Sovereign wealth funds are building risk monitoring systems based on warning signs such as rising commodity prices to help them reduce the risk in their portfolios in advance of market shocks, according to a panel of experts.
Sung Cheng Chih, former chief risk officer for the government of Singapore Investment Corporation (GIC) and currently a consultant to several sovereign institutions, said: “The financial crisis highlighted the importance of preparing for contingencies, with some funds now seeking to create risk dashboards based on pre-agreed signals for portfolio de-risking.”
Sung was speaking at a roundtable discussion including BNY Mellon investment professionals and a senior adviser to sovereign institutions. The roundtable discussed traditional investment and risk management models to help sovereign wealth funds become better stewards of their national wealth for current and future generations.
Rumi Masih, senior investment strategist for BNY Mellon’s Investment Strategy and Solutions Group (ISSG), said: “It appears to be counter-intuitive, but a sovereign wealth fund that is sensitive to changes in commodity prices should begin moving into more liquid assets as commodity prices are peaking instead of waiting for them to decline.”
Masih said: “Sovereign wealth funds, like other large institutional investors, are trying to apply the lessons of the last financial crisis. That way, they can be more nimble if another crisis occurs.” Masih said that sovereign wealth funds could develop signals that could trigger moves to increased liquidity. He said such warnings could be customized depending on the drivers of a nation’s economy.
The roundtable group focused on three challenges that became apparent during the 2008 financial crisis:
- The need for an investment approach that takes a broader, more multi-generational view of liabilities, including the potential liabilities that could arise during market stress
- Governance models that allow for greater tactical flexibility
- A more transparent way to combine risk exposures across liquid and illiquid asset classes while accurately measuring value-added performance
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