Shoot for Alpha, Not Beta in Low-Returning 2016, Mercer Says

Opportunistic and dynamic strategies are key to adding value as few asset classes are still considered “cheap.”

Investors will have to be more tactical opportunistic in their approach and willing to tilt portfolios from beta to alpha to ensure survival in a low-return environment, according to Mercer.

According to the consulting firm’s paper on investment themes, 2016 presents an “environment of heightened uncertainty and fatter tails,” from events such as China’s slowdown and central banks’ monetary policies.

“Alpha is challenging to find and is not a single homogeneous return source that may be captured by appointing active managers.”“With relatively few markets that can be described as ‘cheap,’ investors will be well-served by remaining patient but ready and able to act opportunistically when markets move to extremes,” said Deb Clarke, Mercer’s global head of investment research.

To add value amid the current unattractive risk/return tradeoffs of traditional beta, Mercer argued investors allocate more to active management—but only if they are able to tolerate fees and are skilled in manager selection.

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“It is important to recognize that alpha is challenging to find and is not a single homogeneous return source that may be captured by appointing one or more active managers,” the report said.

Mercer also argued investors should take advantage of reduced liquidity in traditionally liquid markets—like the US treasury and German bund markets—that could lead to periodic increases in price volatility in “gap moves”.

Contrarian investors have an even better advantage to capture opportunities in such periods of market stress, the paper said, through opportunistic and dynamic strategies.

Furthermore, a maturing credit cycle also calls investors to take a “more cautious stance,” Mercer said.

For those that are able to adjust market exposures dynamically over time, the consultant suggested tilting portfolios towards less volatile strategies such as low volatility equity, high-quality credit, and absolute-return fixed income.

Investors could also take advantage of high default rates and opportunities in distressed debt.

“Although this phase of the cycle could yet be a few years away, investors wishing to capitalize on such an opportunity may want to start considering the asset class and possible implementation approaches during 2016,” Mercer advised.

Home > News > Risk > How Well Do You Measure Risk?

Risk January 25, 2016

How Well Do You Measure Risk?

Forecasts based on typical techniques are “indistinguishable from random noise” for shorter time horizons, according to a Dutch central bank researcher.

The most common forms of risk measurement may not be the most accurate, according to research from Dutch central bank De Nederlandsche Banke (DNB).

The study—an examination of the accuracy and reliability of risk analysis techniques—focused on the difference between value-at-risk (VaR) and expected shortfall (ES). Of the two methods, VaR forecasts were more accurate, found DNB researcher Chen Zhou and the London School of Economics’ Jon Danielsson.

This counters the common view that VaR is “inherently inferior to ES.”

“Perhaps swayed by the theoretical advantages, ES appears increasingly preferred both by practitioners and regulators,” the study’s authors wrote.

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In fact, international bank regulator the Basel Committee suggested replacing 99% VaR with 97.5% ES in its latest Basel III market risk proposal.

“This will lead to less accurate risk forecasts,” Danielsson and Zhou argued. “If the regulators are concerned with precision, VaR is preferred.”

To compare the two techniques, the researchers conducted risk forecasts for sample sizes ranging from one year to 50 years. They found that both methods were “highly sensitive” to the sample size, with uncertainty increasing “rapidly” as the sample size decreased. For samples below a few thousand days, the uncertainty became “considerable.”

“At the smallest samples, often the most commonly used in practice, the uncertainty is so large that the risk forecast is essentially indistinguishable from random noise,” the researchers wrote.

ES carried more uncertainty than VaR, when the two techniques were projected at the same probability levels and when using the Basel III combination of 97.5% ES and 99% VaR.

The ES technique was found to have one advantage: It was harder to manipulate than VaR. As manipulated risk forecasts would also lack accuracy, this might be a reason to prefer ES, Danielsson and Zhou noted.

But regardless of the method chosen, the researchers said risk forecasts will remain “virtually indistinguishable from random noise” except when derived from large sample sizes.

“Common practices and trends in risk management are misguided,” Danielsson and Zhou wrote. “It is a concern that vast amounts of resources are allocated based on such flimsy evidence.”

Read the full paper, “Why Risk is so Hard to Measure.”

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