  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.
