44,220 research outputs found
Risk-Seeking versus Risk-Avoiding Investments in Noisy Periodic Environments
We study the performance of various agent strategies in an artificial
investment scenario. Agents are equipped with a budget, , and at each
time step invest a particular fraction, , of their budget. The return on
investment (RoI), , is characterized by a periodic function with
different types and levels of noise. Risk-avoiding agents choose their fraction
proportional to the expected positive RoI, while risk-seeking agents
always choose a maximum value if they predict the RoI to be positive
("everything on red"). In addition to these different strategies, agents have
different capabilities to predict the future , dependent on their
internal complexity. Here, we compare 'zero-intelligent' agents using technical
analysis (such as moving least squares) with agents using reinforcement
learning or genetic algorithms to predict . The performance of agents is
measured by their average budget growth after a certain number of time steps.
We present results of extensive computer simulations, which show that, for our
given artificial environment, (i) the risk-seeking strategy outperforms the
risk-avoiding one, and (ii) the genetic algorithm was able to find this optimal
strategy itself, and thus outperforms other prediction approaches considered.Comment: 27 pp. v2 with minor corrections. See http://www.sg.ethz.ch for more
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Asset price dynamics with small world interactions under hetereogeneous beliefs
We propose a simple model of a financial market populated with heterogeneous agents. The market represents a network with nodes symbolizing the agents and edges standing for connections between them, thus, embodying local interactions in the market. By local interactions we mean any kind of interplay between the decisions of the agents unaffected by the market mechanism and unrelated to the physical distance between the agents. Using the rewiring procedure we restructure a network from regular lattice to random graph by varying the probability of the agents to switch from one trading strategy to another. We study how the network structure influences the asset price dynamics. The results show that for some intermediate values of the probability to switch, corresponding to a small world network, the price dynamics become reminiscent to the real. While for the boundary values of the probability the dynamics lacks some typical features of the real financial markets.local interactions, networks, small world, heterogeneous beliefs, price dynamics, bifurcations, chaos
Comparative study of central decision makers versus groups of evolved agents trading in equity markets
This paper investigates the process of deriving a single decision solely based on the decisions made by a population of experts. Four different amalgamation processes are studied and compared among one another, collectively referred to as central decision makers. The expert, also referred to as reference, population is trained using a simple genetic algorithm using crossover, elitism and immigration using historical equity market data to make trading decisions. Performance of the trained agent population’s elite, as determined by results from testing in an out-of-sample data set, is also compared to that of the centralized decision makers to determine which displays the better performance. Performance was measured as the area under their total assets graph over the out-of-sample testing period to avoid biasing results to the cut off date using the more traditional measure of profit. Results showed that none of the implemented methods of deriving a centralized decision in this investigation outperformed the evolved and optimized agent population. Further, no difference in performance was found between the four central decision makersAgents, Decision Making, Equity Market Trading, Genetic Algorithms, Technical Indicators
Implementation of a Port-graph Model for Finance
In this paper we examine the process involved in the design and
implementation of a port-graph model to be used for the analysis of an
agent-based rational negligence model. Rational negligence describes the
phenomenon that occurred during the financial crisis of 2008 whereby investors
chose to trade asset-backed securities without performing independent
evaluations of the underlying assets. This has contributed to motivating the
search for more effective and transparent tools in the modelling of the capital
markets.
This paper shall contain the details of a proposal for the use of a visual
declarative language, based on strategic port-graph rewriting, as a visual
modelling tool to analyse an asset-backed securitisation market.Comment: In Proceedings TERMGRAPH 2018, arXiv:1902.0151
ATTac-2000: An Adaptive Autonomous Bidding Agent
The First Trading Agent Competition (TAC) was held from June 22nd to July
8th, 2000. TAC was designed to create a benchmark problem in the complex domain
of e-marketplaces and to motivate researchers to apply unique approaches to a
common task. This article describes ATTac-2000, the first-place finisher in
TAC. ATTac-2000 uses a principled bidding strategy that includes several
elements of adaptivity. In addition to the success at the competition, isolated
empirical results are presented indicating the robustness and effectiveness of
ATTac-2000's adaptive strategy
Flexible Decision Control in an Autonomous Trading Agent
An autonomous trading agent is a complex piece of software that must operate in a competitive economic environment and support a research agenda. We describe the structure of decision processes in the MinneTAC trading agent, focusing on the use of evaluators – configurable, composable modules for data analysis and prediction that are chained together at runtime to support agent decision-making. Through a set of examples, we show how this structure supports sales and procurement decisions, and how those decision processes can be modified in useful ways by changing evaluator configurations. To put this work in context, we also report on results of an informal survey of agent design approaches among the competitors in the Trading Agent Competition for Supply Chain Management (TAC SCM).autonomous trading agent;decision processes
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Introducing Competition in the French Electricity Supply Industry: The Destabilisation of a Public Hierarchy in an Open Institutional Environment
The French electricity supply industry is characterized by a vertically integrated monopoly and public ownership and when the government introduced market rules, it was with the aim of preserving the integration of the public incumbent as a national champion. This had two paradoxical effects in favour of competition development and the building of safeguards for entrants
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