Paper: arXiv 2503.03858

Abstract

This study pioneers the application of the market microstructure framework to an informal financial market. By scraping data from websites and social media about the Cuban informal currency market, we model the dynamics of bid/ask intentions using a Limit Order Book (LOB). This approach enables us to study key characteristics such as liquidity, stability and volume profiles. We continue exploiting the Avellaneda-Stoikov model to explore the impact of introducing a Market Maker (MM) into this informal setting, assessing its influence on the market structure and the bid/ask dynamics. We show that the Market Maker improves the quality of the market. Beyond their academic significance, we believe that our findings are relevant for policymakers seeking to intervene informal markets with limited resources.

Complexity vs Empirical Score

  • Math Complexity: 3.5/10
  • Empirical Rigor: 8.5/10
  • Quadrant: Street Traders — practical and empirical, lighter on theory

Why this score: The paper applies a known market microstructure framework (Avellaneda-Stoikov) with minimal novel derivations, keeping math complexity moderate. However, it demonstrates high empirical rigor by scraping and analyzing a large, novel dataset (814k orders) from a real informal market, providing statistical validation and data availability.

Research Flowchart

  flowchart TD
  A["Research Goal:<br>Model informal currency market as LOB"] --> B["Data Collection:<br>Scraped bid/ask data from Cuban websites & social media"]
  B --> C["Methodology:<br>Construct Limit Order BookLOB) model"]
  C --> D["Computational Process:<br>Apply Avellaneda-Stoikov Model to simulate MM impact"]
  D --> E{"Key Findings/Outcomes"}
  E --> F["Market Maker improves<br>market quality & liquidity"]
  E --> G["Policymakers can use LOB model<br>to target informal markets efficiently"]