摘要翻译:
本文应用Agent系统建立了一个非线性分布式信号处理模型。在以实际货币兑换时间序列为代表的随机时变环境中,研究了由预测时间尺度的多样化趋势跟随者组成的智能体系统的演化。分析了非相互作用和相互作用情况下的时变总体及其统计特性。我们的分析结果以平均寿命时间、平均效用和相应分布的形式给出。它们表明,种群容易受到Agent间相互作用的强度和形式的影响。我们相信,我们的结果将有助于鲁棒自适应预测系统的发展。
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英文标题:
《Multi-agent based analysis of financial data》
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作者:
Tom\'a\v{s} Tok\'ar, Denis Horv\'ath, Michal Hnatich
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最新提交年份:
2011
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分类信息:
一级分类:Quantitative Finance 数量金融学
二级分类:Statistical Finance 统计金融
分类描述:Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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一级分类:Physics 物理学
二级分类:Adaptation and Self-Organizing Systems 自适应和自组织系统
分类描述:Adaptation, self-organizing systems, statistical physics, fluctuating systems, stochastic processes, interacting particle systems, machine learning
自适应,自组织系统,统计物理,波动系统,随机过程,相互作用粒子系统,机器学习
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一级分类:Physics 物理学
二级分类:Data Analysis, Statistics and Probability 数据分析、统计与概率
分类描述:Methods, software and hardware for physics data analysis: data processing and storage; measurement methodology; statistical and mathematical aspects such as parametrization and uncertainties.
物理数据分析的方法、软硬件:数据处理与存储;测量方法;统计和数学方面,如参数化和不确定性。
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一级分类:Quantitative Finance 数量金融学
二级分类:Trading and Market Microstructure 交易与市场微观结构
分类描述:Market microstructure, liquidity, exchange and auction design, automated trading, agent-based modeling and market-making
市场微观结构,流动性,交易和拍卖设计,自动化交易,基于代理的建模和做市
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英文摘要:
In this work the system of agents is applied to establish a model of the nonlinear distributed signal processing. The evolution of the system of the agents - by the prediction time scale diversified trend followers, has been studied for the stochastic time-varying environments represented by the real currency-exchange time series. The time varying population and its statistical characteristics have been analyzed in the non-interacting and interacting cases. The outputs of our analysis are presented in the form of the mean life-times, mean utilities and corresponding distributions. They show that populations are susceptible to the strength and form of inter-agent interaction. We believe that our results will be useful for the development of the robust adaptive prediction systems.
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PDF链接:
https://arxiv.org/pdf/1110.2603