Equity Research Report Analysis Using NLP Data

Equity-Research-Report

Equity Research Report Analysis Using NLP Data

Equity-Research-Report

When an analyst writes up an equity research report, they take time to convey the full scope of the situation. They don’t simply crank the numbers and write up headline earnings. Equity research reports are rich in text that can convey subtle changes that haven’t affected the hard numbers just yet.

Investors using analyst equity research reports to help them select stocks can get a lot more out of them than they currently are by analysing the body of the report.

The challenge is that parsing through large bodies of text and understanding the subtleties and nuances of the written language is time and resource consuming.

As a result, investors opt to essentially ignore the majority of the equity research report, and look instead at numbers such as the estimate for average earnings per share (EPS) and compare them from quarter to quarter. This is understandable. These hard numbers, after all, are objective data points. But can a single number tell the whole story?

Analysts don’t simply crunch the numbers, they look at all the information available to them to make predictions about the performance of a company, and recommendations on whether to buy, sell or hold. Analysts are often reluctant to change their recommendations frequently, so may hold off on making any explicit statements. However, subtle changes in tone, words and phrasing can belie a change in their view even if their fundamental analysis headline rating remains the same.

This is where natural language processing (NLP) comes in.


What is Natural Language Processing?

NLP combines computer science, artificial intelligence and linguistics to automatically process human language. Symanto’s suite of NLP tools can automatically process words, tone and phrasing to extract useful data around topics mentioned in a text and sentiment.

In recent years the capabilities of these technologies have skyrocketed. Not long ago, the goal of NLP was to match human ability to recognise words, tone and phrasing. Now NPL technologies can recognise subtleties and changes in emotion and sentiment that some humans find challenging.

One of our greatest challenges as humans is objective and dispassionate analysis. Even the most rational and logical of us are still susceptible to persuasion tactics and viewing things from the myopic lens of our own subjective experience. At least, that is, compared to computers.


How NLP Can Be Utilised…


1.    …In equity research report analysis

Rather than simply looking at headlines on equity research reports, investors can use NLP to automatically parse through the body of writing within the report and pick up on subtle changes in sentiment that suggest a change in view not expressed within the headline.

This would enable investors to make predictions about the changes in headline forecasts before they happen and well ahead of the curve.


2.    …In management earnings calls and reports

While NLP tools and platforms currently only process written text, you can use transcripts of earnings calls to analyse in subtleties management’s communications.

During calls and on 10-k forms, Management may subtly hint at changes in their viewpoint around their company. For example, if management lacks confidence in their ability to reach goals and milestones, they may use language with weaker sentiment and may show fewer excitement markers.

Peaks and dips in management confidence can help you more accurately forecast the company’s performance.

 

Other applications of NLP in Private Equity


Industry trends

NLP can identify trends that are driving the market. Forums, news sites, social media pages and online reviews can all be excellent sources of data to extract relevant and emerging topics within almost any industry.

NLP can help you forecast emerging trends and plan for the impact of these changes not only on the main players within the industry but also on all companies across the supply chain.

Trend forecasts that rely on behavioural data require you to wait until the market is already trending upwards. By using organic online conversations to predict trends, there is the potential for you to put yourself ahead of the curve and identify opportunities before behavioural trends emerge.


Company insights

NLP can be used to identify:

  • Which companies in the industry are dominating online conversation
  • Who has the largest share of voice
  • Who has the most loyal customer base
  • Who has the strongest customer sentiment score
  • Which company is best positioned to take advantage of emerging industry trends

You can also use NLP to identify the main challenges faced by a company and assess market conditions to identify post-investment value creation opportunities.


Summary

NLP technologies offer an incredible opportunity for global investors to gain pertinent insights that can facilitate more objective decision-making and make for a stronger bottom line.

Quantitative, easily identifiable, structured data has been used for decades to help make sound investment decisions, but there is a wealth of other data that has remained largely untapped. Equity research reports, 10-k forms and earnings calls are rich with qualitative data and information that was impenetrable before the emergence of NLP technologies.

To find out how to use Symanto NLP technologies to improve your decision making and strengthen your bottom line, get in touch or book your free personalised consultation today.