DIVERSIFIED GROWTH FUNDS: HOW DYNAMIC ARE THEY?

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1 DIVERSIFIED GROWTH FUNDS: HOW DYNAMIC ARE THEY? March 2016 Executive summary Whether active funds are truly actively managed is a hot topic at the moment. Most of the attention has been directed at equity funds managed against index benchmarks; here we look at Diversified Growth Funds, which often refer to themselves as dynamic, but have no index benchmark. How active are they? Though comparing asset allocation across the DGF universe is not straightforward due to different approaches to reporting and the use of derivatives, we found that some DGFs change their high level asset allocation much more actively than others. o There seems to be some evidence that for funds of a similar average asset average allocation structure, more dynamic funds have exhibited lower risk as compared with less dynamic funds. o Funds with a pre-disposition to either high or low equity weightings tend to be less dynamic than the average. Fund size and fund style were not good predictors of the level of asset allocation activity. Overall, our analysis confirms that the universe of Diversified Growth Funds is indeed diverse, and there are no easy short cuts to decide which fund is right for you. Introduction There has been much discussion recently about the extent to which actively managed funds are truly active. The majority of analyses have focused on equity managers versus market benchmarks. By contrast, Diversified Growth Funds, as defined by PiRho, do not measure their performance against specific asset-based benchmarks, but versus cash or inflation targets. Indeed, one reason investors have been drawn to invest in DGFs is that such funds offer exposure to market opportunities as they arise which, it may be assumed, requires a certain degree of dynamism in their asset allocation. Is it necessary for DGFs to be active with regard to asset allocation in order to justify active fee levels? Although there is a case for set and forget allocations, most DGFs explicitly or implicitly suggest that they add value by taking active asset allocation positions. In fact DGF managers often describe themselves as dynamic, and some use this term in the name of their fund. Of course, there is no single definition of dynamism. Assessing dynamism in respect of asset allocation, for example, requires a number of assumptions: some managers have different definitions of asset classes and may classify assets such as convertibles or private equity in different ways. DGFs also operate with very different degrees of leverage or engage in relative value strategies (which may not be easily classified into a mainstream 1

2 asset class). Analysing asset allocation and comparing it between funds is not straightforward. High level asset allocation (i.e. equities, fixed income, alternatives, cash) provides the best degree of comparability between funds. In this paper, we therefore use this approach to analyse our Diversified Growth Fund Universe to assess how dynamic these funds are. Within our broad DGF universe we identified 19 funds that meet the size and track record criteria of at least 50 million in managed assets and at least 4 years of comparable data. The time horizon chosen is long enough to include relatively benign periods as well as volatile months surrounding the 2013 taper tantrum and 2015 summer flash crash. Some of the major DGFs, such as Invesco or Aviva, do not meet the track record criteria and hence are not included in this analysis. As far as possible we have used asset allocation data provided by managers and their definitions of asset classes from the manager factsheets; however in some cases additional information was requested from the managers directly to confirm aggregated holdings. In order to focus on comparability we use quarterly figures since not all of the managers produce monthly factsheets. During the 4-year period to end 2015 there have been a number of changes in the observable asset allocation structure among the DGFs. Fig 1 below shows that although the average values (red diamonds) remained at comparable levels, allocation ranges (e.g. maximum equity weight for the DGFs in our universe minus the minimum equity weight) have changed, especially for fixed income holdings. Fig 1: Asset allocation ranges of DGFs between December 2011 and December asset allocation in dgfs paper.xlsx Source: Manager data, PiRho 2

3 Analysis of dynamism In order to analyse the DGF managers degree of dynamism we have focussed on equity weightings. Investors in DGFs, and pension funds in particular, often hold DGFs in place of pure equity exposure; furthermore unlike alternatives, for example there is a reasonable degree of homogeneity in terms of those investments classified as equities by DGFs. For the charts that follow we look at the extent of the quarterly moves for equity allocations as a measure of dynamism. For example, a fund which exhibits a maximum move from 30% to 40% in equities over one quarter (i.e. a +10 percentage point change) is given a higher implied potential degree of dynamism than another fund which moved from 45% to 40% (i.e. a -5 percentage point change). We then use a second measure, looking at the highest and the lowest equity weightings for each individual fund over the entire period. By combining the two approaches we identify funds with the highest degree of dynamism in their equity allocations (See Fig 2 below) 1. Fig 2: Changes in DGFs equity allocation over the 4 years to December We summarise the underlying reference data in appendices 1-3 at the end of this paper. 3

4 As shown in Fig 2, funds that are broadly dynamic on one measure (range in overall equity allocation), not surprisingly tend to be more dynamic on the other (quarterly changes). Combining the rankings for each fund enables us to give an overall rank for the degree of asset allocation dynamism; this is presented in Fig 3 below. Fig 3: Ranking order of DGF funds for Dynamism Fund Rank of range in equity allocation over entire period Rank of range in monthly change in equity weighting Overall rank More Dynamic Baring IBOF Henderson Schroder Life F&C Ruffer M omentum Newton RR Blackrock DDGF Aberdeen DGF Aberdeen M AF Newton M ADR Trojan Baillie Gifford GARS Putnam Blackrock M ASF M&G Prudential Less Dynamic Pyrford

5 What influences whether a fund is likely to be dynamic? Surprisingly perhaps, the level of equity exposure of a DGF appears to have some link with the degree of dynamism. The chart below shows the relationship between the combined dynamism rank and the average equity weighting of the funds over the four years to end December As shown in Fig 4, the more dynamic funds typically operate with equity weightings within the 30% to 50% range. In comparison, the less dynamic funds have a broader spread of average equity weights. It would appear that the more dynamic funds have no pre-disposition to high or low equity weights. However, average equity weights give only a partial insight, since the 30% to 50% average equity range also includes some of the most and least dynamic DGFs. Fig 4: DGFs dynamism and average equity weighting 5

6 Is there a link between fund size and dynamism? One might hypothesise that size could have an impact on the degree of dynamism within a DGF, with larger, more established funds potentially expected to be less dynamic than smaller funds for a number of reasons. These might include smaller funds finding it easier to trade, while larger funds might, perhaps, be more focused on asset gathering. However, the table in Fig 5 below suggests that asset size does not appear to be a determinant of the degree of change in asset allocation. Fig 5: DGFs Dynamism and PiRho classification Fund size Overall rank Over 1bn assets 1 More Dynamic Over 1bn assets 1 Under 1bn assets 3 Over 1bn assets 4 Under 1bn assets 5 Over 1bn assets 6 Under 1bn assets 6 Over 1bn assets 8 Over 1bn assets 9 Under 1bn assets 9 Under 1bn assets 11 Under 1bn assets 12 Over 1bn assets 12 Over 1bn assets 14 Over 1bn assets 15 Under 1bn assets 16 Under 1bn assets 17 Under 1bn assets 18 Over 1bn assets 18 Less Dynamic 6

7 Does Dynamism matter? The above analysis demonstrates that in practice some funds seem to be significantly more dynamic than others. The following analysis asks a different, and perhaps more important question: do funds that demonstrate a more dynamic approach to asset allocation add any value versus other less dynamic funds? We have not found a link between the degree of dynamism and the level of returns. Therefore in this paper we address risk rather than returns. Fig 6 shows the link between the annualised volatility of DGFs and the average equity exposure in their portfolio over the four year period to end December Not surprisingly, funds with higher average equity weightings tend to show higher annualised volatility. However there is quite a lot of dispersion around this trend. We analysed two groups, A and B, each with similar average equity weightings, in order to examine whether the degree of dynamism appears to add value within its group. Fig 6: Annualised volatility and average DGF equity weightings over 4 years DGF Paper Dynamism Data.xlsx Source: Manager data, Datastream, PiRho 7

8 Fig 7 below shows the relationship between the annualised volatility of DGFs and the combined dynamism score for those DGFs in group A with an average equity weighting over the four year period to end December 2015 of around 34%. The more dynamic funds in this group tend to have managed volatility better than the average, but there are a number of outliers to this relationship. The Standard Life GARS fund in particular has lower exhibited volatility than would be expected on our measure of asset allocation dynamism. It may be, however, that due to their extensive use of derivatives the underlying degree of dynamism is higher than appears in our high level analysis. This may also be the case for other funds that make significant use of derivatives. By contrast Pyrford s low volatility seems to have benefited from its large stable holdings in government bonds over the period (a time where there has been extreme de-correlation of these two assets). Fig 7: Group A DGFs (funds with average equity weighting around 34%) Historic annualised volatility and Dynamism Score DGF Paper Dynamism Data.xlsx Source: Manager data, Datastream, PiRho Moving to Group B (average equity weighting over the four year period of around 48%) as shown on Fig 8 overleaf, there appears to be a link between the annualised volatility of DGFs and the combined dynamism score. It appears that the funds with higher combined PiRho scores for dynamism have managed volatility better than the average, although the sample size is very small. However, Newton Real Return appears to be an outlier to this relationship, with much lower volatility versus the dynamism score. Possible explanatory factors could include: use of equity options to protect downside and periodic high cash positions. 8

9 Fig 8: Group B DGFs (funds with average equity weighting around 48%) Historic annualised volatility and Dynamism Score DGF Paper Dynamism Data.xlsx Source: Manager data, Datastream, PiRho PiRho Classification There are four broad categories within the PiRho DGF Universe: Capital Preservation: funds for which capital preservation is a primary objective; they tend to be more cautious than the average and may incorporate derivative strategies to protect against sharp short term losses. Sharpe: characterised by an explicit focus on the risk return trade-off and a risk management process which often leads to defensive actions during bear markets Growth: a tilt towards investment in growth assets regardless of market environment. Diversification is in itself may be viewed as a main risk tool. Hedge Fund Lite: a very heterogeneous group, with a tendency to depend heavily on manager skill (through significant use of leverage and/or relative value strategies), rather than on market beta. We have shown the classification of the DGFs and the degree of dynamism on the Fig 9 overleaf. 9

10 Fig 9: Dynamism and PiRho DGF classification PiRho DGF classification Overall rank Sharpe 1 More Dynamic Hedge Fund Lite 1 Sharpe 3 Growth 4 Hedge Fund Lite 5 Capital Preservation 6 Sharpe 6 Capital Preservation 8 Sharpe 9 Sharpe 9 Growth 11 Growth 12 Capital Preservation 12 Growth 14 Hedge Fund Lite 15 Hedge Fund Lite 16 Hedge Fund Lite 17 Growth 18 Capital Preservation 18 Less Dynamic Hedge Fund Lite funds typically use derivatives to implement relative value trades (e.g. long US Equities, Short European Equities) and hence the physical amount held in each asset class may appear little changed from quarter to quarter. Three out of five of the least dynamic DGFs, based on this analysis, are classified by PiRho in the Hedge Fund Lite category. However, this category also has the highest dispersion in terms of asset class dynamism, highlighting that such funds are idiosyncratic and individual analysis is essential. We would expect Sharpe funds to be more dynamic than Growth or Capital Preservation; the style suggests that they are likely to be constantly tinkering with asset allocation to attempt to get the best risk-return trade-offs as market conditions change. Our analysis on dynamism seems to bear this out. Interestingly, there is little to choose between Capital Preservation and Growth funds in terms of dynamism. This possibly reflects the point made with above that each category has a predisposition to either a low or high equity weighting which tends to be fairly stable over time. Krzysztof Lasocki, Nicola Ralston and Phil Irvine 10

11 Appendix 1: Equity Weightings at end quarter Date Aberdeen DGF Aberdeen MAF Baillie Gifford Baring Blackrock DDGF Blackrock MASF F&C SLI GARS Henderson IBOF M&G Prudential Momentum Newton MADR Newton RR Putnam Pyrford Ruffer Schroder Life Trojan Dec-11 30% 67% 11% 24% 24% 10% 30% 32% 40% 10% 50% 20% 37% 41% 21% 35% 42% 31% 33% Mar-12 37% 69% 10% 46% 31% 15% 40% 29% 33% 28% 51% 21% 37% 42% 24% 35% 49% 43% 33% Jun-12 35% 62% 10% 32% 28% 17% 38% 26% 41% 17% 49% 27% 39% 43% 20% 35% 46% 40% 33% Sep-12 37% 63% 10% 30% 35% 15% 41% 28% 45% 33% 50% 24% 38% 47% 20% 35% 50% 48% 31% Dec-12 37% 64% 11% 43% 40% 15% 43% 29% 42% 28% 52% 24% 37% 51% 21% 35% 55% 49% 29% Mar-13 35% 64% 18% 50% 41% 15% 43% 30% 37% 34% 49% 31% 34% 55% 24% 35% 46% 48% 31% Jun-13 35% 65% 16% 56% 39% 15% 31% 32% 38% 27% 48% 34% 33% 55% 23% 35% 48% 47% 34% Sep-13 35% 63% 18% 49% 37% 15% 36% 35% 37% 38% 48% 37% 35% 52% 24% 35% 48% 52% 31% Dec-13 35% 73% 16% 52% 40% 15% 37% 39% 38% 42% 49% 42% 36% 56% 27% 35% 52% 54% 40% Mar-14 39% 72% 15% 55% 40% 14% 31% 36% 39% 37% 49% 35% 37% 53% 25% 35% 49% 51% 42% Jun-14 38% 71% 15% 57% 37% 14% 39% 38% 38% 43% 50% 27% 28% 55% 23% 35% 51% 52% 43% Sep-14 40% 70% 18% 48% 37% 15% 33% 36% 36% 44% 50% 27% 32% 59% 27% 30% 44% 51% 43% Dec-14 40% 68% 21% 57% 38% 15% 34% 39% 40% 33% 49% 30% 29% 57% 27% 30% 46% 48% 40% Mar-15 31% 67% 21% 53% 39% 13% 34% 39% 34% 34% 51% 29% 34% 48% 26% 30% 42% 57% 40% Jun-15 25% 67% 21% 49% 33% 14% 24% 37% 18% 30% 49% 27% 34% 46% 20% 30% 43% 50% 39% Sep-15 28% 63% 23% 56% 35% 12% 29% 34% 29% 14% 49% 28% 31% 38% 24% 30% 41% 41% 41% Dec-15 31% 63% 24% 55% 35% 14% 27% 33% 22% 17% 52% 30% 32% 43% 23% 30% 39% 46% 41% DGF Paper Dynamism Data.xlsx Source: Manager data 11

12 Appendix 2: Examining quarterly movements in equity weightings Aberdeen DGF Aberdeen MAF Baillie Gifford Baring Blackrock DDGF Blackrock MASF F&C SLI GARS Henderson IBOF M&G Prudential Momentum Newton MADR Newton RR Putnam Pyrford Ruffer Schroder Life Trojan Biggest positive quarterly change in 7.5% 9.6% 7.1% 21.6% 7.6% 4.7% 9.4% 4.3% 11.1% 17.9% 2.5% 6.8% 4.6% 4.7% 4.1% 0.0% 7.0% 12.3% 9.0% equity weighting Biggest negative quarterly change in -8.4% -6.4% -2.6% -14.0% -6.2% -2.3% -11.7% -3.8% -16.3% -16.2% -3.0% -7.6% -9.0% -8.7% -6.8% -5.0% -9.0% -9.5% -3.0% equity weighting Range in quarterly change in equity weighting 15.9% 16.0% 9.7% 35.7% 13.8% 7.0% 21.0% 8.0% 27.4% 34.1% 5.5% 14.4% 13.5% 13.4% 10.9% 5.0% 16.0% 21.8% 12.0% Appendix 3: Examining movements in equity allocation over the entire period Aberdeen DGF Aberdeen MAF Baillie Gifford Baring Blackrock DDGF Blackrock MASF F&C SLI GARS Henderson IBOF M&G Prudential Momentum Newton MADR Newton RR Putnam Pyrford Ruffer Schroder Life Trojan Maximum equity weighting over period 40.1% 72.6% 24.3% 57.0% 40.8% 17.3% 43.1% 39.4% 45.2% 43.6% 52.1% 41.5% 39.4% 59.2% 27.2% 35.2% 55.0% 57.0% 43.0% Minimum equity weighting over period 24.8% 62.1% 10.1% 24.3% 23.8% 10.0% 24.1% 26.5% 17.6% 10.4% 47.7% 20.3% 27.7% 37.9% 19.6% 30.0% 39.0% 30.6% 29.0% Range in equity allocation over entire 15.3% 10.5% 14.2% 32.7% 17.0% 7.3% 19.0% 12.9% 27.6% 33.2% 4.4% 21.2% 11.7% 21.3% 7.5% 5.2% 16.0% 26.4% 14.0% periods 12

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