpe Christian

Statistical inference of locally stationary functional coefficient models

Journal of Statistical Planning and Inference (2020)

Ding Hao, Hu Jianhua, Liu Liangyuan, and Feng Jingyan

Stock prices, exchange rates and portfolio equity flows: A Toda-Yamamoto Panel Causality Test

Journal of Economic Studies (2019)

Andriansyah Andriansyah

A Multi-Scale Learning Local Phase and Amplitude Blind Image Quality Assessment for Multiply Distorted Images

IEEE Access (2018)

Li Chaofeng

A Simple Test for Zero Multiple CorrelationCoefficient in High-Dimensional Normal Data UsingRandom Projection

Working Paper (2019)

Najarzadeh Dariush

Catch me if you can. Can human observers identify insiders in asset markets?

Journal of Economic Psychology (2018)

Palan Stefan and Stöckl Thomas

Specification tests in semiparametric transformation models - a multiplier bootstrap approach

Working Paper (2019)

Kloodt Nick and Neumeyer Natalie

Aggregation mechanisms for crowd predictions

Experimental Economics (2019)

Huber Jürgen, Palan Stefan, and Senninger Larissa

Does Investor Risk Perception Drive Asset Prices in Markets? Experimental Evidence.

Journal of Banking and Finance (2019)

Huber Jürgen, Zeisberger Stefan, and Palan Stefan