英文标题：
《Reality-check for Econophysics: Likelihood-based fitting of
  physics-inspired market models to empirical data》
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作者：
Nils Bertschinger and Iurii Mozzhorin and Sitabhra Sinha
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最新提交年份：
2018
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英文摘要：
  The statistical description and modeling of volatility plays a prominent role in econometrics, risk management and finance. GARCH and stochastic volatility models have been extensively studied and are routinely fitted to market data, albeit providing a phenomenological description only.   In contrast, the field of econophysics starts from the premise that modern economies consist of a vast number of individual actors with heterogeneous expectations and incentives. In turn explaining observed market statistics as emerging from the collective dynamics of many actors following heterogeneous, yet simple, rather mechanistic rules. While such models generate volatility dynamics qualitatively matching several stylized facts and thus illustrate the possible role of different mechanisms, such as chartist trading, herding behavior etc., rigorous and quantitative statistical fits are still mostly lacking.   Here, we show how Stan, a modern probabilistic programming language for Bayesian modeling, can be used to fit several models from econophysics. In contrast to the method of moment matching, which is currently popular, our fits are purely likelihood based with many advantages, including systematic model comparison and principled generation of model predictions conditional on the observed price history. In particular, we investigate models by Vikram & Sinha and Franke & Westerhoff, and provide a quantitative comparison with standard econometric models.
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中文摘要：
波动率的统计描述和建模在计量经济学、风险管理和金融学中发挥着重要作用。GARCH和随机波动率模型已经得到了广泛的研究，并且通常适用于市场数据，尽管只提供了现象学描述。相比之下，经济物理学领域从一个前提出发，即现代经济体由大量具有不同期望和激励的个体行为者组成。反过来，解释观察到的市场统计数据是从许多行动者的集体动态中产生的，这些行动者遵循的是异质的、但简单的、相当机械的规则。虽然此类模型产生的波动率动态定性地匹配了若干典型事实，从而说明了不同机制（如图表交易、羊群行为等）的可能作用，但仍然缺乏严格的定量统计拟合。这里，我们展示了一种用于贝叶斯建模的现代概率编程语言Stan如何用于拟合经济物理学中的多个模型。与目前流行的矩匹配方法相比，我们的拟合完全基于可能性，具有许多优点，包括系统的模型比较和根据观察到的价格历史原则生成模型预测。特别是，我们研究了Vikram&Sinha和Franke&Westerhoff的模型，并与标准计量经济学模型进行了定量比较。
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分类信息：

一级分类：Computer Science        计算机科学
二级分类：Computational Engineering, Finance, and Science        计算工程、金融和科学
分类描述：Covers applications of computer science to the mathematical modeling of complex systems in the fields of science, engineering, and finance. Papers here are interdisciplinary and applications-oriented, focusing on techniques and tools that enable challenging computational simulations to be performed, for which the use of supercomputers or distributed computing platforms is often required. Includes material in ACM Subject Classes J.2, J.3, and J.4 (economics).
涵盖了计算机科学在科学、工程和金融领域复杂系统的数学建模中的应用。这里的论文是跨学科和面向应用的，集中在技术和工具，使挑战性的计算模拟能够执行，其中往往需要使用超级计算机或分布式计算平台。包括ACM学科课程J.2、J.3和J.4（经济学）中的材料。
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一级分类：Quantitative Finance        数量金融学
二级分类：General Finance        一般财务
分类描述：Development of general quantitative methodologies with applications in finance
通用定量方法的发展及其在金融中的应用
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