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Big data for growth stock investing

Can big data analytic methods be used for comparing Compounded Growth Rate (CGR) for a stock versus the industry median?

So they say

That’s an affirmative, according to Big Data for Finance via The Benefits of Going Big (June 2012), and posted on Twitter today, from the 2013 World Economic Forum in Davos, Switzerland.

Rationale

Comparing stock CGR’s with the industry median over time, then filtering those that exceed the median is computationally intensive:

The growth rate has to be calculated not only for every stock in the universe but also for the industry it belongs to. Typically, this kind of analytic takes tens of seconds to compute. The Eikon data cloud – through its proprietary ‘vega effect’ – decomposes the query into data retrieval, data level and application analytics and applies speed and scale to each layer.

This is accomplished by applying techniques such as

… efficient data retrieval algorithms, vectorisation, and parallel processing… the same analysis now takes less than one second to compute.

Such work required 30 seconds or even a minute using Microsoft Excel, 20 years ago. Modern MS Excel might require a full 5 or 10 seconds today…!

Realistically speaking…

For a quick explanation that describes my personal outlook, glance at this recent Canadian Market Research and Intelligence Association (MRIA) post about big data as a phenomenon.

Next, I found an Adelaide commercial law blog that provided a more nuanced assessment of big data. However, it is consistent with the marketing researchers’ outlook, excerpt:

Big Data is somewhat of a misnomer because it is not like standard ICT* spending… it will be run with technical services [for] determining veracity through market sentiment. If an investment bank is trying to determine the initial share price for an IPO they would run trend analysis on similar companies while [gauging] investor sentiment. Big Data used in this way is… a likely competitive advantage for smaller companies.

* ICT is an abbreviation for “information and communications technology”.

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