Financial time series Motif mode mining method based on trading volume index

A financial time series and pattern mining technology, which is applied in the fields of finance, instruments, and electrical digital data processing, can solve problems such as nonlinearity, non-normality, and difficulty in meeting the technical needs of the financial field, so as to solve data noise interference and reduce costs Effect

Pending Publication Date: 2020-08-11
KUNMING UNIV OF SCI & TECH
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Problems solved by technology

Although certain results have been achieved, there are many factors affecting stocks, and the financial time series has the characteristics of non-stationary, non-normal, and nonlinear. A single stock price research is difficult to meet the technical needs of the financial field

Method used

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  • Financial time series Motif mode mining method based on trading volume index
  • Financial time series Motif mode mining method based on trading volume index
  • Financial time series Motif mode mining method based on trading volume index

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Embodiment

[0060] Such as Figure 1-7 As shown, the inventor selected 10 stock data of Shanghai Stock Exchange A-shares and Shenzhen Stock Exchange A-shares, and the time interval was from January 2, 2019 to December 31, 2019 (a total of 224 trading days). Daily data constitute time series set; Utilize a kind of financial time series Motif pattern mining method based on trading volume index of the present invention to carry out experiment, described method comprises the following steps:

[0061] Step1, obtain the interface that provides historical stock data from the data platform; Specifically, in this embodiment, the inventor obtains the interface that provides historical stock data from the data platform through Sohu Company and Qianlong Company;

[0062] Step2. Use Matlab to parse the historical data of all stocks in the Shanghai Stock Exchange and / or Shenzhen Stock Exchange within a specified time into a mat file and store it locally;

[0063] Step3. Take out the transaction volume...

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Abstract

The invention aims to better research stock market morphological significance and short-term trend prediction in a financial time sequence and provides a financial time series Motif mode mining methodbased on a trading volume index. The method comprises the steps of carrying out stock market analysis by changing the observed spatial dimension, wherein firstly, preprocessing transaction volume indexes, then selecting a proper data representation mode; secondly, introducing a partwise broken line fitting method, displaying the data in a broken line form by adopting a sliding window algorithm, finally, correspondingly segmenting the transaction volume and the stock price data, finding a price broken line Motif mode with research significance from the data, and carrying out mode detection bycombining a short-term trend clustering method. The inventor performs empirical analysis on historical data of Shanghai securities exchange and Shenzhen securities exchange, and the result shows thatthe method can highlight the characteristics of the data, reflect the implicit information of the quantity-price relationship and solve the problem of data noise interference.

Description

technical field [0001] The invention relates to a financial time series Motif pattern mining method based on trading volume indicators, which belongs to the field of financial time series analysis. Background technique [0002] Stock trend analysis is one of the important topics in financial time series analysis. Traditional time series analysis methods such as Arima, Arch and Garch are mostly applied to stock price changes. Although certain results have been achieved, there are many factors affecting stocks, and the financial time series has the characteristics of non-stationary, non-normal, and nonlinear. A single stock price research is difficult to meet the technical needs of the financial field. With the development of science and technology, the mining and forecasting of stock price patterns has become a hot topic, while there are relatively few studies on trading volume. Trading volume, as a popular indicator of stock trading, can reflect the flow of funds into and o...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/2458G06Q40/04
CPCG06F16/2465G06F16/2474G06Q40/04
Inventor 刘晓彤车文刚程文辉
Owner KUNMING UNIV OF SCI & TECH
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