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An analyst who works in Germany is more likely to publish a high (low) price target regarding a DAX30 stock if other Germany based analysts are also optimistic (pessimistic) about the same stock. This finding is not biased by the fact that DAX30 companies are headquartered in Germany. In times of bull markets, price targets of analysts who regularly exchange their opinion are higher correlated compared to other analysts. This effect vanishes in a bearish market environment. This suggests that communication among analysts indeed plays an important role. However, analysts’ incentives induce them not to deviate too much from the overall average during an economic downturn.
An analyst who works in Germany is more likely to publish a high (low) price target regarding a DAX30 stock if other Germany based analysts are also optimistic (pessimistic) about the same stock. This finding is not biased by the fact that DAX30 companies are headquartered in Germany. In times of bull markets, price targets of analysts who regularly exchange their opinion are higher correlated compared to other analysts. This effect vanishes in a bearish market environment. This suggests that communication among analysts indeed plays an important role. However, analysts’ incentives induce them not to deviate too much from the overall average during an economic downturn.
With this paper, I propose a simple asset pricing model that accounts for the influence from social interaction. Investors are assumed to make up their mind about an asset's price based on a forecasting strategy and its past profitability as well as on the contemporaneous expectations of other market participants. Empirically analysing stocks in the DAX30 index, I provide evidence that social interaction rather destabilises financial markets. At least, it does not have a stabilising effect.
With this paper, I propose a simple asset pricing model that accounts for the influence from social interaction. Investors are assumed to make up their mind about an asset’s price based on a forecasting strategy and its past profitability as well as on the contemporaneous expectations of other market participants. Empirically analysing stocks of the DAX30 index, I provide evidence that social interaction rather destabilises financial markets. Based on my results, I state that at least, it does not have a stabilising effect.
In this paper, I analyse the reciprocal social influence on investment decisions within an international group of roughly 2000 mutual fund managers that invested in companies of the DAX30. Using a robust estimation procedure, I provide empirical evidence that in the average a fund manager puts 0.69% more portfolio weight on a particular stock, if other fund managers increase the corresponding position by 1%. The dynamics of this influence on portfolio weights suggest that fund managers adjust their behaviour according to the prevailing market situation and are more strongly influenced by others in times of an economic downturn. Analysing the working locations of the fund managers, I conclude that more than 90% of the magnitude of influence is due to pure observation. While this form of influence varies much in time, the magnitude of influence resulting from the exchange of opinion is more or less constant.
In this paper, I analyse the reciprocal social influence on investment decisions within an international group of roughly 2,000 mutual fund managers who invested in companies in the DAX30. Using a robust estimation procedure, I provide empirical evidence that the average fund manager puts 0.69% more portfolio weight on a particular stock, if his peers on average assign a weight to the corresponding position which is 1% higher compared to other stocks in the portfolio. The dynamics of this influence on the choice of portfolio weights suggest that fund managers adjust their behaviour according to the prevailing market situation and are more strongly influenced by others in times of an economic downturn. Analysing the working locations of the fund managers, I conclude that more than 90% of the magnitude of influence stems from the social learning. While this form of influence varies much over time, the magnitude of influence resulting from the exchange of opinion is more or less constant.