The CFA Institute and the IFRS Foundation hosted a panel debate to ask participants whether traditional metrics are still relevant amidst rapid technological advancements.
If investing is as much an art as a science, any debate about the impact of technology is bound to prompt as much fear as hope.
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 standardised 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.
Preparers of accounts are focused on automation, particularly in drawing together data from different sources. Here the elimination of humans helps as they are more prone to errors (and to manipulating the data) than are robots. The acceleration in the process is also important and suggests that the time taken to report financial information to investors can also be shortened.
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).
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