How Investor Herding Shapes Price Runs in a Continuous Double Auction

Summary

The study builds a stochastic order-book model for investor behavior in a continuous double auction, a mechanism used by major exchanges. It represents two forms of crowd behavior: investors may submit orders that follow recent price trends, or orders that oppose those trends. The authors use simulated price series to examine the range of price movements that continue in one direction and compare the cumulative distributions produced by the different behavior models.

Trend-following behavior produces a power-law tail in the distribution of directional price-run ranges, while the opposing behavior model produces a different distribution. The analysis attributes some trend formation to orders temporarily clustering on the book in line with recent price movements. These findings offer a possible mechanism linking participant behavior and large price runs. They come from a model and its simulations, however; the document does not provide empirical validation on live order-book data or assess whether the patterns can be traded profitably.

Key ideas

• The model represents both trend-following and trend-opposing order submission in a continuous double auction.
• Simulated price data are analyzed by the ranges of movements that continue in one direction.
• Trend-following behavior produces a power-law tail in the cumulative distribution of price-run ranges.
• The authors connect trend formation to temporary clustering of orders in line with recent price trends.
• The reported evidence comes from a stochastic model and simulations rather than documented live-market tests.

Tags

# Simple Stochastic Order-Book Model of Swarm Behavior in Continuous Double Auction


# Simple Stochastic Order-Book Model of Swarm Behavior in Continuous Double Auction









In this study, we present a simple stochastic order-book model for investors' swarm behaviors seen in the continuous double auction mechanism, which is employed by major global exchanges. Our study shows a characteristic called "fat tail" is seen in the data obtained from our model that incorporates the investors' swarm behaviors. Our model captures two swarm behaviors: one is investors' behavior to follow a trend in the historical price movement, and another is investors' behavior to send orders that contradict a trend in the historical price movement. In order to capture the features of influence by the swarm behaviors, from price data derived from our simulations using these models, we analyzed the price movement range, that is, how much the price is moved when it is continuously moved in a single direction. Depending on the type of swarm behavior, we saw a difference in the cumulative frequency distribution of this price movement range. In particular, for the model of investors who followed a trend in the historical price movement, we saw the power law in the tail of the cumulative frequency distribution of this price movement range. In addition, we analyzed the shape of the tail of the cumulative frequency distribution. The result demonstrated that one of the reasons the trend following of price occurs is that orders temporarily swarm on the order book in accordance with past price trends.

Shown in full with attribution under the source's licence. Licence: abstract CC0

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.