经济与金融中随机波动的基于模型与经验分析
Model-based and empirical analyses of stochastic fluctuations in economy and finance
AI总结：
本研究利用统计力学与信息论工具，通过基于统计的建模与经验分析，探讨金融与经济系统的复杂性与随机性，核心贡献在于推导并分析相关变量的概率分布函数以揭示其时间依赖性。
摘要：
本工作的目标是利用统计力学和信息论工具，研究金融与经济系统的复杂性、不对称性、随机性和非线性。更准确地说，本论文涉及基于统计的建模和经验分析，应用涵盖金融、预测、生产过程和博弈论。在这些领域中，概率分布的时间依赖性是首要关注点，并且对于模型系统可以进行测量或精确计算。相关系数和矩是描述随机变量的动力学和相互关联的有用物理量。然而，只有当变量的概率分布函数已知时，才能实现全面的研究；其推导是本工作的主要重点之一。
英文摘要：
The objective of this work is the investigation of complexity, asymmetry, stochasticity and non-linearity of the financial and economic systems by using the tools of statistical mechanics and information theory. More precisely, this thesis concerns statistical-based modeling and empirical analyses with applications in finance, forecasting, production processes and game theory. In these areas the time dependence of probability distributions is of prime interest and can be measured or exactly calculated for model systems. The correlation coefficients and moments are among the useful quantities to describe the dynamics and the correlations between random variables. However, the full investigation can only be achieved if the probability distribution function of the variable is known; its derivation is one of the main focuses of the present work.
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。
