摘要翻译：
经济学和其他科学的现代研究需要存储、共享和复制实验结果和方法的能力，这些结果和方法通常是多学科的，并产生大量的数据。鉴于各种知识的复杂性和交互作用日益增加，必须确定一个平台，以适当支持协作研究和跟踪数据的来源、准确性和使用情况。本文首先定义了一套利用科学原理的方法，并倡导这些方法在多学科、计算机密集领域如计算金融中的重要性。本文的下一部分定义了一类被称为科学支持系统的系统，与生物信息学、物理学和工程学等其他研究领域的应用相比较。我们概述了一组基本概念，并列出了我们的目标和动机，以利用这些系统来实现大规模调查，即经济学中的“人群驱动科学”。本文的核心分五个步骤提供了FRACTI的轮廓。首先，我们提出了与财务内在的科学支持系统相关的定义，并描述了财务用例的共同特征。第二步集中于通过可共享实体的定义（称为贡献）可以交换的内容。第三步是描述概念框架构建块的分类系统，称为方面。第四步介绍了元模型，它将支持数据片段的来源跟踪、表示和模拟。最后，我们描述了FRACTI的主要优势：科学研究方法在计算金融、大规模协作和模拟中的应用。
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英文标题：
《Supporting Crowd-Powered Science in Economics: FRACTI, a Conceptual
  Framework for Large-Scale Collaboration and Transparent Investigation in
  Financial Markets》
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作者：
Jorge Faleiro, Edward Tsang
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最新提交年份：
2018
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Computational Finance        计算金融学
分类描述：Computational methods, including Monte Carlo, PDE, lattice and other numerical methods with applications to financial modeling
计算方法，包括蒙特卡罗，偏微分方程，格子和其他数值方法，并应用于金融建模
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一级分类：Economics        经济学
二级分类：Econometrics        计量经济学
分类描述：Econometric Theory, Micro-Econometrics, Macro-Econometrics, Empirical Content of Economic Relations discovered via New Methods, Methodological Aspects of the Application of Statistical Inference to Economic Data.
计量经济学理论，微观计量经济学，宏观计量经济学，通过新方法发现的经济关系的实证内容，统计推论应用于经济数据的方法论方面。
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一级分类：Economics        经济学
二级分类：General Economics        一般经济学
分类描述：General methodological, applied, and empirical contributions to economics.
对经济学的一般方法、应用和经验贡献。
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一级分类：Quantitative Finance        数量金融学
二级分类：Economics        经济学
分类描述：q-fin.EC is an alias for econ.GN. Economics, including micro and macro economics, international economics, theory of the firm, labor economics, and other economic topics outside finance
q-fin.ec是econ.gn的别名。经济学，包括微观和宏观经济学、国际经济学、企业理论、劳动经济学和其他金融以外的经济专题
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一级分类：Quantitative Finance        数量金融学
二级分类：Trading and Market Microstructure        交易与市场微观结构
分类描述：Market microstructure, liquidity, exchange and auction design, automated trading, agent-based modeling and market-making
市场微观结构，流动性，交易和拍卖设计，自动化交易，基于代理的建模和做市
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英文摘要：
  Modern investigation in economics and in other sciences requires the ability to store, share, and replicate results and methods of experiments that are often multidisciplinary and yield a massive amount of data. Given the increasing complexity and growing interaction across diverse bodies of knowledge it is becoming imperative to define a platform to properly support collaborative research and track origin, accuracy and use of data. This paper starts by defining a set of methods leveraging scientific principles and advocating the importance of those methods in multidisciplinary, computer intensive fields like computational finance. The next part of this paper defines a class of systems called scientific support systems, vis-a-vis usages in other research fields such as bioinformatics, physics and engineering. We outline a basic set of fundamental concepts, and list our goals and motivation for leveraging such systems to enable large-scale investigation, "crowd powered science", in economics. The core of this paper provides an outline of FRACTI in five steps. First we present definitions related to scientific support systems intrinsic to finance and describe common characteristics of financial use cases. The second step concentrates on what can be exchanged through the definition of shareable entities called contributions. The third step is the description of a classification system for building blocks of the conceptual framework, called facets. The fourth step introduces the meta-model that will enable provenance tracking and representation of data fragments and simulation. Finally we describe intended cases of use to highlight main strengths of FRACTI: application of the scientific method for investigation in computational finance, large-scale collaboration and simulation.
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PDF链接：
https://arxiv.org/pdf/1808.07959