Volume 116, Number 2, October 2016
|Number of page(s)||6|
|Section||Interdisciplinary Physics and Related Areas of Science and Technology|
|Published online||01 December 2016|
Quantifying immediate price impact of trades based on the k-shell decomposition of stock trading networks
1 Department of Finance, East China University of Science and Technology - Shanghai 200237, China
2 Postdoctoral Research Station, East China University of Science and Technology - Shanghai 200237, China
3 Research Center for Econophysics, East China University of Science and Technology - Shanghai 200237, China
4 School of Sports Science and Engineering, East China University of Science and Technology Shanghai 200237, China
5 Shenzhen Stock Exchange - 5045 Shennan East Road, Shenzhen 518010, China
6 Department of Mathematics, East China University of Science and Technology - Shanghai 200237, China
7 Department of Physics and Center for Polymer Studies, Boston University - Boston, MA 02215, USA
Received: 25 October 2016
Accepted: 16 November 2016
Traders in a stock market exchange stock shares and form a stock trading network. Trades at different positions of the stock trading network may contain different information. We construct stock trading networks based on the limit order book data and classify traders into k classes using the k-shell decomposition method. We investigate the influences of trading behaviors on the price impact by comparing a closed national market (A-shares) with an international market (B-shares), individuals and institutions, partially filled and filled trades, buyer-initiated and seller-initiated trades, and trades at different positions of a trading network. Institutional traders professionally use some trading strategies to reduce the price impact and individuals at the same positions in the trading network have a higher price impact than institutions. We also find that trades in the core have higher price impacts than those in the peripheral shell.
PACS: 89.20.-a – Interdisciplinary applications of physics / 89.75.Da – Systems obeying scaling laws
© EPLA, 2016
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