Identification of clusters of investors from their real trading activity in a financial market

Tumminello, Michele; Lillo, Fabrizio; Piilo, Jyrki; Mantegna, Rosario N.

doi:10.1088/1367-2630/14/1/013041

Cited by 97 publications

(78 citation statements)

References 59 publications

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“…The decrease of mean degree can be interpreted in the following way: as γ increases, the interaction involving the same pair of agents is repeated and effectively a dimerisation takes place. Similar dimers and small clusters have been observed by Tumminello et al [27] for agents in stock market data. Crossover to a dimerised state occurs as γ is increased.…”

Section: Model Bsupporting

confidence: 87%

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Agent based models for wealth distribution with preference in interaction

Goswami

Sen

2014

Physica A: Statistical Mechanics and its Applications

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h i g h l i g h t s• We propose a set of conservative wealth exchange models.• Three parameters α, β and γ are introduced to mimic real trading. • Wealth distribution, network properties and activity, etc., have been studied.• Phase transition and other interesting features are presented. • Correspondence to real data is shown for different combinations of α, β and γ . a b s t r a c tWe propose a set of conservative models in which agents exchange wealth with a preference in the choice of interacting agents in different ways. The common feature in all the models is that the temporary values of financial status of agents is a deciding factor for interaction. Other factors which may play important role are past interactions and wealth possessed by individuals. Wealth distribution, network properties and activity are the main quantities which have been studied. Evidence of phase transitions and other interesting features are presented. The results show that certain observations of the real economic system can be reproduced by the models.

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Section: Model Bsupporting

confidence: 87%

“…Some real data are available to this respect. It has been shown that within a small interval of time most clusters are of size 2 [26,27] which can be termed as 'dimerisation'. Another observation is regarding the activity, i.e., the distribution of the volume of individual trade that also follows a power law with an exponent ≃4.3 [28].…”

Section: Introductionmentioning

confidence: 99%

Agent based models for wealth distribution with preference in interaction

Goswami

Sen

2014

Physica A: Statistical Mechanics and its Applications

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“…39 to investigate preferential credit links between banks and firms based on their mutual credit relationships or ( ii ) in Ref. 40 to identify clusters of investors from their real trading activity in a financial market. Further details about the methodology, specifically applied to mobile phone data, can also be found in Ref.…”

Section: Discussionmentioning

confidence: 99%

A comparative analysis of the statistical properties of large mobile phone calling networks

Jiang

Xie

et al. 2014

Sci Rep

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Mobile phone calling is one of the most widely used communication methods in modern society. The records of calls among mobile phone users provide us a valuable proxy for the understanding of human communication patterns embedded in social networks. Mobile phone users call each other forming a directed calling network. If only reciprocal calls are considered, we obtain an undirected mutual calling network. The preferential communication behavior between two connected users can be statistically tested and it results in two Bonferroni networks with statistically validated edges. We perform a comparative analysis of the statistical properties of these four networks, which are constructed from the calling records of more than nine million individuals in Shanghai over a period of 110 days. We find that these networks share many common structural properties and also exhibit idiosyncratic features when compared with previously studied large mobile calling networks. The empirical findings provide us an intriguing picture of a representative large social network that might shed new lights on the modelling of large social networks.

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“…we consider the investor not active on day t. According to Tumminello et al (2012), in the present study, we set θ = 0.01. Roughly speaking, investors in a buy (sell) state can be seen as acting as net buyers (sellers), while investors in a buy and sell state can be thought as intermediaries or day traders.…”

Section: Definition Of the Variablesmentioning

confidence: 99%

How news affects the trading behaviour of different categories of investors in a financial market

Lillo

Miccichè

Tumminello

et al. 2014

Quantitative Finance

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We investigate the trading behaviour of a large set of single investors trading the highly liquid Nokia stock over the period 2003–2008 with the aim of determining the relative role of endogenous and exogenous factors that may affect their behaviour. As endogenous factors, we consider returns and volatility, whereas the exogenous factors are the total daily number of news articles and a semantic variable based on a sentiment analysis of the news. Linear regression and partial correlation analysis of the data show that different categories of investors are differently correlated to these factors. Governmental and non-profit organizations are weakly sensitive to news and returns or volatility, and, typically, they are more correlated with the former than with the latter. Households and companies, on the contrary, are very sensitive to both endogenous and exogenous factors, and volatility and returns are, on average, much more relevant than the number of news articles and sentiment, respectively. Financial institutions and foreign organizations are intermediate between these two cases, in terms of both the total explanatory power of these factors and their relative importance. We explicitly consider the role of overnight news and overnight returns on the successive trading activity and trading balance of the different categories of investors. We observe the role of the overnight news, which is weaker than the ones observed between synchronous variables. By performing a vector autoregression (VAR) analysis, we show that the flux of news of the previous day affects the trading activity of companies, households and foreign investors and the dynamics of volatility. VAR is not detecting any role of the lagged sentiment in the successive values of the difference between the number of buying and selling investors for each category of investors

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Identification of clusters of investors from their real trading activity in a financial market

Cited by 97 publications

References 59 publications

Agent based models for wealth distribution with preference in interaction

Agent based models for wealth distribution with preference in interaction

A comparative analysis of the statistical properties of large mobile phone calling networks

How news affects the trading behaviour of different categories of investors in a financial market

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