Stock index tracking and prediction method and system based on social network clustering

Abstract

The invention discloses a stock index tracking and prediction method based on social network clustering. The method comprises the following steps: acquiring indices of a previous month and a current month and component stock data from a third-party database, and carrying out data cleaning, so that in-sample data and out-of-sample data that can be used for researches are obtained; calculating metric distances through correlation coefficients among component stocks to construct a social network among the component stocks, carrying out the network clustering through the adaptive affinity propagation clustering algorithm, extracting a clustering center of each cluster to form a stock pool, utilizing an index tracking optimization model to achieve the optimized tracking of stocks in the stock pools on a benchmark index, and determining the optimized weight of index tracking; and applying the stock pools and the optimized weight obtained through in-sample training to the index tracking for the out-of-sample data, so that a predicted index is obtained. The invention further provides a stock index tracking and prediction system. The method and system provided by the invention has the advantages that correlation among the constructed stock pools is low, tracking errors are small, replication results are highly stable, and accurate index tracking is achieved.

Description

technical field [0001] The invention relates to a securities data analysis and processing method and system, in particular to an index replication model construction technology based on social network clustering, which belongs to the technical field of data analysis and prediction. Background technique [0002] The stock price index is a numerical value obtained after average calculation and dynamic comparison of stock prices issued by some representative companies in the stock market. The stock price index can comprehensively examine the dynamic change process of the stock market, reflect the price level of the stock market, and provide the public with a reference basis for stock investment and legitimate stock appreciation activities. These representative company stocks are generally called constituent stocks . For example, the Shanghai Stock Exchange 180 Index and the Shenzhen Stock Exchange 100 Index are two typical indexes in the Shanghai and Shenzhen stock markets, an...

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Problems solved by technology

[0007] Existing index replication technology based on constituent stocks pays too much attention to factors such as market capitalization and weighting factors, ignoring the role of some small market capitalization stocks in index composition; The correlation between stocks, the correlation between stocks is higher

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