IFRS in the new world – hopes and fears

Are traditional metrics still relevant?, asks an article on the IFRS.org website.

The article summarizes some of the observations arising from a June 2018 panel debate hosted by CFA Institute and the IFRS Foundation, “asking whether traditional metrics are still relevant amidst rapid technological advancements.”  The observations are grouped under the headings “hopes” and “fears” – here are some of each:


  • Quantitative analysis has been around for decades, enabling a statistical and modelled approach to investing that rules out human biases. The escalation of technological developments in data collection and analytics, including AI-driven back-testing against price movements, has ushered in a new era in systematic investing.
  • Data can now be collected on customer behaviour by tracking their mobile phones, on trade via sensors in ship containers, on the movement of goods in and out of warehouses. The latest analytics can then search for past price correlations and use these to predict future movements. It is an edge in active investing that can be quickly eroded, but which can also move on quickly to the next set of unstructured (and therefore previously underused) data.
  • For a systematic investment operation, this relegates traditional financial information to a smaller part of the relevant data pool. Its continuing value lies in its structure, notably standardized definitions, in its comparative reliability and in the long run of evidence on links to price movements. New sources of data are tested against the traditional variety.
  • Those new sources include monitoring the tone of voice of executives at analyst meetings (CFOs are apparently more reliable than CEOs), and could move on to detecting emotion via tiny facial changes in video clips.
  • The prospect of machines doing the grunt work while humans investigate the results is an appealing one. But a gap remains between theory and reality, and the issue of data quality and integrity persists—how clean are the inputs?


  • Technology-driven price crashes are one of the dangers that exchanges and regulators will continue to grapple with, although humans may welcome the chance to take advantage of these dislocations (if they can get rapid enough access to the distorted prices).
  • Standardized information has always been the analyst’s friend, enabling comparisons over time and between asset classes and their constituents. Important questions include whether more data means better data, and whether human biases are baked into the algorithms sifting it.
  • Standardized definitions remain important and the International Accounting Standards Board’s project on the primary financial statements will produce more sub-totals, possibly including operating income and earnings before interest and tax.
  • Given clean inputs of well-defined data, the outlook for robo-investing—from smart stock screens to dynamic rebalancing of portfolios—is tantalizing, as illustrated by the advance of automation in exchange-traded funds.
  • But with so much of the technological approach related to price movements and gaining a relative edge, the fundamental question is who is setting prices with an eye on fundamental value? All the developments of recent years have done nothing to allay fears of asset price bubbles.

As in much writing about the ongoing importance of traditional financial statements, there seems to be an inherent contradiction here. If the capacity to gather and analyze data is so vast as to encompass fluctuations in tone of voice, it doesn’t make sense to suppose that the recommendations and decisions resulting from that process could be thrown materially off course by variations in such high-level matters as income statement subtotals. This would be roughly comparable to thinking a sophisticated AI reader might completely misunderstand the contents of a book, just because of a misleading blurb on the back of the dust jacket. I’ve mentioned (too) many times how the IASB perpetually fails to grapple adequately with the implications of technology, as have many others, but that’s partly only because of its stubborn persistence in this respect. The summary regards the potential of robo-investing as being dependent on ”clean inputs of well-defined data,” but a quarterly (at best) communication of summarized information delivered perhaps several months in arrears will never be capable of meeting the bulk of the robo-investors’ demands. This is why the IASB so often appears to be diligently attending to an inherently declining franchise.

It’s perhaps peculiar to observe that “All the developments of recent years have done nothing to allay fears of asset price bubbles,” because why did anyone ever think they should have done? Even the summary itself acknowledges (in the first point under  “Fears”) that people welcome such bubbles as much as they fear them. With such volatility surely here to stay, the question of who “is setting prices with an eye on fundamental value” threatens to become redundant. Of course, individual investors may use IFRS-compliant reporting as an input into their own assessment of what a particular company’s stock is worth, and then either get into or stay out of the market for that stock accordingly. But such investors seem more likely to occupy a rarified investing niche (and one that periodically risks leaving a lot of money on the table) than the centre of the investing universe…

The opinions expressed are solely those of the author

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