Artificial Market Research Articles

Confidence and the Stock Market: An Agent-Based Approach

Using a behavioral finance approach we study the impact of behavioral bias. We construct an artificial market consisting of fundamentalists and chartists to model the decision-making process of various agents. The agents differ in their strategies for evaluating stock prices, and exhibit differing memory lengths and confidence levels. When we increase the heterogeneity of the strategies used by the agents, in particular the memory lengths, we observe excess volatility and kurtosis, in agreement with real market fluctuations—indicating that agents in real-world financial markets exhibit widely differing memory lengths. We incorporate the behavioral traits of adaptive confidence and observe a positive correlation between average confidence and return rate, indicating that market sentiment is an important driver in price fluctuations. The introduction of market confidence increases price volatility, reflecting the negative effect of irrationality in market behavior.

Application of Artificial Capital Market in Task Allocation in Multi-robot Foraging

AbstractBecause of high speed, efficiency, robustness and flexibility of multi-agent systems, in recent years there has been an increasing interest in the art of these systems. Artificial market mechanisms are one of the well-known negotiation multi-agent protocols in multi-agent systems. In this paper artificial capital market as a new variant of market mechanism is introduced and employed in a multi-robot foraging problem. In this artificial capital market, the robots are going to benefit via investment on some assets, defined as doing foraging task. Each investment has a cost and an outcome. Limited initial capital of the investors constrains their investments. A negotiation protocol is proposed for decision making of the agents. Qualitative analysis reveals speed of convergence, near optimal solutions and robustness of the algorithm. Numerical analysis shows advantages of the proposed method over two previously developed heuristics in terms of four performance criteria.

Entrepreneurial piracy through strategic deception: the 'make, buy, or steal' decision

In this paper, we explore the antecedents of entrepreneurial piracy through a case study approach involving the move of the National Basketball Association’s (NBA’s) Seattle Supersonics to Oklahoma City (OKC). The move of the Supersonics highlights an aspect of organisational strategy where existing theory is deficient in explaining the phenomena regarding firm boundaries and resource acquisition. Specifically, we argue in this paper for an expansion of the traditional ‘make or buy’ decision to include a ‘steal’ option. Several propositions are offered to suggest that the context in which this act of entrepreneurial piracy occurred could be generalised to other cases of artificial market constraints on valuable resources and includes the features of information compactedness, opportunism, bounded rationality, and strategic deception.

An Agent-based Model to Study the Evolution of Service Systems through the Service Life Cycle

We introduce a unified concept of service life cycle (SLC) for the study of service system evolution. The need for this research arises from the fact that studying service ecosystems has become a critical need in the modern service economy. Adopting the view that a service ecosystem is a complex adaptive system of interacting service systems, we propose Agentbased Modeling methodology as a potential candidate for service research. Our agent-based model simulates an artificial market, in which one hypothetical service is being offered and customer agents interact with service provider agents to co-create value. The design of the model takes inputs from the service dominant logic, Kauffman’s NKCS model and the ISPAR model of service system interactions. The simulation results reveal that the evolution of service providers follows a life cycle pattern, which we call the Service Life Cycle. We propose the SLC to be used as a reference to evaluate the performance of service providers in a service ecosystem, initiating a novel S-D logic based discussion on sustainability of business firms.

A controllable laboratory stock market for modeling real stock markets

Based on the different research approaches, econophysics can be divided into three directions: empirical econophysics, computational econophysics, and experimental econophysics. Because empirical econophysics lacks controllability that is needed to study the impacts of different external conditions and computational econophysics has to adopt artificial decision-making processes that are often deviated from those of real humans, experimental econophysics tends to overcome these problems by offering controllability and using real humans in laboratory experiments. However, to our knowledge, the existing laboratory experiments have not convincingly reappeared the stylized facts (say, scaling) that have been revealed for real economic/financial markets by econophysicists. A most important reason is that in these experiments, discrete trading time makes these laboratory markets deviated from real markets where trading time is naturally continuous. Here we attempt to overcome this problem by designing a continuous double-auction stock-trading market and conducting several human experiments in laboratory. As an initial work, the present artificial financial market can reproduce some stylized facts related to clustering and scaling. Also, it predicts some other scaling in human behavior dynamics that is hard to achieve in real markets due to the difficulty in getting the data. Thus, it becomes possible to study real stock markets by conducting controlled experiments on such laboratory stock markets producing high frequency data.

Trade-offs in designing water pollution trading policy with multiple objectives: A case study in the Tai Lake Basin, China

Abstract The design of an emissions trading system crucially depends not only on cost-efficiency but also on the nature of the pollutant being regulated and traded. Because the water quality impacts of the pollution discharged by polluters are closely related to the polluters’ locations, a water pollution trading system for non-uniformly mixed pollutants such as chemical oxygen demand (COD) may cause violations of predetermined water quality standards over the length of a river. Trading ratios are a way of ensuring the equivalency of the potential water quality impact between an allowance generated in one location and used in another location in a watershed. This research proposed a zonal-based trading ratios (ZTR) system to improve cost-efficiency while meeting environmental constraints. An artificial market for COD trading in the Wujingang watershed in Tai Lake Basin was constructed by applying an agent-based model. A Water Quality Analysis Simulation Program (WASP) model was introduced to predict the water quality impacts of the water pollution trading market on the river system. The results show that a simply designed tradable discharge permit (TDP) system for the Tai Lake Basin without trading ratios has the potential to decrease water quality in some locations. A trading market restricted by ZTR is more efficient in creating trade-offs between achieving cost-efficiency and meeting water quality standards. Thus, the integration of trading ratios in pilot programs for water pollution trading policy deployments in the Tai Lake Basin and throughout China is suggested to minimize adverse water quality impacts.

A New Tradable Credit Scheme for the Morning Commute Problem

This paper seeks to apply a new tradable credit scheme in the morning commute problem. When implementing such a scheme, the congestion management authority first delineates a peak-time window and then requires all traveler who pass the bottleneck within that window to either pay certain units of mobility credits, or a peak time toll (which is comparably more expensive). The authority also rewards credits to anyone who passes the bottleneck during the designated off-peak time window. An artificial market is created so that the travelers may trade these credits with each other. Our analyses, which are based on the Vickrey’s bottleneck model managed by step tolls, indicate that the proposed scheme has several notable advantages. First, the market allows those who value travel time savings less to be directly compensated by selling credits to those who value them more. This mechanism promises simpler and fairer distribution of the benefits from congestion relief. Second, as no transfer of wealth takes places between travelers and the authority, the payment made to acquire credits is less likely to be perceived as a tax. Third, the rewarding-charging mechanism avoids the top-down allocation of credits in existing tradable credit schemes. In the proposed scheme, credits are only rewarded to those who contribute to congestion relief. Last but not least, the proposed scheme is easy to understand and simple to implement. In particular, we show that the best choice of the rewarding-charging ratio is 1, i.e., each peak-time user will be charged one credit and each off-peak user will be awarded one credit.

Investigating the Impact of Trading Frequencies of Market Makers: A Multi-Agent Simulation Approach

This research builds an artificial market, which was composed of stylized traders and of market makers, to study the market impact under different trading frequencies of market makers. In addition,...

Study on the Stability of an Artificial Stock Option Market Based on Bidirectional Conduction

Although stock option markets have grown dramatically over the past several decades, the relation between an option and its underlying asset, especially bidirectional conduction, is not particularly clear. So far, there have been many debates about this topic. We try to investigate this problem from a novel angle: an artificial stock market including a stock option is constructed in this paper. The model includes two parts, one is a stock trade module based on the Santa Fe Institute Artificial Stock Market (SFI-ASM), and the other is an option trade module. In the latter module, three types of option traders are employed. The results show that the model is effective, and experiments illustrate that option markets have a remarkable effect on stock markets. Furthermore, by appending options, the model replicates some stylized properties, such as volatility clustering and GARCH effect, which can be observed in real financial markets.

Design of Financial Market Regulations against Large Price Fluctuations Using by Artificial Market Simulations

We built an artificial market model and compared effects of price variation limits, short selling regulations and up-tick rules. In the case without the regulations, the price fell to below a fundamental value when an economic crush occurred. On the other hand, in the case with the regulations, this overshooting did not occur. However, the short selling regulation and the up-tick rule caused the trading prices to be higher than the fundamental value. We also surveyed an adequate limitation price range and an adequate limitation time span for the price variation limit and found a parameters’ condition of the price variation limit to prevent the over-shorts. We also showed the limitation price range should be bigger than a volatility calculated by the limitation time span.

Investigation and Optimal Designing of a Price Variation Limit, a Short Sell Regulation and an Up-Tick Rule using by Artificial Market Simulations

Investigation and Optimal Designing of a Price Variation Limit, a Short Sell Regulation and an Up-Tick Rule using by Artificial Market Simulations

Analysis of the Impact of Changing Strategy on the GARCH Effect with Artificial Market Simulation

Analysis of the Impact of Changing Strategy on the GARCH Effect with Artificial Market Simulation

The Evolution of the Generalized Differentiated Services Architecture and the Changing Role of the Internet Engineering Task Force

The changing role of the Internet Engineering Task Force (IETF) standard setting process from designing and implementing the best effort TCP/IP protocol as a universal standard towards a platform for dealing with the increasing need for variety in the design of a Quality of Service (QoS) differentiated traffic management architecture is demonstrated. The IETF´s contributions to a flexible open transmission architecture able to supply the required transmission qualities for the different applications provide the relevant pillars towards a Generalized Differentiated Service (DiffServ) architecture. Furthermore, the role of entrepreneurial traffic management within the Generalized DiffServ architecture and the division of labor between the IETF and entrepreneurial traffic management is analyzed. Within the umbrella architecture of Generalized DiffServ with the potential to combine basic elements of QoS differentiated traffic architectures a flexible framework for entrepreneurial traffic quality differentiation strategies is evolving. Its basic characteristic is market driven network neutrality with all applications bearing the opportunity costs of their required traffic capacities. As a consequence an artificial market split between best effort TCP and managed services would conflict with the integrated service approach of the IETF. Finally, the implementation of Generalized DiffServ via Next Generation networks is considered.

Application of Artificial Stock Market in the Stock Market Tradi Mechanism

Application of Artificial Stock Market in the Stock Market Tradi Mechanism

La lógica del mercado como desreguladora de la sociedad

In this article we will try to show, as its first objective, the notion of market logic within the dominant economic structure. The difference between the conception of natural and artificial market– as the economic system coincides today – is crucial if we want to understand the impact that the artificial market has today. The second objective is to make an approach of how the market logic is considered the only dominant economic structure of the society, proclaiming itself universal and denying any other possibility of economic system. Furthermore we will describe the emergence of alternatives that face the current model referring to the possibilities that brings the Social and Solidarity Economy. Also, we will review what should be the basics - from the SSE - into effect an economic system that is guided by a human logic and not by economic interests.Key words: market logic, market economy, Social Solidarity Economy.

Analyzing the Pareto Principle Based on the Artificial Stock Market

Analyzing the Pareto Principle Based on the Artificial Stock Market

Stock Prices in an Artificial Stock Market with Optimistic and Pessimistic Agents

This research aims to investigate, through simulation models, how the interaction among agents in an artificial stock market can affect the dynamics of asset prices. Thus, the study follows a different methodology for the analysis of prices by exploring the simulation of agents’ behavior in an artificial stock market. From the defining characteristics of heterogeneous agents, we set up an artificial stock market in which individuals interact, by demanding and supplying assets, driving the price of a stock to an equilibrium value. The results suggest that, under the assumption of utility maximizers agents with different expectations about future dividends, asset prices may under-react. The gradual change of prices observed in the sub-reaction confronts the efficient market hypothesis, in which all information is instantly

Simulation Research on Artificial Financial Market Based on Multiple Competitive Market-Makers

Most of the past studies about dealership market involved only one monoplistic market-maker. The paper aims to build an artificial financial market based on multiple competitive market makers on ANYLOGIC platform, in which one market-maker adopts BAYES learning rule to estimate the fundamental value and the other employs a rough method. In order to validate the effectiveness of dealers’ quotes, we carried out two group simulation experiment. The results show that the quote of each dealer can converge to the fundamental value with certain deviation. What’s more, the deviation of the market-maker with learning ability is smaller while the converging speed slower.

Bookworms and party animals: an artificial labour market with human and social capital accumulation

Data show that educated workers earn higher wages and are unemployed less often. Some researchers believe that education improves a worker's productivity (or human capital), making them more desirable on the job market, while others believe that it improves a worker's network (or social capital), giving them more information about lucrative openings and more resources to secure a job (such as references from peers). Much of the research on human and social capital focuses on quantifying the various impacts of schooling on workers and often overlooks how economic systems actually manage to produce those outcomes. This paper develops an agent-based complex adaptive system featuring formal schooling and on-the-job training, social networks, labour market search and durable employment contracts to explain the process linking education to labour market outcomes and economic performance in New Zealand (and similar economies). Sample simulations show that human capital accumulation explains many of the novel facts seen in the data, while social capital alone is not enough.

Analyzing the Pareto Principle Based on the Artificial Stock Market

Analyzing the Pareto Principle Based on the Artificial Stock Market