Banking / Finance

Can big data be your big ticket to stock market success?

24th Jul `14, 11:48 AM in Banking / Finance

Big data could be used to predict how the stock of a certain company will fluctuate over time…

BDMS
Guest Contributor
 

Big data could be used to predict how the stock of a certain company will fluctuate over time given the right information. Here’s how:

Big data is being used for many applications and of that, finding trends in social media is a growing field in which big data is being used. A lot of companies are using data from websites like Facebook, Twitter and other social media websites to get an insight into customer buying patterns.

Today’s consumers are extremely social media savvy. Because of its expansive nature, social media has become an amazing tool to harness information about users, consumers and potential consumers. Here are some statistics which highlight the impact of social media on the world population.

1. Twitter was launched in 2006 and has about 255 million active users and growing
2. Facebook was launched in 2004 has more than billion active users and is expected to grow further.
3. Facebook generates 85% of its income through advertisements

Also Read: The Rise of Social Media [STATS INFOGRAPHIC]

This shows that users are increasingly using social media to take their choices in terms of products they use and services they avail. Take a look at this article to see how Facebook tracks advertisements. This makes social media websites the ideal location to understand customer response about products or policies. We can gain a lot by understanding the patterns in customer responses and this is precisely how we can predict the company’s track in the near future.

In the near future, we could see an evolution of “Sense and Response” system which could track the positive or negative response towards a product. This could serve as a vital cog in making stock market trading decisions.

This “Sense and Response” system essentially would get information about customer responses and give feedback about products through various sources. User responses can be obtained by two ways; social media tracking and cookie matching.

In social media tracking the ways in which information could be gathered include: garnering positive/negative keywords through tweets and statuses, getting review blog ratings, checking positive/negative keywords in comments to popular articles about the product or the company, ratings for videos of product reviews in relation to number of hits, Reddit posts could be monitored to gain an insight about information about user response.

Cookie matching is a powerful approach to tracking consumers’ online path to purchase, it involves matching digital data from website usage to everything to tags or cookies placed on customer’s devices. However, customers who wish to opt out of online tracking or log in from multiple devices cannot be tracked easily.

A system, if it ever exists would involve getting data from all of these sources and processing the information to get some insight into the mood of the customers. This insight could be used in taking useful trade decisions. An extension of this system could even scan the internet to get information about potential companies which are up and rising in the market.

But creating such a system looks like a rosy path to stock market success, even it has its own thorns. This system would be useful only on companies which rely on customer products or provide service to consumers which generates a response. Other companies would gain nothing by looking at social media for responses. For example, it would be counter-productive for oil and gas or energy companies which face harsh criticism from environmentalists. Considering the fact that environmentalists primarily use social media to spread their causes. Additionally. The raw data from any of these websites would be littered with various responses irrelevant to the product and filtering the data might take valuable time which could lead to lost profits. Maintaining relevance, accuracy and speed at the same time is not an easy task when dealing with large amounts of data and processing them in real time.

The technological capability to get sub second response time responses from data infrastructure is already available. This means we already have the ability to create this system even now. This is explained in this book, authored by Mike Barlow.

Taking stock market decisions based on a complex system running on big data would probably be possible very soon. It is possible that a response system which tells us which trading decisions to take in a split second could be developed in the near future or could even be in development now.

This article was written based on a white paper by Infosys.

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