Swiss Pension Fund Aggregate Indices Performance Monitor

Credit Suisse Pension Fund Index & UBS Pension Fund Index Family

From 31.12.1999 onward, Credit Suisse calculate the first pension fund aggregate index, based on some 100 Swiss pension funds to whom Credit Suisse acts as Global Custodian. While the index has monthly increments, it is only published quarterly. With an inception date of 31.12.2005, UBS Group began to publish a family of pension fund indices, also based on custody. In contrast to the Credit Suisse counterpart, UBS publish their indices monthly. UBS distinguish pension fund indices by size: small, medium, and large pension funds, plus a general pension fund index. Below, the performance of Swiss pension fund aggregate indices is most often compared to the medium risk-tier synthetic pension fund benchmark index LPP-C40. This is a synthetic performance benchmark with a static asset allocation, of which 40% is in equities. Performance benchmarks in asset management (with the exception of peer group references) are free from any attempt to generate ‘value-added’. Thus, benchmark indices must not be read as quality reference. They are merely a description of circumstances.

Taking Advantage Of Monthly Performance Updates

The calculation of many quantitative and qualitative metrics requires large data data samples to generate meaningful results. Unlike the data for specific pension funds, any of the aforementioned aggregate indices is available with monthly frequency, thus permitting a depth of analysis and comparisons not possible with quarterly, or annual data. As individual pension funds show a very high degree of congruency with the aggregate indices used here, the analysis of monthly data for the aggregates can be taken as advance insight into pension funds investment performance released much later.

Exhibit-01 (above)

As entry into the analysis, Chart-01 shows most recent 18 months of history, rebased to 100. The graphs allow an initial, visual inspection of Swiss pension fund performance in the context of domestic financial markets, and global benchmark indices.

Exhibit-02 (below)

In Table-01, numerical data is given for fixed dates. Index values are shown for most recent months since year end. Rates of return are given, comparing across ten, five, and three years, as well as year-to-date, three months, and last month.

Exhibit-03 (above)

Chart-02 displays most recent performance data visually, for the main benchmark index LPP-C40, the Swiss Pension Fund Composite, and two pension fund aggregates. The widening gap between the Credit Suisse and UBS Indices is noteworthy. However, this could be, at least in part, due to defered reporting. Credit Suisse publish their monthly data only quarterly. Please refer to Table-1 to examine for which month a provisional estimate was used.

Exhibit-04 (below)

The chart plots 3-year normalised rates of return. The plot is smoothed for the sake of filtering out mere ‚noise’. As a result, values may appear different when compared the corresponding ‚actual’ data as shown in the Tables. Financial markets have had a pretty ‚good run’ for an uncommonly extended period of time. 3-Year normalised returns had not been negative since early 2010. By any measure, a genuine bear market -that is now likely unfolding- was long overdue, delayed only by massive central bank interventions artificially inflating financial asset prices.

Exhibit-05 (above)

Just as the previous exhibit plotted normalised return, Chart-04 shows 3-year normalised risk. The metric is ‚Observed Risk’ which is not only much more sensitive than the popular pseudo-risk proxy ‚Volatility’. It is also directional with no sign ambiguity. Exhibit 05 shows observed risk as negative value. Pension funds have traditionally been able to run risk lower than the medium risk benchmark shown here (but higher than the low risk benchmark). For a closer inspection of pension fund’s risk patterns, consult Exhibit-09, Exhibit-10, and Exhibit-13, and/or consult the section dedicated to pension fund benchmarks . Being a contrary indicator, very low risk should be taken as warning sign, suggesting excessive optimism. It had been rapidly moving in that direction from April 2018 onward. Plenty of time for pension funds to examine how much market risk they consider affordable against their liabilities, or how willing they were to fight the odds.

Exhibit-06 (below)

Swiss pension funds run their investment portfolios extremely close to benchmark indices. The exact degree of dependence (r-squared, or congruency) will vary, subject to the length of record used in the regression analysis, and the interval chosen (months, quarter, years). Chart-05 uses 36-month trails (sample size) of rates of change. At a generally very high level, r-squared values fluctuate only little, but are shown in Chart-05 using a very detailed scale. In contrast to the market weakness 2017/2018, this time, benchmark congruency has been rising, with falling markets, reaching 98.9%, a record high, suggesting that pension funds are unwilling to decouple themselves from markets for the sake of capital preservation. Put differently, the chart demonstrates that decision risk is being minimised, at the expense of safety.

Exhibit-07 (above)

What was shown graphically in Chart-05, is being given greater detail in Table-02. It shows the elements of the regression equation of all pension fund aggregates (again with LPP-C40 as x-value), including intercept (alpha) and slope (beta). R-squared among the various pension fund aggregates differs ever so slightly. While only small pension fund appear to generate negative alpha, beta values are generally too low across of pension fund segments to enjoy the benefit of positive alphas. Contrary to propaganda, positive alphas are not a measure of ‚excess return’ over benchmark. A glance at differential returns will illustrate that.

Exhibit-08 (below)

5-year normalised risk and return data are shown as scatter diagram(s) with return displayed vertically, and observed risk horizontally. A dashed diagonal indicates equilibrium between the two. Included are all three risk-tier benchmark indices, the pension fund composite as well as the Credit Suisse Pension Fund Index, and the UBS Pension Fund Index (all sizes). The left scatter displays current data, the one on the right gives values from one year previous. Comparing the two scatters shows a mild increase in normalised risk accompanied by a sharp decline in normalise returns. Simultaneously, returns are comparing, at least more so than risk. Neither any benchmark, nor any segment of pension funds has achieved a return high enough to compensate for the risks taken.

Exhibit-09 (above)

The two graphs in Exhibit-09 give a split-view of cumulative monthly gains (left) and cumulative monthly losses (right). Values for the pension fund composite are shown in colour. A black line plots data for LPP-C40, the medium risk tier benchmark. Please note that the right-hand scales in each graph may be different. They merely serve to show he direction in which pension fund’s specific (gain/loss) sensitivity moves. From April 2017 onward, pension funds gains relative to LPP-C40 have remained stable around 0.83x those of the benchmark. Since early 2018, relative losses, while below 1.0x and below relative gains, have risen more than those of the benchmark. Put differently, pension funds have been increasing risk at exactly the wrong time. This pattern strongly suggests that pension funds are driven by a fear of missing out on the upside, blindly trusting that increasing risk exposure will be rewarded, and all that near the top of one of the worst market bubbles in living memory. By doing that, they are repeating a mistake already made just before every single bear-market in the last 20 years.

Exhibit-10 (below)

Table-03 in Exhibit-10 changes the analytical time frame to ten years. The top section positions starting and end values in the context of high and low values achieved in that time. Thanks only to the strong gains in April, this erosion now looks mild again. The table should be seen in conjunction with Chart-10 in Exhibit-13 further down.

Exhibit-11 (above)

Shown is a straightforward plot of LPP-C40 and the Swiss Pension Fund Composite, re-based to 100 ten years ago. For reference the compounding legal minimum rate of interest payable on account balances is also shown.

Exhibit-12 (below)

The upper graph in Exhibit-12 illustrates 120 months performance of Swiss pension funds against each of the three risk-tiers. This is supplemented with the development of the higher risk tier relative to the lower one. If that line increases, then risk is being rewarded. The display emphasises the opportunity, if not outright need, to implement shifts in strategy, rather than tactic. On balance, and precisely because of their pattern of mirroring a benchmark, regardless of market cycle, pension funds keep failing to outperform any of the risk-tiers for any relevant length of time. They appear content to remain at the mercy of financial markets, no matter what. Such fatalism can not possibly qualify as professional.

Exhibit-13 (above)

The chart plots drawdown from all-time-high of the Swiss pension fund composite during the latest 120 months. Obviously it would not be feasible to expect any managed fund to be immune against drawdowns. Thus, the drawdown is put into an appropriate context: the horizontal lines show the normalised annual rate of risk for all risk-tiers. So if a pension fund pretending to run a lower-risk strategy is beginning to suffer losses that are in excess of ‚normality’ then it should at least consider to view initial losses as the cheapest. If nothing else, each pension fund should know their specific ‚line drawn into the dust’, where discussions about vague future return expectations end, and a contingency plan is implemented, protecting against additional losses. The chart demonstrates how pension funds favour ‚hope over experience’.

Exhibit-14 (below)

If it has not become clear by now, how random pension fund performance is, then this illustration should finally prove that point. Dividing the entire history since 31.12.1999 into months, quarters, and years, it shows counts of pension fund performance better or worse than each of the three benchmarks and the average over- or underperformance per time increment. The main portion in the middle indicates the resulting frequency of success, regardless of extent, but does so net of pure chance (50:50, or ‚coin flips). Two comments on that: Firstly, only the lowest risk-benchmark is being beating marginally more often than random. The excess frequency is insufficient to suggest professional expertise. Secondly, regardless of success frequency, the magnitude of relative gains is nearly always smaller than the magnitude of relative losses. If this were a widget factory, one would close it down on the spot for failure to generate anything consistent, or useful. That kind of output does not justify any expense at all. One can only hope that such an analysis of aggregates masks at least a worthy minority of competently managed pension funds.

Exhibit-15 (above)

Finally, an illustration of pension funds congruency with LPP-C40 using all complete years since 31.12.1999. Current year-to-date is treated in the analysis as if it were a year in itself. Obviously, such a bird’s-eye view of the correlation does not reveal how congruency has emerged, or is fluctuating. But it does serve to show that in spite of a positive alpha, the on-balance performance over the benchmark is quite negative. For this to change, either alpha would have to be considerably higher, and/or beta. Coupled with that low alpha, a beta of 0.71 is way too low to permit pension funds to outperform this benchmark while maintaining such a high correlation.

One can not achieve a better result with an identical portfolio, or for that matter, a worse one. When pension fund’s still manage to achieve a worse result, then this is explained by investment management fees they pay to managers who clearly do not deserve them.

Data Sources

Raw data underlying all calculations and illustrations was sourced from:

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