Trading networks, abnormal motifs and stock manipulation

Abstract

We study trade-based manipulation of stock prices from the perspective of complex trading networks constructed by using detailed information of trades. A stock trading network consists of nodes and directed links, where every trader is a node and a link is formed from one trader to the other if the former sells shares to the latter. Specifically, three abnormal network motifs are investigated, which are found to be formed by a few traders, implying potential intention of price manipulation. We further investigate the dynamics of volatility, trading volume, average trade size and turnover around the transactions associated with the abnormal motifs for large, medium and small trades. It is found that these variables peak at the abnormal events and exhibit a power-law accumulation in the pre-event time period and a power-law relaxation in the post-event period. We also find that the cumulative excess returns are significantly positive after buyer-initiated suspicious trades and exhibit a mild price reversal after seller-initiated suspicious trades. These findings can be better understood in favor of price manipulation. Our work shed new lights into the detection of price manipulation resorting to the abnormal motifs of complex trading networks.Comment: 14 Latex pages including 5 figures and 2 tables, Submitted to QF

Unveiling correlations between financial variables and topological metrics of trading networks: Evidence from a stock and its warrant

“…However, by checking the local structures of the nodes with large degrees, we surprisingly find that those nodes having large degrees are connected by multiple edges in some trading networks, known as an abnormal trading motif [9]. Such trading networks may exhibit relatively large assortative indexes, but still negative.…”

“…Regardless of the link direction, most trading networks are trees. However, there are also trading networks with loops, some of which are probably caused by price manipulators [9]. The most striking feature of these networks is a star-like local structure.…”

Which stocks are profitable? A network method to investigate the effects of network structure on stock returns

“…Li [21] HSI fluctuation patterns Important topological nodes Hong Kong stock market Bakker [22] Investment behavior of trust traders Impacts of trust networks on the stabilization of market NA Jiang [23] Trading behavior Power-law degree distribution Shenzhen stock exchange Jiang [24] Trading behavior Abnormal motifs Shenzhen stock exchange Li [25] Trading behavior Correlations between financial variables and network metrics A specific stock…”

“…Furthermore, they extend their work on trading networks to investigate financial research problems. One representative work is to identify the abnormal trading motifs and stock manipulations based on the network topology [24]. It contributes to the field of market surveillance.…”

Investigating the Influence Relationship Models for Stocks in Indian Equity Market: A Weighted Network Modelling Study

“…Weighted network analysis has been used in several studies in past for identification of influential nodes and quantification of their interactive strengths. Some of them include the following: examining the flux movement in transportation related network, for instance the air traffic networks and Internet networks [15, 16]; analysis of the rate of turnover of molecules through a metabolic pathway in cellular systems [17,18, 19, 20]; study of the statistical properties of trading activity network existent in stock exchanges in developing economies [21,22,23]; investigation into the degree distribution, node distribution and weight distribution of the world investment networks[24] and lately for analysis of the dynamics of stock market networks [25,26,27]. …”