Pension plans ramping up factor-based investing

Pension schemes in Asia plan to increase and broaden their use of smart-beta strategies in 2016, including state retirement funds in Japan and Taiwan.
Pension plans ramping up factor-based investing

Pension funds in Asia, like their peers globally, are increasingly identifying factors such as low volatility, momentum and quality as key to achieving better risk-adjusted returns.

Priscilla Luk, senior director of global research in Hong Kong at S&P Dow Jones Indices, says Asian institutions that have made allocations to so-called ‘smart beta’ are now diversifying their approach in this area.

For example, Japan’s $1.2 trillion Government Pension Investment Fund is employing low-volatility and value-factor strategies since the revision of its policy asset mix in November 2014. GPIF does not disclose the exposure, but it is believed to be some 5% of its equity allocation. Meanwhile, Taiwan’s Bureau of Labor Funds (BLF) is using fundamental indexing and minimum volatility strategies. Both institutions plan to increase their use of smart beta as they expand their global exposure.

BLF has been a relatively early mover among Asian pension funds in adding factor-based investments to diversify its assets with a view to achieving stable returns. As at end-December 2015, its investments in smart-beta strategies amounted to $6.2 billion out of total assets of $88 billion at the end of November 2015. The fund issued an RFP for $2.1 billion of enhanced Asia-Pacific equity mandates in December, as part of its moves to expand its international portfolio.

Huang Chao-Hsi, BLF’s director general, told AsianInvestor it was formulating an Asia-Pacific value-based mixed-equity strategy, which integrates the three factors of minimum volatility, quality and value.

“The mixed index offers the prospect of a sound investment return over the long term that will be better than a cap-weighted index approach, and with downside protection, since it also includes a low-volatility element,” noted Huang.

Although the trend is in its early stages in Asia, pension funds in Europe and the US have been using factor-based strategies for some time. One $4 billion American corporate pension plan hired State Street Global Advisers in 2014 to implement a multi-factor defensive smart-beta strategy for diversification and the opportunity to invest in higher-quality companies.

Multi-factor is likely to catch on in Asia because a single-factor exposure requires a high level of conviction, said S&P Dow Jones’s Luk. One advantage of a blended approach to factor investing is that it avoids sector biases often present in single strategies.

Luk told AsianInvestor: “If an investor just bought the market, it would be difficult to isolate what was driving returns." By having individual factors, she argued that investors had more control over the investment outcome and could therefore better manage their long-term liabilities.

S&PDJI has been busy developing smart-beta indices and has studied how factors perform in different market cycles. Their research showed which strategies were most consistently reliable and which failed to live up to the smart-beta hype, said Luk.

“Naturally enough, momentum does well in a bull market but badly in a bear market, and worst of all in a recovery phase,” she noted. “The reason for this is that when there is an inflection point in a market, the momentum strategy will pick up the wrong signals.” According to the S&P study, the factors to use in the recovery cycle are value, growth, size and dividend.

S&P’s analysis of sources of active return in relation to smart-beta portfolio factors show that industry tilts contribute the most to annualised excess return generated by the ‘quality’ factor over the 10 years to December 2014. There are various subjective views as to what constitutes 'quality', although certain characteristics – profitability, earnings and financial robustness – are common to all. The other major contributors to return were value, low earnings volatility and high price volatility.

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