Model-based and empirical analyses of stochastic fluctuations in economy and finance

Rubina Zadourian
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引用次数: 0

Abstract

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.
基于模型和经验的经济和金融随机波动分析
这项工作的目标是利用统计力学和信息论的工具,研究金融和经济系统的复杂性、不对称性、随机性和非线性。更确切地说,本论文涉及基于统计的建模和实证分析,并应用于金融、预测、生产过程和博弈论等领域。在这些领域中,概率分布的时间依赖性是人们最感兴趣的问题,可以对模型系统进行测量或精确计算。相关系数和矩是描述随机变量间动态和相关性的有用量。然而,只有在已知变量的概率分布函数的情况下,才能对其进行全面研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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