Roman Šperka

Transaction costs influence on the stability of financial market: agent-based simulation

We implement an agent-based simulation of financial market model. Agent-based simulations are used nowadays as an alternative to the traditional models, based on predetermined equilibrium state theory. Agent technology brings some kind of local intelligence and rational expectations to the decision support system of financial market participants. Agents follow technical and fundamental trading rules to determine their speculative investment positions. We consider direct interactions between speculators and they may decide to change their trading behaviour. If a technical trader meets a fundamental trader and they realize that fundamental trading has been more profitable than technical trading in recent past, the probability that the technical trader switches to the fundamental trading rules is relatively high. In particular the influence of transaction costs is studied in this paper. Transaction costs can be increased by the off-market regulation (for example in the form of taxes) on financial market stability, by overall volume of trade and other market characteristics. The paper shows a positive impact of suitable transaction costs on the financial market stability in the long run.

Control Loop Model of Virtual Company in BPM Simulation

The motivation of the paper is to introduce agent-based technology in the business process simulation. As in other cases, such simulation needs sufficient input data. However, in the case of business systems, real business data are not always available. Therefore, multi-agent systems often operate with randomly (resp. pseudo randomly) generated parameters. This method can also represent unpredictable phenomena. The core of the paper is to introduce the control loop model methodology in JADE business process simulation implementation. At the end of this paper the analysis of agent-based simulation outputs through process mining methods and methods for analysis of agents’ behavior in order to verify the correctness of used methodology is presented. The business process simulation inputs are randomly generated using the normal distribution. The results obtained show that using random number generation function with normal distribution can lead to the correct output data and therefore can be used to simulate real business processes.

An influence of random number generation function to multiagent systems

The paper deals with modeling and simulation of business processes. A multiagent system was implemented as a tool to manage the simulation. Multiagent systems often operate with random (respectively pseudorandom) generated parameters in order to represent unpredictable phenomena. The aiml of the paper is to show the influence of different random number generation functions to the real multiagent system outputs. It is obvious, that outputs of the multiagent system simulation differs from turn to turn, but the motivation was to find, if the differences are significant. An accurate number of agents with the same parameters were used for each case, with different kinds of randomness while generating agents internal state attributes. The results obtained show that using inappropriate random number generation function leads to significant output data distortion, so the generation function selection must be done very carefully.

Extraction of Agent Groups with Similar Behaviour Based on Agent Profiles

This paper deals with the log files suitable to extract valuable information about agents and their behaviour from agent-based simulation in a model of virtual company. Such information, presented in a transparent way, can be used as a support for simulation verification to achieve the suitable design of the proposed system. Hence, based on the similar behaviour (represented by extracted sequences) of agents, we are able to construct models which explain certain aspects of agent behaviour. Moreover, we can extract agent profiles based on behaviour and find latent ties between different agent groups with similar behaviours. The paper extends the results of our previous works about sequence extraction and comparison. The approach for agent network construction based on agent profiles is described. Two different methods were used for construction of agent network. One method uses cosine similarity and graph partitioning and the second self organization maps and Euclidean similarity for agent relations. Each of these methods has its advantages and disadvantages which are summarized in the paper and presented in the form of the visualization of relations between agents.

Microeconomic Demand Functions Implementation in Java Experiments

The aim of this paper is to introduce microeconomic demand functions (Marshallian demand function and Cobb-Douglas utility function) in Java simulation experiments. The motivation is to use these function as a core element in a seller-to-customer price negotiation in an agent-based simulations. Furthermore, multi-agent model is proposed and implemented in Java to serve as a simulation framework to support the virtual company trading processes. The main background of this framework is to be integrated in management information systems as a decision support module. The paper firstly presents some of the existing principles about consumer behavior, agent-based modeling and simulation in the same area and demand function theory. Secondly, presents multi-agent model and demand functions negotiations. Lastly, depicts some of the simulation results in a trading processes throughout one year of selling commodities to consumers. The results obtained show that in some metrics the demand functions could be used to predict the trading results of a company.

MAREA – From an Agent Simulation Application to the Social Network Analysis☆

Abstract The aim of the paper is to present an enhanced software simulation application based on a trading company control loop and to validate agents’ behavior from simulation experiments using simple Petri net, and social network analysis. The main purpose of the application is to improve existing decision support systems with the use of a simulation. The ERP system using the REA ontology approach is used as a measuring element in the application. The system has been developed in cooperation between Silesian University in Opava, School of Business Administration in Karvina, Czech Republic and REA technology Copenhagen, Denmark. After the prototype tests at the end of the year 2011, we presented it at the beginning of 2012 for the very first time. Firstly, the enhanced framework with several types of agents and negotiation possibilities is described. This is followed by the decision function explanation, which is the core of the price negotiation. Secondly, a brief look on the graphical user interface and main parts of MAREA simulation monitor is provided. Brief results of the model validation performed by means of ProM software are presented. To conclude, MAREA is a software application with simulation possibilities, which can be used to present trading behavior of a company for decision support.

Trading Agents’ Negotiation in Business Management Using Demand Functions: Simulation Experiments with Binomial Distribution☆

Abstract The aim of this paper is to propose an experimental business management approach to cover a seller-to-customer price negotiation in an agent-based simulations. The core element in this approach is the price negotiation. We used Marshallian demand function and a Cobb-Douglas utility function in the negotiation process. Moreover, multi-agent model is proposed and implemented in Jade development platform. Its task is to serve as a simulation framework for the trading processes execution. The main background of this framework is to be integrated in management information systems as a decision support module for a prediction of key performance indicators of a virtual company. A binomial distribution was used in presented experiments to simulate the quantity of negotiated commodities. The paper firstly presents some of the existing principles about consumer behavior, agent-based modeling and simulation in the same area and demand function theory. Secondly, presents multi-agent model and demand functions negotiations more formally. Finally, shows some of the simulation results in a trading processes throughout one year of selling commodities to consumers. The results obtained show that the demand functions could be properly used to simulate trading processes.

Application of a Business Economics Decision-Making Function in an Agent Simulation Framework

The aim of the paper is to introduce a novel multi-agent simulation approach and its application allowing to deal with the trading processes of a virtual company. The motivation is to use implemented simulation framework as a basic part of an information system, operating as an integrated component of an actual ERP system implemented within a company so as to investigate and to predict the chosen business metrics of a company. Such a system serves to enable the management of a company to support their decision-making processes. The paper firstly presents the contemporary importance of simulation method. Secondly, the paper characterizes concrete multi-agent model of a virtual company, agents, and the decision-making function. Thirdly, the simulation framework application MAREA will be introduced. Lastly, the simulation results and their comparison with actual data, and the verification possibilities of the simulation model are described. It will be demonstrated that the proposed approach to customer behaviour in an agent-based simulation model could properly contribute to a better decision-making process.

Advantages of Application of Process Mining and Agent-Based Systems in Business Domain

Businesses and business decisions are getting driven by the information gained from the data more and more nowadays. The number of businesses supporting and managing their processes through the use of information systems and new technologies is growing every day. Even though, there is still a lot of rigidity in the implementation of new technologies. There is a great potential for the use of two of so far not so common disciplines in a business domain, which complement each other. That are process mining and multi-agent systems. Thus, in this paper, we are going to demonstrate the possible utilization of both process mining and multi-agent approaches in business domain. To demonstrate it, we use multi-agent simulator of trading company called MAREA. We analyzed implemented company model with the use of process mining. Process mining was used in two different ways. Firstly, to validate the workflow of the process model. Secondly, to analyze bottlenecks in company’s business processes and the impact of marketing campaigns on these business processes.

Part-time Jobs: Opportunity or Obstacle? Case of the Moravian-Silesian Region

Abstract cBackground and Purpose: Part-time employment could be seen as a modern form of employment or a type of innovative organizational change. The average share of part-time jobs in the Czech Republic in the observed period of 2004-2016 was 3.9 % according to the OECD, in comparison to the average OECD value of 16.6%. The main question to arise was, are there any regional differences? The presented conclusions are based on a regional study in the Moravian-Silesian Region (MSR) in the Czech Republic where the median value of part- time jobs is 10%. The main goal is to evaluate the regional level of part-time job offers and identify the main opportunities and obstacles which cause the low number of these job positions. Design/Methodology/Approach: The paper is based on a quantitative study using a questionnaire-based survey, comprising 215 respondents - owners of small and medium-sized enterprises (SMEs) in the Moravian-Silesian Region in the Czech Republic. The survey consists of 16 questions in three main areas: (i) Entrepreneurial motivation (1 item), (ii) External factors - Labour market problems (4 items), and (iii) Internal factors. Secondary information such as the results of earlier studies and regional government websites were used for data results comparison. All variables are compared in the context of the branch of business, number of employees, turnover, and age. Finally, a factor analysis was used to find the main way how to improve part-time job offers. Results: The variety of businesses and different regional locations opens up space for discussion regarding parttime job support. A factor analysis found five significant issues, which could affect local labour market and company behaviour. Conclusion: The added value of the paper can be seen in the factor identification, where internal willingness to support part-time employment and qualification growth as organizational change must be in first place.