[1]LI Hailin,LIANG Ye.Research on the stock index futures hedging strategy using label propagation time series clustering[J].CAAI Transactions on Intelligent Systems,2019,14(2):288-295.[doi:10.11992/tis.201707023]
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Research on the stock index futures hedging strategy using label propagation time series clustering

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 14 Number of periods: 2019 2 Page number: 288-295 Column: 学术论文—机器学习 Public date: 2019-03-05
Title:
Research on the stock index futures hedging strategy using label propagation time series clustering
Author(s):
LI Hailin1; 2;  LIANG Ye1
1. Department of Information Systems, Huaqiao University, Quanzhou 362021, China;
2. Research Center of Applied Statistics and Big Data, Huaqiao University, Xiamen 361021, China
Keywords:
label propagation; time series; clustering; dynamic time warping; hedging
CLC:
TP391
DOI:
10.11992/tis.201707023
Abstract:
Choosing a suitable clustering method is crucial in using time series clustering in stock index futures hedging. This study aims to investigate and improve the application performance of time series clustering in the financial data analysis field from a new perspective. We propose a model of stock index futures hedging based on label propagation time series clustering. In the model, a network space of spot stock was built using dynamic time warping as similarity measure. Each stock in the network was treated as a node, which would be divided into different clusters using label propagation, and finally, the stock data was clustered successfully. An optimization model for minimizing tracking error was constructed to obtain the optimal weight of each stock in the spot portfolio. Finally, we obtained the optimal spot portfolio. The tracking errors of the portfolio of the proposed method and that of the traditional clustering method were compared by tracking the index in the experiment. The proposed method showed the ability to improve tracking accuracy, providing a new way to enrich the investment and management of financial market.
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