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Uniform standards, experience of existed mainstream databases and data sources are main factors18 to influence the data classification standard’s utilization efficiency, there are still various other factors that should be involved in the establishment of financial data classific...

Framework Formation of Financial Data Classification Standard in the Era of the Big Data

Procedia Computer Science, (2014): 88-96

Cited by: 4|Views6

Abstract

Deeper excavation of relevance of data and a top-down thinking to take apart financial data into blocks for more efficient analysis are essential for the big data, as well as to eliminate data noise and to remove data redundancy in the process1. The financial data classification standard, which always performs excellently in these aspects...More

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Introduction
  • In the era of the big data, the authors need deeper excavation of relevance and a top-down thinking to take apart the financial data into blocks for more efficient analysis.
  • The classification standard will be verificated by data sources, and a corresponding table should be created.
  • The other classification system is strict statistical classification standard like the System of National Accounts (SNA)[11] and the Monetary and Financial Statistics (MFS), these strict statistical classification principles are closely related to the process of economic and make the rules in strict accordance with relevant statistical codes and tables
Highlights
  • In the era of the big data, we need deeper excavation of relevance and a top-down thinking to take apart the financial data into blocks for more efficient analysis
  • Shuang Yang et al / Procedia Computer Science 30 (2014) 88 – 96 index (CPI) and the stock index. Another representative is financial statistics system of the International Monetary Foundation (IMF) with Monetary and Financial Statistics Manual (MFS)[4]. It covers a series of financial data standards to guide the harmonization of national data and statistics, publications and amendments of each country
  • The other classification system is strict statistical classification standard like the System of National Accounts (SNA)[11] and the Monetary and Financial Statistics (MFS), these strict statistical classification principles are closely related to the process of economic and make the rules in strict accordance with relevant statistical codes and tables
  • Its fundamental purpose is to provide a tool for coordinating economic statistics on goods, services and assets for international comparisons, and provide useful guidelines for the country to develop products for the initial classification or amend the existing approaches, making their classification in accordance with international standards
  • In this research, uniform standards, experience of existed mainstream databases and data sources are main factors[18] to influence the data classification standard’s utilization efficiency, there are still various other factors that should be involved in the establishment of financial data classification standard in the era of the big data
Results
  • International financial statistics classification standard and contrast
  • ISIC classification is not intended to replace national industry standards, but provides a reference framework for international comparison of statistics.
  • Its fundamental purpose is to provide a tool for coordinating economic statistics on goods, services and assets for international comparisons, and provide useful guidelines for the country to develop products for the initial classification or amend the existing approaches, making their classification in accordance with international standards.
  • Through BEC classification, can make prepared trade data by international trade standard classification under SITC converse into three basic goods categories in national economy accounting system under (SNA) framework: capital products, and middle products and consumer.
  • 3. Major financial database classification standards and their data sources
  • Covering the world's major financial databases, in micro-financial data, classification standards are mainly in accordance with product classifications- CPC and BEC to gain the specific distinctions; in terms of macroeconomic data, they are basically based on SNA and MFS, whose sector classifications for the collection and collation of data are essential references.
  • The formation steps of the financial data classification framework z Determine the first and the secondary title and their serial numberthen correspond the detailed specific categories to the referenced international uniform data classification standards[15].
  • F3Government financial information z Referenced on the corresponding uniform financial classification standard and relative books, like Finance[16] and Investments and Portfolio Management17 ,gain more detailed categories.
Conclusion
  • This research makes financial data classification standard framework involve in mutual relationships with databases in the content and adapt to trends in the Big Data for its abilities to deeply excavate relevance of data and take apart a great number of data into blocks, which is easy and convenient for data mining and further analysis.
  • In this research, uniform standards, experience of existed mainstream databases and data sources are main factors[18] to influence the data classification standard’s utilization efficiency, there are still various other factors that should be involved in the establishment of financial data classification standard in the era of the big data.
  • More attention ought to be concentrated on the other factors in the completeness of the total standard
Tables
  • Table1: The contrast between SNA and MFS on Financial Statistics
  • Table2: The principal data of the main financial database and the corresponding source
  • Table3: The main data sources of mainstream databases
  • Table4: Financial data classification and its corresponding referenced standard
  • Table5: The correspondence between data storage and data sources
Download tables as Excel
Funding
  • This research is supported by Xinhua News Agency and China Finance Corporation
Reference
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Author
yingjiong zhong
yingjiong zhong
rui liu
rui liu
zili feng
zili feng
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