Academic Master

Sociology

Social Connectedness Essay

Introduction

An investment fund that is based on current trends is known as a momentum fund. The trends that are usually observed include trends of price movements and earnings. Thus, the managers invest in the companies that have positive momentum, and they may also sell the stock of the companies that have negative momentum. Further, individuals must invest in such type of fund as these funds contain a high probability of fetching high return investments. However, there is an important point to understand that these funds require a high level of monitoring because the directional changes might occur during the period and also the momentum factors can be short-term. They consider different characteristics of stock and thus end up with an informed investing decision. The most common factors which are considered while analyzing whether to invest in the momentum fund or not include earnings, price movement, and revenue. Investors must utilize the benefits offered by momentum investing by investing in these funds. There are various other companies which offer such type of investing. However, there are also certain risks that such momentum funds contain that must be in the knowledge of the investors. They must understand those factors which are being considered while constructing a portfolio. For instance, there are funds that only focus on the past performance of the company and others that not only follow the performance momentum but also consider the expectations for the future as well.

Discussion

Research studies suggest that social networks provide easy accessibility to resources, and information and allow sharing and coordination. Thus, those who have strong connections and are socially active are in a better position relative to those investors who do not have such connections. It is because social connections regulate the behaviour of society. They influence the behaviour by affirming or negating them. Further, it is easier to verify the information on social networks. These social relations thus can help an organisation to get the benefits by seeking an adequate level of financing. This notion can be well explained by the embeddedness approach; this concept explains why economic transactions become embedded in social relations and thus affect differentially the valuation and allocation of the resources. Further, there has been a debate that due to the efficient market hypothesis stock returns cannot be predicted (Hong, 1999). However recent studies show that information is a major factor that has the potential to influence stock returns (Qian, 2007). Also, the information contained through social media reaches a broad audience (Risius et al., 2015).

However, there are negative implications of such social connections as well. For instance, these social connections also contain the probability of restricting actions by imposing normative behaviour. Moreover, a gradual Information flow model highlights that the contemporary world differs in two different ways as assumed by the EMH. Firstly, some information is restricted as private and is not available to the public. Secondly, even if the information is disclosed to the investors, their cognitive biases tend to limit their ability to perceive the information (Sul & Yuan 2017).

Research studies on momentum trading have shown the consensus on the point that in the intermediate horizon where the period remains between three to 12 months the stock returns show persistence in generating returns. However, the reasons for such persistence may differ. It depends on the factors which are at the core of the momentum funds and which are kept under consideration while formulating such funds. There are also considerations regarding a view that associates abnormal returns with the momentum strategies and suggest that these momentum strategies fetch abnormal returns as compensation for the unidentified source of non-diversifiable risk (Carhart, 1997). Further, studies also suggest that earning-related news also plays a significant role in price momentum trading (Burch, 2002). This study also strengthens the notion of social connectedness as well. Social connectedness also affirms the theory of an efficient market hypothesis. Thus when the information is available to all the investors than the tendency, inclination and probability to buy such funds increases. It is very important to know what type of information is being rotated in these social networks as it works and vice versa as well.

Research studies suggest that naïve investors may also cause momentum with biased expectations (Hvidkjaer, 2009). It has also been studied that individuals may use heuristics or cognitive biases causing them to suffer. That is the reason these individuals rely on particular models of risk and expected return. Thus by these models, investors tend to buy or sell the same securities at the same time. To conclude, the cognitive biases of the individuals and prices tend to formulate the behaviours of the individuals. This is linked to social connections as well. In an environment of increased networking and social connection, such factors contain the probability of creating negative ties. Thus, It is very important to understand about the behavioural disposition of the abnormal returns that either they are due to the proposed explanation of the behaviour or they are caused by rational motivations. Thus social connectedness works at both ends.

To sum, social connections play an important role in increasing the importance and potential of a fund among the public so that individual investors may look forward to investing in it. The impact of such an impact can be measured by looking at the trends, and the behaviours of the people towards the fund that is being offered. Research studies suggest that social ties and networks play a significant role in financial contexts and in a broader sense they also influence the decisions and outcomes of the managers and directors (Bertrand and Schoar, 2003; Xuan, 2009)

Conclusion:

Thus, the basic demand and supply functions are being disturbed by such a kind of trading.

References

Bertrand, M., Schoar, A., 2003. Managing with style: the effect of managers on firm policies. Quarterly Journal of Economics 118, 1169–1208

Burch, T.R. and B. Swaminathan, 2002, “Earnings news and institutional trading,” working paper (Cornell University).

Carhart, M., 1997, “On persistence in mutual fund returns,” Journal of Finance 52, 83-110.

Hong, H., & Stein, J. C. (1999). A unified theory of underreaction, momentum trading, and overreaction in asset markets. The Journal of Finance, 54(6), 2143–2184.

Hvidkjaer, S., 2006. A trade-based analysis of momentum. The Review of Financial Studies, 19(2), pp.457-491.

Qian, B., & Rasheed, K., (2007). Stock market prediction with multiple classifiers. Applied Intelligence, 26(1), 25–33.

Risius, M., Akolk, F., & Beck, R. (2015). Differential emotions and the stock market—The case of company-specific trading. European Conference on Information Systems, Completed Research Papers, Munster, Germany, Paper 147.

Sul, H.K., Dennis, A.R. and Yuan, L.I., 2017. Trading on Twitter: Using social media sentiment to predict stock returns. Decision Sciences48(3), pp.454-488.

Xuan, Y., 2009. Empire-building or bridge-building? Evidence from new CEOs’ internal capital allocation decisions. Review of Financial Studies 22, 4919–4948.

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