Market Game Research Articles

The determinants of predatory trading: experimental evidence

We investigate the level and determinants of front-running in an experimental asset market game. Participants receive perfect signals about future order-flow that can be exploited to manipulate prices and generate profits. We quantify the changes in front-running activity as we vary the direction, concentration, and noise level of the scheduled order flow. Front-running activity increases with larger, more concentrated, or buy-side anticipated future orders and decreases with noise. Our findings suggest that the inclusion of a large stock in an index should be done in multiple stages to reduce the trading cost of passive investors tracking the index.

Certified data chats for future used car markets

Used car market platforms are interested in extending their offering from information provision to the whole customer journey. Providing certified data on the car’s state and history enables this extension by eliminating the need to physically inspect the car before buying it. Hence, communication and negotiations can move entirely to a used car platform to cover the entire value chain. How can such a market communication be designed when certified data come into play? This study designs and develops a certified data chat for the selective and controlled exchange of blockchain-based certified data in used car negotiations. An experimental market game is played with students to evaluate the usefulness of the chat. The study contributes to the augmentation of market communication with valuable and sensitive data exchange and demonstrates what a key component of a future used car market can look like. It offers three design principles and insight into why certified data chats are useful.

R&D investment and network effects: A dynamic model of the search engine market

ABSTRACT This paper considers R&D investment for quality improvement in a dynamic duopoly game in the search engine market. The aim is to determine the circumstances under which asymmetry between search engines (in terms of quality) tends to increase or decrease over time. I show that when the future sufficiently matters, the low-quality search engine can catch up with the high-quality engine by investing in quality. In contrast, when only the present matters, the high-quality search engine wins and the structure of the market transitions to a monopoly. I also show that a shift in asymmetry between firms can result in either an increase or decrease in consumer welfare, depending on the degree of substitutability between the two search engines.

An Examination to the Policy Market Game of the Inflation Reduction Act--A Response to Energy Revolution

U.S. Inflation Reduction Act as a federal response to energy revolution is a policy game to input least and output most for both legislators and interest groups, resulting in an equilibrium price for demanders of policies to exchange for effective supports of suppliers with re-election resources. The intention of legislators to supply effective supports is subject to ideology preferences, constituent interests and opportunity costs, while the intention of interest groups to purchase their favorite policies is subject to cost-efficient prices of re-election resources. Such an equilibrium theory for examining the Inflation Reduction Act market is able to reflect the U.S. partisan split of ideologies in environment topics, energy revolution in chief sectors of 50 states, U.S. legislative process to pass a bill, but also a huge step to achieve U.S. emission goals or to meet the temperature targets in 2030 that are set in in the Paris Agreement in 2016.

Optimisation of Game Strategies Under Information Asymmetry Between Insurance Companies and Consumers

The information asymmetry common in insurance markets has a profound impact on market operations and outcomes, and game theory provides a framework for understanding and responding to this problem. This paper explores the manifestation of information asymmetry in the insurance market and the application of game theory, as well as the optimisation of strategies between insurers and consumers. On the part of insurance companies, game strategies are optimised through measures such as improving information transparency, enhancing risk assessment and establishing long-term cooperative relationships, while consumers actively participate in the market game by enhancing their awareness of self-protection, improving their insurance knowledge and choosing reputable insurance companies. These optimisation measures help to improve the market environment, enhance market efficiency and achieve a win-win situation in the insurance market, laying the foundation for the healthy development and sustainable stability of the insurance market.

Findings from the Polish InsurTech market as a roadmap for regulators

The dynamic development of modern technologies has changed the rules of the game in the financial market, including the insurance sector. While introducing digital business models may bring certain advantages for insurers, there is a widespread expectation of consumers to manage their financial affairs anytime and anywhere. This article sets out by demonstrating recent phenomena on the insurance market arising from its digitalisation, i.e., automation, personalisation, insurance on-demand, machine learning & artificial intelligence, Big Data, concluding distance contracts; along with the threats to consumer safety they pose a cyber risk that may materialise at different stages of the digital insurance selling process. Further, to provide insights into how modern digital insurance markets work, the article presents the results of a study conducted by the authors on a representative sample of 2,136 respondents from Poland. The study allows one to identify certain behaviour patterns of customers in their dealings with providers of insurance products and services as well as their approach to technological innovations introduced by the traders. Crucially, the study shows that insurance consumers have a positive attitude towards the use of modern technologies in insurance, however, their knowledge on this subject is still limited. Specifically, insurance consumers tend to be more afraid of cyber risks than any legal risks resulting from deploying new technologies in the insurance sector. In conclusion, the article maps out key regulatory challenges related to ensuring consumer protection on digital insurance markets.

Retail competition among multi-type retail electric providers in social networks

Liberalization of the electricity retail market has intensified the competition among different types of retail electricity providers (REPs), leading REPs to pay more attention to electricity consumers' (ECs') preferences for electricity service quality, such as reliability and flexibility. In addition, social learning also greatly influences consumers' electricity purchase strategies. Therefore, this paper models the price and service quality competition among multi-type REPs in a two-layer electricity retail market network that integrates electricity trading and consumer social learning. Firstly, we construct a two-layer network that transforms the dynamic process of ECs switching REPs and changing neighbors into the reconfiguration of the network structure. The upper layer is a bipartite network to express the dynamic transaction between REPs and ECs, while the lower layer is a random network to represent the learning interaction between ECs. Secondly, considering network externalities, we model a retail competition based on price and ECs' preferences for electricity service quality in the network above and get the equilibrium solutions in different scenarios by simulating the electricity consumption data of 600 London households. The results demonstrate that network externalities hinder the transmission of price signals, and the density of the EC network affects the market game result, while the update speed of the EC network has little effect. This study provides theoretical support for multi-agent decision-making in the electricity retail market.

Lessons drawn from a stock market game

A new approach in educational science promotes student involvement to replace frontal lectures. The objective is to create a cooperative environment in class applying the new educational techniques. Gamification is one effective solution to the problem. I used the stock market game described here to introduce my students to the world of trading systems and the basic rules of financial behaviour in a playful but challenging environment. After the introduction and a description of the literature used, this paper describes how the game is played. I have been playing the game in the same order for years, which has had a dual advantage. On the one hand, based on practical experience, introducing new skills and knowledge is best done in an established order both for the fluency of the game and the effective processing of the new knowledge. On the other hand, the identical order of playing the games is important for subsequent statistical analysis and drawing the conclusions. The analysis in the paper has been made using a simple statistical descriptive methodology. By their multiplicity, the 136 teams in the sample would have been sufficient to use deductive methodology, however, the participating students belonged to different groups (undergraduate and post-graduate, reading economics, reading other subjects), so the number of the individual teams has become lower. Also, if you look at the number of individual games, i.e. the 34-component sample, deductive statistics will produce more limited results. It has become clear from the results so far that post-graduate students, particularly those reading non-economics subjects, were more prone to making emotional rather than rational decisions during the course of the game. Psychological elements had a more emphatic impact on their decisions compared to their peers who had a profound knowledge of economics.

Information Sharing in Supply Chains from the Market Game Perspective

Information Sharing in Supply Chains from the Market Game Perspective

Distributed Online Learning Algorithm for Noncooperative Games Over Unbalanced Digraphs.

This article investigates constrained online noncooperative games (NGs) of multiagent systems over unbalanced digraphs, where the cost functions of players are time-varying and are gradually revealed to corresponding players only after decisions are made. Moreover, in the problem, the players are subject to local convex set constraints and time-varying coupling nonlinear inequality constraints. To the best of our knowledge, no result about online games with unbalanced digraphs has been reported, let alone constrained online games. To seek the variational generalized Nash equilibrium (GNE) of the game online, a distributed learning algorithm is proposed based on gradient descent, projection, and primal-dual methods. Under the algorithm, sublinear dynamic regrets and constraint violations are established. Finally, online electricity market games illustrate the algorithm.

Distributed algorithm for nonsmooth multi-coalition games and its application in electricity markets

In this paper, we study distributed nonsmooth multi-coalition games (MCGs), where the players are subject to local convex set constraints and coupled inequality constraints. Different from existing distributed MCGs, our problem involves nonsmooth payoff functions and constraints, relaxes the requirement for communication networks, and only relies on the strict monotonicity of pseudo-gradients. Due to the nonsmoothness of payoff functions and constraints, the weaker communication networks as well as the coexistence of cooperation and competition among players, existing generalized Nash equilibrium (GNE) seeking algorithms cannot solve the problem. Also, they pose obstacles to the algorithm design and analysis, mainly because of the non-global Lipschitz continuity of subgradients and the unconnectedness of subnetworks. To seek the variational GNE (vGNE) of the nonsmooth MCGs, we design a distributed subgradient-based algorithm. We prove that the algorithm converges to the exact vGNE of the nonsmooth MCGs from any initial states. Finally, our result is applied to the electricity market games (EMGs) of smart grids.

Dampak Oligopoli Dan Industri Modern Terhadap Masyarakat

Oligopoly is a form of imperfect market competition where the supply of a product is controlled by a number of companies. In general the number of companies is more than two but less than ten. Each company decides its own policy and all company actions as price changes will be taken into account by other companies, because every company in the market believes in the policy of a company. This business will affect the income and profits of other businesses. In an oligopoly market, each company positions itself as part of a market game so that its profit base is based on the behavior of its competitors. So all promotional efforts, advertising, new product introductions, price changes, etc. This is done with the aim of luring consumers away from competitors. The main cause of this oligopoly is the successful management of business operations to achieve economies of scale which leads to the effectiveness and success of sales promotions in the long term, because it will increase market share. Oligopoly activities are often with the aim of inhibiting potential business participation in the market. More than that, it also aims to enjoy normal profits below the maximum by setting a limited selling price so that price competition between business actors who carry out an oligopoly does not exist.

The Renaissance of Russian pharmaceutical market (2000-2004). Report II. The Pharma servants of Russia

The article (the third one of authors cycle of historical studies of medication supply and pharmaceutical business) examines period of economic renaissance of the Russian pharmaceutical market in the first years of third millennium. The state of market according data of Russian analytical agencies, medical periodicals and recollections of participants is considered. The article consists of three reports. In the first report the issue was the "field players" of pharmaceutical market, and in the second one - all the personnel serving market game, making it possible, their reflections on their new, post-Soviet experience of life in private business.

Operating Strategy of LNG Terminal in Interdependent Electricity and Natural Gas Markets

With the ever strengthening interdependence between electricity and natural gas (NG) systems, the outcomes of the two energy markets could be affected by market entities from both markets. The existing studies mainly discuss the strategic behaviors of market entities participating in directly the two energy markets, lacking the concentration on the market entities participating in one single market while they could still pose impacts on the other market via the interdependence between the two markets. This paper studies the operating strategy of liquified NG (LNG) terminal, by describing the problem as a NG market game and an electricity market game. The problem is then reformulated as a bi-level single-leader multi-follower mix-integer programming (MIP) model where the LNG terminal acts as the leader while the NG fired power plants (NGPPs) as the followers. The model could be converted to a single-level one with the value-function method, and the interaction between the leader and followers is addressed with the sample-based algorithm, combined with the diagonalization algorithm to find the equilibrium among followers. The case studies further demonstrate the feasibility and effectiveness of the proposed methodology and illustrate the outcomes of the interdependent electricity and NG markets with the strategic LNG terminal.

Nash Equilibrium Seeking Algorithm Design for Distributed Nonsmooth Multicluster Games Over Weight-Balanced Digraphs.

In this article, we study the multicluster games over weight-balanced digraphs, where the cost functions of all players are nonsmooth. Besides, in the problem, not only are the decisions of all players constrained by heterogeneous local constraints but also the decisions of players in the same cluster are constrained by coupling constraints. Due to the nonsmooth cost functions, the coupling constraints, the general local convex constraints, and the weight-balanced digraphs, existing Nash equilibrium seeking algorithms cannot solve our problem. In order to seek the Nash equilibrium of the game, we design a distributed algorithm based on subgradient descent, differential inclusions, and projection operations. In the algorithm, a distributed learning strategy is embedded for the players to estimate the decisions of other players. Moreover, we analyze the asymptotical convergence of the algorithm via set-valued LaSalle invariance principle. Finally, a numerical simulation about electricity market games is presented to illustrate the effectiveness of our result.

Dampak Oligopoli Terhadap Ekonomi Masyarakat Di Wilayah Surabaya

Oligopoly is a form of market structure where there are a few producers or dominate the market for a particular product or service. In an oligopoly, there are a few large companies that control most of the supply of goods or services, thus having the ability to influence prices and control competition. In an oligopoly market, each company will position itself as part of the market game. This certainly needs to be done because the profits they get are very dependent on their competing companies. Every policy taken by one company will greatly influence other companies so that competition will become increasingly fierce in terms of price and quality.

A distributed strategy for games in Euler–Lagrange systems with actuator dead zone

This paper explores a distributed Nash equilibrium (NE) seeking problem for games in which the involved players are of Euler–Lagrange (EL) dynamics with actuator dead zone. To find NE of such games, a novel distributed algorithm with a dynamical dead-zone compensator is proposed. The compensating module in this new strategy is regarded as a fast dynamics that rapidly addresses the effect caused by actuator dead-zone characteristic. The other module of this algorithm is a slow optimizer that enables the actions of EL players to approach the NE. Since the designed strategy is a two-time-scale model, semi-global practical asymptotic stability of this strategy can be obtained by utilizing the generalized singular perturbation method. Finally, an electricity market game with six turbine-generator dynamics is utilized to validate the theoretical result of the proposed method.

Optimal Trading Mechanism Based on Differential Privacy Protection and Stackelberg Game in Big Data Market

Big data has become a fundamental resource and a commodity in economic activities, thus, it is necessary to build a market model capable of supporting efficient data trading. However, two major challenges remain. Firstly, researches have considered constructing data trading mechanisms, while few of them are based on the method of measuring data value in multiple dimensions. Secondly, a data market involved an intermediary trading platform (i.e., a third party) which is honest but curious, results may be obtained due the the leakage of private information. In this paper, we design TM-OUE, a data trading mechanism based on Optimized Unary Encoding that enables reasonable trading mechanism and protects the privacy of data trading. First of all, we combine qualitative and quantitative methods to measure the value of data in multiple dimensions and formulate data trading model between the data provider and data users. Then, we utilize an Optimized Unary Encoding (OUE) protocol to protect the privacy of the data trading mechanism. Based on the above steps, we develop a two-stage single leader multi-follower Stackelberg game to jointly maximize profits of the data provider and data users. Experimental results demonstrate that TM-OUE can offer appropriate price for data and maximize benefits both for data providers and data users, which guarantees fair data trades while protecting privacy.

How bad is the merger paradox?

The merger paradox is a classic, counter-intuitive result from the literature of Industrial Organization saying that merging firms typically experience a decline in their overall profit compared to their total pre-merger profit. This phenomenon is more striking in small oligopolistic markets, where mergers increase market concentration and may hence trigger a substantial increase in prices. In this paper, we investigate the severity of the merger paradox in Cournot oligopoly markets. Namely, we study the worst-case magnitude of this profit loss in quantity-setting market games. We consider convex, asymmetric production costs for the firms, and we show that the profit loss can be substantial even in small markets. That is, two merging firms can lose half of their pre-merger profit, but no more than half in markets with concave demand functions. On the positive side, we show that in markets with affine demand two firms can never lose more than 1/9 of their profit when merging, and this bound is tight. We also study the asymptotic loss in larger markets, where it is easy to show that the profit loss can be arbitrarily large when multiple firms merge; we give bounds that characterize the profit loss from a merger as a function of the market size and the number of merging firms.

Contributing with private bundles to public goods

We extend to multiple private commodities the seminal model by Bergstrom et al. (J Public Econ 29:25–49, 1986) on the private provision of public goods. Considering the relative value of the aggregate donations, we define a notion of equilibrium and show its existence. We analyze the effects of resource redistributions on the equilibrium outcome, identifying conditions that guarantee neutrality. We study some further properties of the contribution equilibrium, and provide a strategic market game approach, defining a sequence of non-cooperative games whose equilibria converge to an equilibrium of the economy.