A solutions framework for generating alpha


A solutions framework for generating alpha

01 Nov, 2022

Traditionally, super funds have sought to achieve superior returns for their members by investing in external active managers, who in turn seek to deliver alpha through security selection and/or market timing within their investment universe. For example, an Australia Equity manager is benchmarked against S&P/ASX 300 and typically invests exclusively within that universe. For the super funds themselves, APRA’s Your Future, Your Super performance test defines the relevant benchmark for any given investment and, simplistically, alpha is measured as the out/under-performance of an investment versus that benchmark.
Insto table Aug 22

We introduce a different framework for generating alpha. 

Our overall philosophy revolves around utilising investment components, or building blocks, to construct investment solutions. The appeal of this approach is that we can now source alpha and beta from different places and customise investment solutions to meet specific investor requirements. This contrasts with a more “take it or leave it” approach when considering an investment product. It’s a far more flexible approach that allows us to create a spectrum of solutions, not just the binary “passive vs active” of traditional investment products, and also enables efficient switching between individual components as outcomes and/or objectives evolve.

Examples of the spectrum of investment solutions

Figure 1: Examples of the spectrum of investment solutions

Enhanced Beta

Consider a simple example for global equities. We can access beta directly by, for example, receiving the total return on MGWD (MSCI ACWI AUD Net Total Return Index) at a funding spread of BBSW – 10bp. Because the TRS is unfunded, we can take the cash and invest it in a money market fund earning, conservatively, BBSW flat. The net result (TRS + Cash) is the benchmark return + 10bp. The most basic of strategies has delivered 10bp of “alpha”! 

A simple equity index TRS and cash enhanced beta solution

Figure 2: A simple equity index TRS + cash “enhanced beta” solution

The example consists of 2 building blocks: 1) an equity index total return swap (TRS); and 2) cash. It delivers alpha (or at least something very much resembling alpha) because the funding on ACWI TRS is particularly cheap.

We can deliver additional alpha if we can earn additional excess return on the cash building block. For example, term deposits currently offer in the region of BBSW + 30bp or even higher. We have also traded structured notes linked to the term structure of EU Carbon Allowance Futures with a hold-to-maturity yield of BBSW + 50bp or more. And Challenger offers term annuities at BBSW + 60bp (higher for longer terms). More generally the alpha we can generate in this way can be calculated as follows.

Calculation graph

This works when we’re able to access the beta synthetically, and the excess return we can earn on cash exceeds the funding spread on the TRS (when the funding spread is negative, we earn additional alpha). Here, the excess return is fixed at the outset, as is the funding spread, so the alpha we can generate is known. Also, the tracking error versus the benchmark will be minimal if not zero, so these enhanced beta solutions can readily replace passive benchmark allocations. If the alpha generated is high enough, we can even consider complementing active allocations with an enhanced beta solution.

Alpha-Lite Solutions

If an investor is willing to take some tracking error risk, we can expand the concept further, and explicitly look to utilise the framework to populate the active allocations bucket within portfolios. When we invest with active managers, we are willingly taking tracking error risk in return for the possibility of earning alpha. We should similarly be willing to take tracking error in either, or both, of the ‘beta’ and ‘alpha’ building blocks.

Depending on the amount of tracking error risk we are willing to take, we can substitute some, or all, of the cash building block outlined above with a more active source of spread, for example a short-duration credit fund. The spread earned over cash is no longer certain, but the expected excess return should be higher. Even though the return from the credit fund is not certain (as in the previous cash example), it is generally more consistent than equity alpha, for example. 

An alpha-lite solution consisting of an equity TRS and short-duration credit fund

Figure 3: An “alpha-lite solution” consisting of an equity TRS and short-duration credit fund

By mixing and matching sources of beta and alpha, it will often be possible to construct a custom solution with more reliable alpha. The example here combines equity beta with credit spread. The returns from the combination are going to look very much like equities, since equities are more volatile than short duration credit spreads. The investment solution can sit in the equity bucket, and any positive return from the credit building block will manifest as alpha in the equity bucket. This might be a good approach where the beta funding spread is higher, or when a higher target level of alpha is desirable, or even when looking for an alternative to an inconsistent active equity manager.

Alpha Solutions

In the previous example, we basically combined 2 betas (equity and credit) and dressed one (credit) up as alpha. It looks like alpha, because the overall return from the combination will in many (most?) instances outperform the relevant equity benchmark. But it isn’t really alpha in the truest sense of the word. Without getting too caught up with what is and is not alpha, suffice to say that it is probably true that many active managers might also not be delivering “true” alpha.

In the context of active management, the real beauty of our building block approach is that we can mix and match betas and (true) alphas from different places. An active equity manager invests in a portfolio of stocks and seeks to outperform the investment benchmark. The alpha and beta are comingled in one portfolio, which delivers one return, which can be deconstructed into beta (the market performance) and alpha (the residual).

Active manager vs solutions building block approach

Figure 4: Active manager vs solutions “building block” approach

For the typical active manager, the portfolio generating the beta is the same as the one delivering the alpha, so there is no diversification benefit between beta and alpha sources. Our approach allows us to take any beta and combine it with any alpha. If the alpha and beta have low correlation, there can be substantial diversification benefits within the solution. This allows us to take uncorrelated alternatives alpha from, say, our Challenger Liquid Alternatives Balanced Fund, and combine it with an equity beta to create an investment solution to be deployed in the equity bucket.

The chart below shows the performance of a hypothetical solution for an international equities investment which takes $100 of exposure to MGWD and combines it with $70 held in cash and $30 invested in our Liquid Alternatives Balanced Fund. The cash is more than enough to cover any margin requirements on the equity index TRS, and our liquid alts fund delivers alpha of just over 100bp pa, with slightly lower overall volatility than the benchmark.

Hypothetical performance of a alpha solution comprising ACWI TRS cash and Liquid Alternatives Balanc

Figure 5: Hypothetical performance of a “alpha solution” comprising ACWI TRS, cash and Liquid Alternatives Balanced Fund

Beta replication

An equity index TRS is beta in the truest sense of the word – it delivers the exact return of the benchmark index. There is a funding cost associated with it, but we also maintain the use of the cash which can earn sufficient return to more than cover the funding costs, as outline previously. However, not all indices can be accessed directly and/or synthetically.

Where a beta cannot by accessed directly, we might seek replicate benchmark beta indirectly. When moving to a building blocks approach with an alpha-generating objective in mind, it doesn’t really matter whether the tracking error comes from the alpha-block or the beta-block, or both. So long as the alpha being generated is sufficient to justify the overall tracking error (the same could be said for a traditional active investment), the solution is a viable approach.

For example, we have built custom solutions for clients in their fixed income portfolios where we utilise bond futures to deliver returns resembling the duration component for the benchmark fixed income indices, to be paired with unconstrained absolute return fixed income investments. The beta of the benchmark is roughly delivered by the bond futures, while the alpha is delivered by the absolute return from the unconstrained bond fund. On its own, the unconstrained bond investment might not be able to beat the fixed income benchmark during periods of falling interest rates, even if it is delivering on its core investment objective of delivering positive absolute return regardless of market environment. However, when combined with the beta replication portfolio (the bond futures), the total return of the investment solution delivers long term alpha over the benchmark.

Unconstrained bond fund cant keep up with benchmark during FI rally

Figure 6: Unconstrained bond fund can’t keep up with benchmark during FI rally.

Futures replication does a reasonable but imperfect job of tracking the benchmark

Figure 7: Futures replication does a reasonable, but imperfect, job of tracking the benchmark

Beta replication combined with unconstrained bond fund can transform an absolute return product into

Figure 8: Beta replication combined with unconstrained bond fund can transform an absolute return product into a benchmark aware investment solution.

Final thoughts

For the purposes of the discussion here we have outlined a simple beta-block plus alpha-block framework using several illustrative examples. The examples are simple ones which can be easily implemented in the real world. However, it’s the concept, rather than the specific examples cited, that’s important. Once fully understood, the approach can be taken much, much further, and is applicable to many different aspects of portfolio construction. Low correlations between building blocks, lower overall fee outcomes, portable alpha and more consistent alpha generation are just some of the aspects to consider, and of course we can add many more dimensions by creating investment solutions out of more than just two building blocks.

Customised investment solutions can be particularly useful in addressing benchmarking problems associated with the YFYS performance test. For super funds, the cost associated with failing the YFYS performance test is high. Therefore, high tracking error versus the benchmark is particularly undesirable. Some tracking error is required in order to deliver alpha, however, too much tracking error increases the risk of failing the performance test at some point in the future. The framework can be used to help deliver more consistent alpha in more parts of the portfolio at lower cost. 

To find out more please contact the Solutions team at solutions@challenger.com.au.