Quantitative Research Through Investment Tournaments (Presentation Slides)

Abstract

Traditionally, the development of investment strategies has required domain-specific knowledge and access to restricted datasets. These two barriers exist by design: (a) Financial knowledge is hoarded by firms, and protected as trade secrets, and (b) Financial data is expensive, making it inaccessible to the broad scientific community.

This presentation explores how these two barriers impact the quality of quantitative research, and how investment tournaments can help deliver better investment outcomes by overcoming those two barriers.

Keywords: backtest overfitting, selection bias, false investment strategy, tournaments, machine learning

JEL Classification: G0, G1, G2, G15, G24, E44