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Decrypting Financial Markets through E-Joint Attention Efforts: On-Line Adaptive Networks of Investors in Periods of Market Uncertainty.

Casnici N, Dondio P, Casarin R, Squazzoni F - PLoS ONE (2015)

Bottom Line: By measuring the investors' expertise, we found that their behaviour could help predict changes in daily stock returns.We also found that expert investors were more influential in communication processes during high volatility market phases, whereas they had less influence on the real-time forum's reaction after bad news.Our findings confirm the crucial role of e-communication platforms.

View Article: PubMed Central - PubMed

Affiliation: Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy.

ABSTRACT
This paper looks at 800,000 messages on the Unicredit stock, exchanged by 7,500 investors in the Finanzaonline.com forum, between 2005 and 2012 and measured collective interpretations of stock market trends. We examined the correlation patterns between market uncertainty, bad news and investors' network structure by measuring the investors' communication patterns. Our results showed that the investors' network reacted to market trends in different ways: While less turbulent market phases implied less communication, higher market volatility generated more complex communication patterns. While the information content of messages was less technical in situations of uncertainty, bad news caused more informative messages only when market volatility was lower. This meant that bad news had a different impact on network behaviour, depending on market uncertainty. By measuring the investors' expertise, we found that their behaviour could help predict changes in daily stock returns. We also found that expert investors were more influential in communication processes during high volatility market phases, whereas they had less influence on the real-time forum's reaction after bad news. Our findings confirm the crucial role of e-communication platforms. However, they also show the need to reconsider the fragility of these collective intelligence systems when under external shocks.

No MeSH data available.


Related in: MedlinePlus

The communication network before (on the left) and after (on the right) a bad news.Left graph shows the communication network on January the 3rd, 2012 and the second graph shows the communication network on January the 4th, 2012. These snapshots were built such that the stronger was the link between two investors, the thicker the graph’s tie was. The node size was proportional to the investor’s in-degree. The difference of node's colour indicates a different modularity class.
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pone.0133712.g007: The communication network before (on the left) and after (on the right) a bad news.Left graph shows the communication network on January the 3rd, 2012 and the second graph shows the communication network on January the 4th, 2012. These snapshots were built such that the stronger was the link between two investors, the thicker the graph’s tie was. The node size was proportional to the investor’s in-degree. The difference of node's colour indicates a different modularity class.

Mentions: Results show that in the initial period of the sample, when the Unicredit stock volatility was at a minimum, the forum network reacted quickly to any change in stock returns. This was found for all the variables considered, i.e., number of investors, turnover, presence of more expert investors and network stability (see rt-1 column in Table 1). Under low volatility, any decrease of stock returns decreased network stability, i.e., there was less persistence of active investors in the forum and less persistent links, higher presence of expert investors and more quality of information shared. Finally, under high volatility, any decrease of stock returns diminished network stability and attracted new investors in the forum compared to the previous day, including but not limited to expert investors (see Fig 7). It is worth noting that during high volatility, bad news had no effect on the quality of information.


Decrypting Financial Markets through E-Joint Attention Efforts: On-Line Adaptive Networks of Investors in Periods of Market Uncertainty.

Casnici N, Dondio P, Casarin R, Squazzoni F - PLoS ONE (2015)

The communication network before (on the left) and after (on the right) a bad news.Left graph shows the communication network on January the 3rd, 2012 and the second graph shows the communication network on January the 4th, 2012. These snapshots were built such that the stronger was the link between two investors, the thicker the graph’s tie was. The node size was proportional to the investor’s in-degree. The difference of node's colour indicates a different modularity class.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4526688&req=5

pone.0133712.g007: The communication network before (on the left) and after (on the right) a bad news.Left graph shows the communication network on January the 3rd, 2012 and the second graph shows the communication network on January the 4th, 2012. These snapshots were built such that the stronger was the link between two investors, the thicker the graph’s tie was. The node size was proportional to the investor’s in-degree. The difference of node's colour indicates a different modularity class.
Mentions: Results show that in the initial period of the sample, when the Unicredit stock volatility was at a minimum, the forum network reacted quickly to any change in stock returns. This was found for all the variables considered, i.e., number of investors, turnover, presence of more expert investors and network stability (see rt-1 column in Table 1). Under low volatility, any decrease of stock returns decreased network stability, i.e., there was less persistence of active investors in the forum and less persistent links, higher presence of expert investors and more quality of information shared. Finally, under high volatility, any decrease of stock returns diminished network stability and attracted new investors in the forum compared to the previous day, including but not limited to expert investors (see Fig 7). It is worth noting that during high volatility, bad news had no effect on the quality of information.

Bottom Line: By measuring the investors' expertise, we found that their behaviour could help predict changes in daily stock returns.We also found that expert investors were more influential in communication processes during high volatility market phases, whereas they had less influence on the real-time forum's reaction after bad news.Our findings confirm the crucial role of e-communication platforms.

View Article: PubMed Central - PubMed

Affiliation: Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy.

ABSTRACT
This paper looks at 800,000 messages on the Unicredit stock, exchanged by 7,500 investors in the Finanzaonline.com forum, between 2005 and 2012 and measured collective interpretations of stock market trends. We examined the correlation patterns between market uncertainty, bad news and investors' network structure by measuring the investors' communication patterns. Our results showed that the investors' network reacted to market trends in different ways: While less turbulent market phases implied less communication, higher market volatility generated more complex communication patterns. While the information content of messages was less technical in situations of uncertainty, bad news caused more informative messages only when market volatility was lower. This meant that bad news had a different impact on network behaviour, depending on market uncertainty. By measuring the investors' expertise, we found that their behaviour could help predict changes in daily stock returns. We also found that expert investors were more influential in communication processes during high volatility market phases, whereas they had less influence on the real-time forum's reaction after bad news. Our findings confirm the crucial role of e-communication platforms. However, they also show the need to reconsider the fragility of these collective intelligence systems when under external shocks.

No MeSH data available.


Related in: MedlinePlus