Microscopic understanding of heavy-tailed return distributions in an agent-based model

TL;DR

This paper uses an agent-based model of a double-auction order book to demonstrate that heavy-tailed return distributions in financial markets arise primarily from liquidity constraints and order book gaps, rather than trading strategies.

Contribution

It provides a microscopic explanation for heavy tails in return distributions by linking them to order book gaps caused by limited liquidity, independent of trading strategies.

Findings

Heavy tails emerge when liquidity is constrained.

Order book gaps are the main cause of large price shifts.

Dense order books do not produce heavy tails.

Abstract

The distribution of returns in financial time series exhibits heavy tails. In empirical studies, it has been found that gaps between the orders in the order book lead to large price shifts and thereby to these heavy tails. We set up an agent based model to study this issue and, in particular, how the gaps in the order book emerge. The trading mechanism in our model is based on a double-auction order book, which is used on nearly all stock exchanges. In situations where the order book is densely occupied with limit orders we do not observe fat-tailed distributions. As soon as less liquidity is available, a gap structure forms which leads to return distributions with heavy tails. We show that return distributions with heavy tails are an order-book effect if the available liquidity is constrained. This is largely independent of the specific trading strategies.