Risk modeling for the future

(Pictured: Harry Liem)

With a lot of attention being devoted to risk since the global financial crisis, Mercer has issued a reminder of the importance of modeling tools which go beyond mean-variance analysis. Harry Liem, a Mercer principal, says they should be seamlessly integrated.

These increasingly advanced modeling tools include:

• risk factor analysis – examining portfolios on a risk factor, rather than asset class, basis, for example, the equity and credit factor risk embedded in hedge funds.
•  regime switching models – examining stressed regimes, incorporating correlation compression and flight-to-quality effects into government bonds.
• market-aware assumptions – allowing investors to benefit from mean reversion in market cycles over medium-term time frames.
• liquidity tests – allowing investors to understand how a fund manages liquidity in a steady state through the cycle and stressed environment, which is a mandatory requirement for super funds under the new regulations.

Liem says that every major crisis in modern times has been exacerbated by instruments that only gained widespread acceptance a few years prior to the events. For instance, portfolio insurance in 1987, statistical arbitrage in the collapse of Long Term Capital Management in 1998, internet stocks in 2000 and collateralized debt obligations in 2008.

“The one constant is the boom-bust cycle inherent in human behavior,” Liem says in a note entitled: ‘Back to the Future – modeling risk post GFC’.

“This behavior can be modeled by adopting a forward-looking, mean-reverting simulation rather than relying purely on historical outcomes. This enables the examination of many possible economic conditions and their impact on asset and portfolio returns over multiple periods. In addition, alternative asset classes may not possess a rich data history, but paths can be simulated using factor models.”

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