Our Compendium is one of Rebellion Research Papers of the Year 2023!

The Compendium of Data Sources that was written by Oleksandr “Alex” Bilokon, Paul Bilokon, and Saeed Amen has been chosen by Rebellion Research as one of the 2023 Research papers of the Year!

Recent advances in data science, machine learning, and artificial intelligence, such as the emergence of large language models, are leading to an increasing demand for data that can be processed by such models. While data sources are application-specific, and it is impossible to produce an exhaustive list of such data sources, it seems that a comprehensive, rather than complete, list would still benefit data scientists and machine learning experts of all levels of seniority. The goal of this publication is to provide just such an (inevitably incomplete) list – or compendium – of data sources across multiple areas of applications, including finance and economics, legal (laws and regulations), life sciences (medicine and drug discovery), news sentiment and social media, retail and ecommerce, satellite imagery, and shipping and logistics, and sports.

Here is the full list of papers that have been selected:

Implementing Portfolio Risk Management and Hedging in Practice by Paul Bilokon :: SSRN

Deep order flow imbalance: Extracting alpha at multiple horizons from the limit order book – Kolm – 2023 – Mathematical Finance – Wiley Online Library

Valuing Data as an Asset* | Review of Finance | Oxford Academic (oup.com)

Financial Machine Learning by Bryan T. Kelly, Dacheng Xiu :: SSRN

Pseudo-Factors and Factor Investing by Marcos Lopez de Prado :: SSRN

A Compendium of Data Sources for Data Science, Machine Learning, and Artificial Intelligence by Paul Bilokon, Oleksandr Bilokon, Saeed Amen :: SSRN

[2309.05926] SCOP: Schrodinger Control Optimal Planning for Goal-Based Wealth Management (arxiv.org)

Trading with Concave Price Impact and Impact Decay – Theory and Evidence by Natascha Hey, Iacopo Mastromatteo, Johannes Muhle-Karbe, Kevin Webster :: SSRN

Ranking Empirical Evidence in Finance by Marcos Lopez de Prado :: SSRN

Deep Order Flow Imbalance: Extracting Alpha at Multiple Horizons from the Limit Order Book by Petter N. Kolm, Jeremy Turiel, Nicholas Westray :: SSRN

[2309.04547] Kelvin Waves, Klein-Kramers and Kolmogorov Equations, Path-Dependent Financial Instruments: Survey and New Results (arxiv.org)

A Causal Analysis of Market Contagion: A Double Machine Learning Approach | Portfolio Management Research (pm-research.com)

Data Driven Dimensionality Reduction to Improve Modeling Performance by Joshua Chung, Marcos Lopez de Prado, Horst Simon, Kesheng Wu :: SSRN

For more information, please see https://www.rebellionresearch.com/2023-research-papers-of-the-year