Divergence in central bank monetary policies and their changing views have created stark uncertainty in the bond market. The US Federal Reserve, which believed it would raise interest rates four times this year, has not yet followed through with one 2016 rate hike.
Japan’s central bank, which introduced negative rates, went against market expectations this week and decided to hold back on further stimulus. However, the European Central Bank’s aggressive programme announced earlier this month was close to expectations.
Further contrast is seen in Asia, where central banks in China and India, for example, continue to ease monetary policies in the hope of stimulating economic growth.
Yet bond market sentiment may to gain some support because emerging market currencies have had a strong showing so far this year. The recent return of Argentina to bond issuance, for instance, resulted in a record-setting $16.5bn sale which drew $70bn in orders.
In this context, FSA compares two global bond funds – the New Capital Wealthy Nations Bond and the Pimco Global Bond Fund.
Chuen Peng Tan, head of investment products and services at CIMB Private Banking in Singapore, provides a comparative analysis.
Investment Strategy
The two funds are both unit trusts domiciled in Ireland, but their time-in-market differs. The Pimco Global Bond Fund has been in the market since 1995 while the New Capital Wealthy Nations Bond Fund has been the “new kid on the block”, launching in September 2009, Tan said.
The New Capital Fund is managed by EFG Asset Management and advised by Stratton Street Capital. It adopts a combination of top-down and bottom-up analysis. The main investment philosophy is to “lend to someone who has the ability to repay debt”, he said.
New Capital’s top-down approach consists of proprietary macro models. For example, using a proprietary net foreign asset model, countries are first screened by their ability to repay debt, Tan said. This methodology measures a country’s foreign value assets minus any debts owed to foreigners. The value is expressed as a percentage of GDP.
“[The manager] will not invest in countries with net foreign liabilities greater than 50% of their GDP, regardless of their index weighting or supposed credit rating, hence setting the geographical allocation of the portfolio,” he said.
The firm applies its relative value model to identify the most undervalued bonds and focuses bottom-up analysis on those bonds, he said.
“This analysis includes expected upside or downside from the relative value model, general sentiment of the business and industry positioning, government support as well as assessment of financial metrics. They also consider debt ranking factors and research data from external rating agencies,” he said.
For Pimco, a similar process of combining both top-down and bottom-up strategy is adopted.
“Pimco’s top-down approach consists of an annual secular forum where their investment professionals focus on the global economic outlook and financials over the next three-to-five years. These long-term investment strategies are fine tuned at quarterly meetings, where members from Pimco’s global network discuss and debate the state of global markets and economies,” he said.
The firm’s portfolio committee conducts further discussions to identify key points of the macroeconomic outlook and find opportunities and risks for different regions.
“A bottom-up analysis, which involves on-the-ground research, is subsequently combined to achieve a holistic result,” he added.
Relative to the respective benchmarks, Pimco’s objective is to outperform a chosen benchmark on a consistent basis, while maintaining benchmark-like risk, he said.
By comparison, New Capital takes the view that as a country becomes more indebted, its weight in the index increases, whereas smaller, well-run economies with little debt have a very low representation.
“Hence, New Capital is more inclined to follow their unique net foreign asset ratio model to decide their asset allocation.”
Although both funds invest in global bond markets, they assume exposures in different sectors of the market, Tan said.
New Capital invests solely in investment grade corporate, quasi-sovereign and sovereign bonds, while Pimco has a broader spectrum that consists of high yield, mortgage-backed securities, municipals and interest rates.
“They also implement their strategies using instruments apart from direct bonds, such as derivatives, forwards and swaps. Pimco has a higher exposure to developed markets like US and Europe while New Capital’s credit selection process results in higher allocation to the emerging markets, such as Asia and Middle East.”
Sector Comparison
| New Capital | % | Pimco | % |
| Quasi | 65.51 | Government Related | 70.8 |
| Corporate | 22.96 | Inflated linked | 11.8 |
| Sovereign | 7.71 | Securitised | 6.2 |
| Supranational | 1.31 | Emerging markets | 4.7 |
| Cash | 2.50 | Investment Grade Credit | 4.5 |
| High yield credit | 1.6 |
Source: CIMB
Performance
As of 31 March 2016, New Capital’s one-year performance was 4.3% while Pimco returned 2.32%, according to data from CIMB.
Over three- and five-year periods, New Capital returned 3.31% and 6.04% respectively, while the Pimco product returned less — 2.58% and 4.94% respectively.
“The conviction to follow the macro models and the credit selection process likely explained the performance of New Capital,” Tan said. “In 2015, while most investors avoided oil-dependent countries like Russia and the Middle East, New Capital held on to their convictions that these countries will still be creditworthy with low level of government debt even as they faced pressure and stress from the crash in oil price.”
On the other hand, Pimco’s product demonstrated lower volatility. Over a one-year period, the fund’s standard deviation was 3.12% and New Capital’s was 5.44%.
Over a five-year period, standard deviation for Pimco was 3.16% and for New Capital it was 6.23%.
The two funds over over a five-year period. The Pimco fund’s lower volatility is evident during the global market rout that began at the end of 2015.
Source: FE Analytics
