The Value of Investor Relations Quantified with Machine Learning

07 September 2020  |  Iridium Quant Lens
The Value of Investor Relations Quantified with Machine Learning

This report - the first in a series exploring the science and practice of Investor Relations - introduces the world's first Machine Learning algorithms that are capable of quantifying the value of investor relations.


IR adds up to 24% of a company's market capitalization

Company boards and management teams often feel that the business value they generate is not well understood or adequately rewarded by the capital markets. They spend enormous effort to create business value – in the hope that this translates into market value – but only a tiny fraction of their resources on translating their achievements into tangible shareholder returns.

One underlying problem is a lack of quantitative research and evidence on how business value creation translates into shareholder value. In theory, this gap should be bridged through a professional investor relations function.

However, most companies have not yet invested sufficiently in investor relations because they do not have any real proof of the value it adds.

For a number of professionals operating in the investor relations arena, it has been a career-long struggle to convince boards and management teams of the relevance of IR and the value that good IR adds (or poor IR subtracts) from a company's valuation.

In this context, Iridium sought to take a scientific and systematic approach, using the latest Machine Learning techniques, to crack the 'IR Algorithm' and quantify the value of investor relations.