基于Agent的远程记忆非线性随机模型推理
Agent based reasoning for the non-linear stochastic models of long-range memory
摘要：
我们通过引入可变事件时间尺度扩展了Kirman模型。拟议的灵活时间尺度相当于在金融市场中观察到的可变交易活动。随机版本的扩展Kirman的代理为基础的模型相比，在金融市场的长程记忆的非线性随机模型。基于代理的模型提供匹配的宏观描述作为一个微观推理的早期提出的随机模型表现出幂律统计。
英文摘要：
We extend Kirman's model by introducing variable event time scale. The proposed flexible time scale is equivalent to the variable trading activity observed in financial markets. Stochastic version of the extended Kirman's agent based model is compared to the non-linear stochastic models of long-range memory in financial markets. Agent based model providing matching macroscopic description serves as a microscopic reasoning of the earlier proposed stochastic model exhibiting power law statistics.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
