Financial time series segmentation distribution feature computing method and system

A technology of financial time series and distribution features, which is applied in the fields of finance, computing, and special data processing applications, etc., and can solve the problems of difficulty in extracting segmental distribution features of financial time series data, etc.

Active Publication Date: 2015-07-22
上海卡方信息科技有限公司
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  • Abstract
  • Description
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Problems solved by technology

[0006] The technical problem to be solved by the present invention is to propose a calculation method for the segmental distribution feature of f...

Method used

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  • Financial time series segmentation distribution feature computing method and system
  • Financial time series segmentation distribution feature computing method and system
  • Financial time series segmentation distribution feature computing method and system

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Embodiment 1

[0050] first reference Figure 7 Shown, method flow process of the present invention is as follows:

[0051] Perform differential processing on the acquired financial transaction data according to the price-time series, remove the DC component in the data, and obtain the differential sequence;

[0052] Continuously segment the difference sequence in time order to obtain several binary vectors;

[0053] Carry out statistics on the distribution characteristics of continuous segments, screen out different types of segments, and count the number of occurrences of the same segment; then sort the segments of different types to form a segment feature matrix, where: the number of each row in the matrix The row vector formed from the first column to the second column represents each segment, and the third column represents the number of occurrences of the corresponding segment; the fourth column to the last column are segment feature vectors;

[0054] According to the segmented featu...

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Abstract

The invention discloses a financial time series segmentation distribution feature computing method. According to the method, based on TICK data of the bargain price, a differential direct-current removal data preprocessing method is adopted, a new segmentation series data structure is configured, continuous segmentation is conducted on the difference series, statistics is conducted on prior probability distribution of the segmentation series, and financial transaction data trend distribution computing is achieved. The invention further provides a financial time series segmentation distribution feature computing system, compared with other financial time series feature extraction algorithms, the system is of a more concise data processing structure, more excellent in recognition performance and good in data consistency; meanwhile, the series distribution feature obtained through the data processing method is obvious, and the performance is more excellent on the aspect of fuzzy estimation compared with other similar algorithms.

Description

technical field [0001] The invention relates to a method for extracting distribution features of financial time series data, which belongs to the technical field of computer data processing. Background technique [0002] Time series analysis has become an integral part of financial market research both theoretically and empirically. Time series analysis method is one of the mainstream methods of financial quantitative analysis. Many research results of modern econometrics and financial markets are based on time series analysis. Engle and Grange won the Nobel Prize in Economics in 2003 for their extensive application of time series models in economics and finance, which is a strong proof that the importance of time series analysis methods is widely recognized in the world. [0003] Financial time series analysis studies the theory and practice of the evolution of asset values ​​over time. For financial asset return series, volatility is often not observed, and statistical ...

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Application Information

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IPC IPC(8): G06F17/30G06Q40/04
Inventor 曹东
Owner 上海卡方信息科技有限公司
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