AI dominates today’s portfolios, but the failures will outweigh the successes without genuine active management argues Loomis, Sayles & Company’s Aziz Hamzaogullari.
Water is a finite and scarce commodity, and institutional asset owners have a big part to play in ensuring the long-term conservation and management of water resources – not only for their direct beneficiaries, but also for the long-term good of the planet and future generations.
The transition to net zero is well underway, but it won’t be a smooth path and getting there will pose significant risks for investors. These are the conclusions of a new report by Pictet Asset Management and the Institute of International Finance. It will require higher levels of borrowing by the companies they invest in; the
Foundational research by CFA Institute aims to prompt the best minds in the asset management and asset owner communities to consider how to better consider climate risk. Institute chief executive Marg Franklin says governance, organisational design and systems thinking will be core elements of how the industry evolves its thinking and
[vc_column] Overview Quantifying the impact of climate change on physical assets and business models presents a challenge for all investment professionals. Scenario analysis and carbon pricing are central to understanding plausible future outcomes.[vc_column_text css=””]Images of island nations disappearing under the waves might come to mind, while worsening heatwaves, droughts, wildfires and floods are already evident.
Demographics is destiny, or so the saying goes. As populations grow, and as they move about, there will be investment opportunities that arise from their needs, their activity and their consumption. The trick for investors, however, is working out how long-term trends figure in generating shorter-term investment performance.
An investment theme that incorporates all traditional businesses trying to exploit technology, including AI, is simply too broad. Focusing on AI alone leaves investors exposed to the uncertainty of future developments. In between is an approach that recognises AI as an accelerant to existing trends.
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