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Auto-calls versus GARS

By Paul Milburn - Investment Manager at Lowes Financial Management

For many years structured products have struggled to establish themselves as a mainstream asset class for investors with many financial advisers. This comes despite the defined return profile they offer within specified market conditions and the strong overall returns which they have produced. There are two common arguments given by some advisers as to why they don’t recommend structured products, counterparty risk and complexity.

When investing in a structured product, you accept that you are taking on the counterparty risk of the issuing bank. Failure of the institution could see an investor lose all of their investment and so it pays to diversify your investment portfolio and not take excess risk. Much information is readily available on the counterparty and will be stated within product literature.

The second common reason put forward by some advisers for not recommending structured products is that they are complex, stating that it is difficult to explain to clients how the products work and the risks which exist. However, the return outcome for these products is clearly stated, along with any attached risks. In contrast to other investments, you know exactly how a structured product will perform in different market conditions.

As advisers who believe that structured products can play a part in client portfolios, this got us thinking about other asset classes commonly invested in which also carry these two concerns. When it comes to the question of what types of more mainstream and generally accepted funds which potentially contain counterparty risk and complexity, we were drawn to the IA Targeted Absolute Return sector. In particular, we consider the most popular fund within this sector, the Standard Life Investments Global Absolute Return Strategies fund, commonly known as GARS.

Since its launch in May 2008 the fund has been incredibly successful, achieving an annualised return of 6.5% with an annualised volatility of only 4.2% over the last 5 years. This fund looks to invest in many strategies, based on macroeconomic outlook, typically executed through the use of options and futures. The blend of these strategies is expected to reduce volatility substantially within the overall portfolio. However, the strategy of employing futures and options as a way of investing in the managers’ chosen themes introduces counterparty risk into the fund. Although there is typically a margin call which will require daily settlement, there remains the potential risk that the counterparty of such products may fail.

With this fund, complexity is also a potential concern. Strategies and tools are employed, many of which a typical private investor will be unfamiliar with. For example, strategies quoted at the end of December within the fund included “Long Equity Variance” and “Long European Payer Swaptions” . Most private investors would not understand the ‘investment’ being implemented or the strategy or investment tool being used to achieve it. However, due to the ‘outcome’ success of the fund and the change in investor psychology since the credit crisis, the fund has been incredibly successful in amassing assets under management, standing at a staggering £23bn at the end of December 2014.

Let us again therefore consider structured products. In this instance we shall consider a simple auto-call, with the underlying asset as the FTSE 100. We know that the product will strike on a particular date, when the FTSE 100 index level will be recorded. We know that unless the FTSE 100 falls below a stated barrier, for example 40% below the initial index level, our capital will be returned, subject to the counterparty remaining solvent. Furthermore, some products available are collateralised using high quality assets such as gilts, which further reduces the credit risk. We accept that the GARS fund has greater diversification in terms of exposure to underlying strategies and asset classes covered. At the end of December, GARS had 33 individual strategies in place. Our simple structured product example is exposed to one asset class only and only one index. This may give rise to the latter displaying greater volatility between the kick-out and maturity dates, but we know that returns are defined, market protection is provided and are aware of the market conditions under which gains or losses would be made.

So, how do the returns compare between structured products and GARs? At StructuredProduc-tReview.com we have substantial maturity data and have been able to extract all capital-at-risk auto-calls, with the FTSE 100 as their underlying index which have been released and subsequently matured over the period of GARS existence, of which there were 327. We have calculated the average annualised return of all these plans, which comes out at a strong 9.22% with an average term of 1.49 years. For comparison purposes we then calculated the return of GARS over each of the plan dates, to arrive at an average annualised return of 7.17%, again an attractive return from an investment which has low volatility.

The distribution of returns paints an interesting picture, as illustrated in the chart below. Here we can see that the distribution of returns achieved by capital-at-risk FTSE 100 auto-calls has a narrower distribution of returns compared to GARS.

Distribution of Returns - FTSE 100 Autocalls vs GARS

Source: StructuredProductReview.com

The purpose of this article is not to dismiss GARS as an investment. The fund is clearly successful in achieving its desired outcomes, giving rise to a substantial amount of assets being amassed. With a suitable level of education and learning undertaken, this fund will be suitable for particular investors. However, we would argue the same for structured products, in that after suitable learning and education, these products, with their defined outcomes in specific market conditions, will be a suitable investment in a diversified portfolio, and that the argument of counterparty and complexity is not enough to dismiss the investments.