# Information-Based Trading

**Authors:** George Bouzianis, Lane P. Hughston, Leandro Sánchez-Betancourt  
**arXiv:** [2201.08875](https://arxiv.org/abs/2201.08875)  
**Date:** 2022-01-21  
**Summary page:** https://www.summarizepaper.com/en/paper/2201.08875v4/

## Key points

- Study focuses on dynamics of trading in a market where information is crucial
- Introduces tiered trading concept with tier-1 market and tier-2 informed trader
- Draws parallels to existing literature such as "Pythagorian" formula and statistical arbitrage arguments
- Considers scenarios with distinct information processes for traders
- Analyzes how different types of markets can be studied within an information-based framework
- Explores situations involving multiple trades, inventory aversion, and varying levels of informational superiority among traders
- Demonstrates that higher information flow rates can lead to advantageous trading outcomes
- Emphasizes importance of understanding market dynamics and impact of informational advantages on trading strategies

## Summary

In this study, we explore the dynamics of trading in a market where information plays a crucial role. Building upon previous research by Brody, Hughston & Macrina (2007, 2008) and Brody, Davis, Friedman & Hughston (2009), we focus on a scenario where two traders operate with varying levels of information. The first trader possesses more comprehensive information about a security that yields a random cash flow at a fixed future time $T$, while the second trader's information is a subset of the first trader's knowledge. Using a model inspired by previous works, we introduce the concept of tiered trading, where the market as a whole can be viewed as a tier-1 trader and the informed trader as a tier-2 trader. We draw parallels to existing literature such as the "Pythagorian" formula and statistical arbitrage arguments to analyze how traders make prices based on their respective information flows. Expanding on the idea of heterogeneous markets explored in prior studies, we consider scenarios where each trader has access to distinct information processes. We compare this approach to hierarchical models like the one presented in our paper, which showcase how different types of markets can be analyzed within an information-based framework. Furthermore, we extend our analysis to situations involving multiple trades, inventory aversion, and varying levels of informational superiority among traders. By simulating these scenarios and conducting numerical analyses, we demonstrate that having higher information flow rates can lead to advantageous trading outcomes. Throughout our exploration of trading models within an information-based framework, we highlight the importance of understanding how different types of markets operate and how informational advantages can impact trading strategies. Our findings contribute to ongoing discussions in the field of market dynamics and provide insights into optimizing trading decisions based on available information sources. This work was presented at the 16th Research in Options conference (RIO 2021) and benefited from feedback received from participants at various academic institutions. We acknowledge contributions from seminar participants at McMaster University and thank colleagues for their valuable input during earlier drafts of this study.