摘要翻译：
本文提出了外部资源再分配的经济增长融合机制。它导致企业在规模上的Zipf分布，由于规模依赖效应而转向伸展指数，并预测个人收入在个人之间的指数分布。本文还提出了基于热（短时间）和冷（长时间）自由度分离的描述市场波动的新方法，它预测了稳定尾指数mu=3(mu=2)的波动的帐篷状分布。该理论预测了可观察到的分布不对称性，以及它的大小依赖关系。在金融市场中，该理论解释了第一次市场磨坊模式、条件分布、D-smile、Z型响应、条件双重动力学、偏态等。我们导出了一组Langeven方程组，它预测了价格变化对交易量和跳跃后波动模式的对数依赖性。我们计算了不同时间尺度下的价格分布参数、相关函数和Hurst指数。在很大程度上，价格经历分数布朗运动，长期持续和反持续行为的混乱切换，并计算了相应的概率、响应函数和风险。
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英文标题：
《Theory of market fluctuations》
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作者：
S.V. Panyukov
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最新提交年份：
2008
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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：Physics and Society        物理学与社会
分类描述：Structure, dynamics and collective behavior of societies and groups (human or otherwise). Quantitative analysis of social networks and other complex networks. Physics and engineering of infrastructure and systems of broad societal impact (e.g., energy grids, transportation networks).
社会和团体（人类或其他）的结构、动态和集体行为。社会网络和其他复杂网络的定量分析。具有广泛社会影响的基础设施和系统（如能源网、运输网络）的物理和工程。
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英文摘要：
  We propose coalescent mechanism of economic grow because of redistribution of external resources. It leads to Zipf distribution of firms over their sizes, turning to stretched exponent because of size-dependent effects, and predicts exponential distribution of income between individuals. We also present new approach to describe fluctuations on the market, based on separation of hot (short-time) and cold (long-time) degrees of freedoms, which predicts tent-like distribution of fluctuations with stable tail exponent mu=3 (mu=2 for news). The theory predicts observable asymmetry of the distribution, and its size dependence. In the case of financial markets the theory explains first time market mill patterns, conditional distribution, D-smile, z-shaped response, conditional double dynamics, the skewness and so on. We derive the set of Langeven equations, which predicts logarithmic dependence of price shift on trading volume and volatility patterns after jumps. We calculate parameters of price distributions, correlation functions and Hurst exponents at different time scales. At large times the price experiences fractional Brownian motion with chaotically switching of long-time persistent and anti-persistent behavior, and we calculate corresponding probabilities, response functions, and risks.
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PDF链接：
https://arxiv.org/pdf/0804.4191