A simulation analysis of the microstructure of double auction markets*

Chiarella, Carl; Iori, Giulia

doi:10.1088/1469-7688/2/5/303

Cited by 240 publications

(146 citation statements)

References 9 publications

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“…We modify an order-driven market with heterogeneous investors, which was originally constructed by Chiarella and Iori (2002). In the order-driven market of Chiarella and Iori, investors set bids and asks and submit limit or market orders according to exogenously fixed rules.…”

Section: Introductionmentioning

confidence: 99%

Long-memory in an order-driven market

LeBaron

Yamamoto

2007

Physica A: Statistical Mechanics and its Applications

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This paper introduces an order-driven market with heterogeneous investors, who submit limit or market orders according to their own trading rules. The trading rules are repeatedly updated via simple learning and adaptation of the investors. We analyze markets with and without learning and adaptation. The simulation results show that our model with learning and adaptation successfully replicates long-memories in trading volume, stock return volatility, and signs of market orders. We also discuss why evolutionary dynamics are important in generating these long memory features.2

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Section: Introductionmentioning

confidence: 99%

Long-memory in an order-driven market

LeBaron

Yamamoto

2007

Physica A: Statistical Mechanics and its Applications

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“…The model developed here extends the earlier one of Chiarella and Iori (2002) in several important aspects, in particular agents have heterogenous time horizons and can submit orders of sizes larger than one, determined either by utility maximisation or by a random selection procedure. The model seeks to capture a number of features suggested by recent empirical analysis of limit order data, such as; fat-tailed distribution of limit order placement from current bid/ask; fat-tailed distribution of order execution-time; fat-tailed distribution of orders stored in the order book; long memory in the signs (buy or sell) of trades.…”

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confidence: 99%

The Impact of Heterogeneous Trading Rules on the Limit Order Book and Order Flows

2004

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In this paper we develop a model of an order-driven market where traders set bids and asks and post market or limit orders according to exogenously fixed rules. The model developed here extends the earlier one of Chiarella and Iori (2002) in several important aspects, in particular agents have heterogenous time horizons and can submit orders of sizes larger than one, determined either by utility maximisation or by a random selection procedure. The model seeks to capture a number of features suggested by recent empirical analysis of limit order data, such as; fat-tailed distribution of limit order placement from current bid/ask; fat-tailed distribution of order execution-time; fat-tailed distribution of orders stored in the order book; long memory in the signs (buy or sell) of trades. We analyze the impact of chartist and fundamentalist strategies on the determination of both the placement level and the placement size, on the shape of the book, the distribution of orders at different prices, and the distribution of their execution time. We compare the results of model simulations with real market data.

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“…Others focus on automated internet commerce and trading strategies (Chen 2000;Das 2003;Cliff 2006;Ma and Leung 2008). Others again address specific questions about observed dynamics in trading (Cliff and Preist 2001;Chiarella and Iori 2002). But none offers an overarching general framework to study market-based control (MBC) of resource allocation.…”

Section: Overview Of Existing Work On Agent-based Modelling Of Price mentioning

confidence: 99%

A Generic Framework for a Combined Agent-based Market and Production Model

2012

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Agent-based market models are in general based on a-priori defined supply and demand schemes. Likewise, production models assume that prices are known a-priori. In reality prices depend on variable demands and supplies, while demand and supply depend on variable prices, and these two processes are interconnected. This paper describes a model that for the first time simulates a combined agent-based double auction market and production model. The model is built around von Neumann technology matrices (von Neumann, Rev Econ Stud 13(1):1-9, 1946) which provide the links between products. Agents possess one or more technologies to produce products from other products. They trade in order to acquire the inputs and sell in order to generate revenue, and the price is determined by a process of negotiation between buyers and sellers. The algorithm of negotiation is based on Cliff's Zero Intelligence Plus approach (Cliff, Minimal-intelligence agents for bargaining behaviors in market-based environments. Technical report, School of Cognitive and Computing Sciences, University of Sussex, 1997), but instead of a single commodity with fixed limit prices the agents change their limit prices for multiple products based on the simulated economic situation. The combination of production and market provides a simple but complete bottom-up model framework for microeconomics. As the results show, the model employs a price mechanism that results in an appropriate allocation of resources without a central command.

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A simulation analysis of the microstructure of double auction markets*

Cited by 240 publications

References 9 publications

Long-memory in an order-driven market

Long-memory in an order-driven market

The Impact of Heterogeneous Trading Rules on the Limit Order Book and Order Flows

A Generic Framework for a Combined Agent-based Market and Production Model

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