TY - GEN
T1 - Social network-based stock correlation analysis and prediction
AU - Rao, Yuan
AU - Zhong, Xuhui
AU - Lu, Shumin
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/7/2
Y1 - 2016/7/2
N2 - In order to forecast the price movement with the correlation between two different stocks, the model of Stock Social Network (SSN) is proposed to represent and analyze the intrinsic complex relationship. We choose 313 stocks from 9 industries to build an evolution model of SSN, which predicted that some stocks clusters are isolated and the nodes and edges in SSN are decreasing distinctly step by step with the change of threshold δ from 0.7, 0.75 and 0.8, respectively. Meanwhile, the coverage rate of nodes in SSN arrives 0.2076 at δ = 0.8, in reverse, the 79.24% nodes is trimmed during the process of evolution of SSN. Based on these results, we design a new portfolio strategy based on new index, named CSSNI, to optimize the asset pricing model. The results show that the ratio of return is 0.92666 based on the CSSNI, which is much better than the result by traditional strategy.
AB - In order to forecast the price movement with the correlation between two different stocks, the model of Stock Social Network (SSN) is proposed to represent and analyze the intrinsic complex relationship. We choose 313 stocks from 9 industries to build an evolution model of SSN, which predicted that some stocks clusters are isolated and the nodes and edges in SSN are decreasing distinctly step by step with the change of threshold δ from 0.7, 0.75 and 0.8, respectively. Meanwhile, the coverage rate of nodes in SSN arrives 0.2076 at δ = 0.8, in reverse, the 79.24% nodes is trimmed during the process of evolution of SSN. Based on these results, we design a new portfolio strategy based on new index, named CSSNI, to optimize the asset pricing model. The results show that the ratio of return is 0.92666 based on the CSSNI, which is much better than the result by traditional strategy.
KW - Asset Portfolio
KW - Price Movement Forecasting
KW - Risk of Stock
KW - Stock Social network
UR - https://www.scopus.com/pages/publications/85050853245
U2 - 10.1109/IIKI.2016.102
DO - 10.1109/IIKI.2016.102
M3 - 会议稿件
AN - SCOPUS:85050853245
T3 - Proceedings - 2016 International Conference on Identification, Information and Knowledge in the Internet of Things, IIKI 2016
SP - 573
EP - 576
BT - Proceedings - 2016 International Conference on Identification, Information and Knowledge in the Internet of Things, IIKI 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 International Conference on Identification, Information and Knowledge in the Internet of Things, IIKI 2016
Y2 - 20 October 2016 through 21 October 2016
ER -