Waiting Times in Simulated Stock Markets

TL;DR

This paper uses an agent-based simulation of a stock exchange to analyze the robustness of the Continuous Double Auction mechanism across various market microstructures and operator behaviors, revealing insights into market efficiency.

Contribution

It introduces a detailed agent-based model that reproduces realistic order flows and evaluates the CDA's robustness across diverse simulated market conditions.

Findings

CDA effectively clears different order flows

Milan stock exchange shows slightly higher efficiency than NYSE

Market complexity influences clearing efficiency

Abstract

Exploiting a precise reproduction of a stock exchange, the robustness of the Continuous Double Auction (CDA) mechanism, evaluated by means of the waiting time distributions, has been proved versus 36 different set ups made by varying both the operators' behaviour and the market micro structure. The obtained results demonstrate that the CDA remains able to clear strongly different order flows, though the Milan stock exchange seemed to be a little more efficient than the NYSE under the allocative point of view, witnessing the intrinsic complexity of the stock market. The simulation has been built as an Agent Based Model in order to obtain a plausible order flow. The decisions of single agents and their interaction through the market book are realistic and reproduce some empirical analysis results. The mentioned results have been obtained either by the analysis of the complete pending time series and the same computation of the asks and bids series alone.