Optimal Trading in a Limit Order Book Using Linear Strategies (original) (raw)

Time-dependent trading strategies in a continuous double auction

Emergent Results of Artificial Economics, 2011

We model a continuous double auction with heterogenous agents and compute approximate optimal trading strategies using evolution strategies. Agents privately know their values and costs and have a limited time to transact. We focus on equilibrium strategies that are developed taking into account the number of traders that submitted orders previously, as well as the number of who will submit subsequently. We find that it is optimal to place increasingly aggressive orders, according to a roughly linear schedule, and test the resulting equilibrium for robustness and accuracy.

Statistical theory of the continuous double auction

Quantitative Finance, 2003

Most modern financial markets use a continuous double auction mechanism to store and match orders and facilitate trading. In this paper we develop a microscopic dynamical statistical model for the continuous double auction under the assumption of IID random order flow, and analyze it using simulation, dimensional analysis, and theoretical tools based on mean field approximations. The model makes testable predictions for basic properties of markets, such as price volatility, the depth of stored supply and demand vs. price, the bid-ask spread, the price impact function, and the time and probability of filling orders. These predictions are based on properties of order flow and the limit order book, such as share volume of market and limit orders, cancellations, typical order size, and tick size. Because these quantities can all be measured directly there are no free parameters. We show that the order size, which can be cast as a nondimensional granularity parameter, is in most cases a more significant determinant of market behavior than tick size. We also provide an explanation for the observed highly concave nature of the price impact function. On a broader level, this work suggests how stochastic models based on zero-intelligence agents may be useful to probe the structure of market institutions. Like the model of perfect rationality, a stochastic-zero intelligence model can be used to make strong predictions based on a compact set of assumptions, even if these assumptions are not fully believable.

Efficiency of continuous double auctions under individual evolutionary learning with full or limited information

Current Medical Research and Opinion, 2010

In this paper we explore how specific aspects of market transparency and agents’ behavior affect the efficiency of the market outcome. In particular, we are interested whether learning behavior with and without information about actions of other participants improves market efficiency. We consider a simple market for a homogeneous good populated by buyers and sellers. The valuations of the buyers and the costs of the sellers are given exogenously. Agents are involved in consecutive trading sessions, which are organized as a continuous double auction with order book. Using Individual Evolutionary Learning agents submit price bids and offers, trying to learn the most profitable strategy by looking at their realized and counterfactual or “foregone” payoffs. We find that learning outcomes heavily depend on information treatments. Under full information about actions of others, agents’ orders tend to be similar, while under limited information agents tend to submit their valuations/costs. This behavioral outcome results in higher price volatility for the latter treatment. We also find that learning improves allocative efficiency when compared to outcomes with Zero-Intelligent traders.

Simulating new markets by introducing new accepting policies for the conventional continuous double auction

Proceedings of the …, 2008

In recent years a huge number of online auctions that use Multi Agent systems have been created. As a result there are numerous auctions that provide the same product. In this case each customer can buy a product with the lowest possible price. But searching between auctions in terms of finding the suitable product can be time consuming for consumers and also providing products in different markets is a difficult task for suppliers. So the need for an autonomous agent in these types of markets is deeply felt. On the other side the structure of an auction mechanism that provides the environment for traders to operate their trades is vital. Despite all the research that has been done about online auctions, most of them were about single markets. But in real world the stocks and commodities of companies are listed and traded in different markets. There is a growing tendency towards research about online auctions and Market Design. Particularly in recent years CAT (CATallactics) game has provided an important opportunity to develop and test new techniques in this field. In this paper after introducing CAT game and PersianCAT agent, we want to challenge the conventional accepting policy used in stock markets like New York Stock Exchange and provide a better solution that improves the general performance of the markets.

Convergence of outcomes and evolution of strategic behavior in double auctions

Journal of Evolutionary Economics, 2011

We study the emergence of strategic behavior in double auctions with an equal number n of buyers and sellers, under the distinct assumptions that orders are cleared simultaneously or asynchronously. The evolution of strategic behavior is modeled as a learning process driven by a genetic algorithm. We find that, as the size n of the market grows, allocative inefficiency tends to zero and performance converges to the competitive outcome, regardless of the order-clearing rule. The main result concerns the evolution of strategic behavior. Under simultaneous orderclearing, as n increases, only marginal traders learn to be price takers and make offers equal to their valuations/costs. Under asynchronous order-clearing, as n increases, all intramarginal traders learn to be price makers and make offers equal to the competitive equilibrium price. The nature of the order-clearing rule affects in a fundamental way what kind of strategic behavior we should expect to emerge.

The Effect of Transaction Costs on Artificial Continuous Double Auction Markets

Lecture Notes in Economics and Mathematical Systems, 2010

The Continuous Double Auction (CDA) is used in the CO2 emissions permits. High market efficiency (close to 100%) is the most robust results in a typical CDA experiment, where transactions and submissions are costless. However, in real world trading, there are monetary costs on transactions. In this paper we study the sensitivity of CDA performance to the imposition of monetary costs on the market using an artificial agent-based model approach. We find that the monetary costs reduce market efficiency according to both the theory and previous Experimental Economics results. Moreover, our model provides new behavioural explanations of these effects that have practical value in the design and analysis of CO2 permits markets

Modeling and simulation of a double auction artificial financial market

Physica A-statistical Mechanics and Its Applications, 2005

We present a double-auction artificial financial market populated by heterogeneous agents who trade one risky asset in exchange for cash. Agents issue random orders subject to budget constraints. The limit prices of orders may depend on past market volatility. Limit orders are stored in the book whereas market orders give immediate birth to transactions. We show that fat tails and volatility clustering are recovered by means of very simple assumptions. We also investigate two important stylized facts of the limit order book, i.e., the distribution of waiting times between two consecutive transactions and the instantaneous price impact function. We show both theoretically and through simulations that if the order waiting times are exponentially distributed, even trading waiting times are also exponentially distributed.

An agent-based model for sequential Dutch auctions

2013 Winter Simulations Conference (WSC), 2013

We propose an agent-based computational mode to investigate sequential Dutch auctions with particular emphasis on markets for perishable goods and we take as an example wholesale fish markets. Buyers in these markets sell the fish they purchase on a retail market. The paper provides an original model of boundedly rational behavior for wholesale buyers' behavior incorporating inter-temporal profit maximization, conjectures on opponents' behavior and fictive learning. We analyse the dynamics of the aggregate price under different market conditions in order to explain the emergence of market price patterns such as the well-known declining price paradox. The proposed behavioral model provides alternative explanations for market price dynamics to those which depend on standard hypotheses such as diminishing marginal profits.

Intermittent Behavior Induced by Asynchronous Interactions in a Continuous Double Auction Model

Advances in Complex Systems, 2017

Continuous asynchronous trading activity is a key to understanding real-world market behavior. However, it is not easy to implement an agent-based computational market model because of the ambiguity between time and space. In this study, we use a model of asynchrony in a continuous double auction market in the form of noise and order restrictions to link inside- and outside- uncertainties in the economic system. Our model shows intermittent behavior with a small parameter value, which leads to the misapplication of the price-update rule, and consequently drives burst behavior. The statistical property of time development shows a similar tendency to that in previous empirical studies. Thus, it demonstrates the relationship between the asynchronous property and the complexity of economic systems.