Daniel Ladley

Zero intelligence in economics and finance

This paper reviews the Zero Intelligence (ZI) methodology for investigating markets. This approach models individual traders, operating within a market mechanism, who behave without strategy, in order to determine the impact of the market mechanism and consequently the effect of trader behaviour. The paper considers the major contributions and models within this area from both the economics and finance communities before examining the strengths and weaknesses of this methodology.

Review: zero intelligence in economics and finance

This paper reviews the Zero Intelligence (ZI) methodology for investigating markets. This approach models individual traders, operating within a market mechanism, who behave without strategy, in order to determine the impact of the market mechanism and consequently the effect of trader behaviour. The paper considers the major contributions and models within this area from both the economics and finance communities before examining the strengths and weaknesses of this methodology.

Logistic constraints on 3D termite construction

The building behaviour of termites has previously been modelled mathematically in two dimensions. However, physical and logistic constraints were not taken into account in these models. Here, we develop and test a three-dimensional agent-based model of this process that places realistic constraints on the diffusion of pheromones, the movement of termites, and the integrity of the architecture that they construct. The following scenarios are modelled: the use of a pheromone template in the construction of a simple royal chamber, the effect of wind on this process, and the construction of covered pathways. We consider the role of the third dimension and the effect of logistic constraints on termite behaviour and, reciprocally, the structures that they create. For instance, when agents find it difficult to reach some elevated or exterior areas of the growing structure, building proceeds at a reduced rate in these areas, ultimately influencing the range of termite-buildable architectures.

Wasps, termites, and waspmites: Distinguishing competence from performance in collective construction

We introduce a distinction between algorithm performance and algorithm competence and argue that bio-inspired computing should characterize the former rather than the latter. To exemplify this, we explore and extend a bio-inspired algorithm for collective construction influenced by paper wasp behavior. Despite its being provably general in its competence, we demonstrate limitations on the algorithms performance. We explain these limitations, and extend the algorithm to include pheromone-mediated behavior typical of termites. The resulting hybrid waspmite algorithm shares the generality of the original wasp algorithm, but exhibits improved performance and scalability.

Who to listen to: exploiting information quality in a ZIP-Agent market

Market theory is often concerned only with centralised markets. In this paper, we consider a market that is distributed over a network, allowing us to characterise spatially (or temporally) segregated markets. The effect of this modification on the behaviour of a market populated by simple trading agents was examined. It was demonstrated that an agents ability to identify the optimum market price is positively correlated with its network connectivity. A better connected agent receives more information and, as a result, is better able to judge the market state. The ZIP trading agent algorithm is modified in light of this result. Simulations reveal that trading agents which take account of the quality of the information that they receive are better able to identify the optimum price within a market.

The Simplicity of Optimal Trading in Order Book Markets

A traders execution strategy has a large effect on his profits. Identifying an optimal strategy, however, is often frustrated by the complexity of market microstructures. We analyse an order book based continuous double auction market under two different models of traders behaviour. In the first case actions only depend on a linear combination of the best bid and ask. In the second model traders adopt the Markov perfect equilibrium strategies of the trading game. Both models are analytically intractable and so optimal strategies are identified by the use of numerical techniques. Using the Markov model we show that, beyond the best quotes, additional information has little effect on either the behaviour of traders or the dynamics of the market. The remarkable similarity of the results obtained by the linear model indicates that the optimal strategy may be reasonably approximated by a linear function. We conclude that whilst the order book market and strategy space of traders are potentially very large and complex, optimal strategies may be relatively simple and based on a minimal information set.

The effects of market structure on a heterogeneous evolving population of traders

The majority of market theory is only concerned with centralised markets. In this paper, we consider a market that is distributed over a network, allowing us to characterise spatially (or temporally) separated markets. The effect of this modification on the behaviour of a market with a heterogeneous population of traders, under selection through a genetic algorithm, is examined. It is demonstrated that better-connected traders are able to make more profit than less connected traders and that this is due to a difference in the number of possible trading opportunities and not due to informational inequalities. A learning rule that had previously been demonstrated to profitably exploit network structure for a homogeneous population is shown to confer no advantage when selection is applied to a heterogeneous population of traders. It is also shown that better-connected traders adopt more aggressive market strategies in order to extract more surplus from the market.

Losing Money on the Margin

Margin trading is popular with retail investors around the world. We show in this paper, however, that the collateral requirement imposed by margin calls results in negative expected returns for these traders whilst also inducing positive skew in the returns distribution. Investments in assets with symmetric returns, when traded on margin, instead offer limited losses and a small chance of a large gain, much like lottery stocks and other gambles. We demonstrate this theoretically and then show empirically, using a unique database of account data from a Chinese retail brokerage, that the realized losses of margin traders are often substantial.

Margin Trading: Hedonic Returns and Real Losses

Margin trading is popular with retail investors around the world. This is a puzzle, since, as we show, it has a negative expected return. Our explanation is that whilst lowering mean returns, the collateral requirement imposed by margin calls induces positive skew in the distribution of returns. Investments in assets with symmetric returns now offer limited losses and a small chance of a large gain, like lottery tickets and other gambles. Results from a unique dataset of retail futures traders show that actual losses are substantial. Traders’ behaviour is demonstrated to be best understood as motivated by hedonic returns.

The Role of Hormones in Financial Markets

Steroid hormones, such as testosterone, have been shown to affect risk preferences in humans with high levels leading to excessive risk-taking. Hormone levels, in turn, are affected by trading outcomes as well as by gender -- males are more sensitive to stimuli than females. We investigate the effects of hormones on market behavior and trader performance. An increase in the proportion of female traders does not necessarily make markets less volatile; however, it reduces the occurrence of market crashes. Male traders on average under-perform females, although the best performing individuals are more likely to be male.