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 compared to the a medium risk-tier synthetic pension fund benchmark index LPP-C40. This is a synthetic performance benchmark with a static asset allocation. 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

Exhibit-1 (above) depicts annualised returns for a Swiss Pension Fund Composite Index, reflecting performance of the Credit Suisse Pension Fund Index and the UBS Pension Fund Index for funds of all sizes. The composite is shown alongside the benchmark ‘LPP-C40’ (middle risk tier). All returns are calculated to the most recent date. The striking piece of information emerging from this simple, initial glance is that pension funds in general have failed to match, much less exceed, returns from an unselected representation of the investment environment, over just about any time horizon that could be considered meaningful: Since the anchor date (31.12.1999) some 20 years ago, over trails of ten, five, and three years, and most the recent twelve months.

The table of Exhibit-2 (below) illustrates the evidence from Exhibit-1 in numerical form while providing additional detail: Performance data for the UBS family of pension fund aggregates and the Credit Suisse Pension Fund Index. The table uses original index values, as published by Credit Suisse and UBS. Please note that the two index groups have different base values: CSPF Index = 100 at 31.12.1999, UBS Indices family = 100 at 31.12.2005.

Exhibit-02
Exhibit-03

Exhibit-3 (above) illustrates performance by calendar year since  2011 together with YTD performance for the Pension Fund Composite Index. The graph reveals a pattern: Pension funds tend to outperform bear markets, while underperforming bull markets.

The simplified interpretation of this pattern (which is echoed by the data of most individual pension funds) is that of a continuously ‚underinvested’ stance: Either pension funds hold too many cash reserves regardless of outlook, or constantly hedge their market exposure, suffering the drag of additional costs, even when counter-productive. But this hypothesis may not be accurate and the pattern merits more detailed analysis.

Whatever the genuine reason behind the pattern, as markets tend to rise more often than fall, this is likely the tip of an ice-berg pension funds frequently encounter with their investment philosophies.

Exhibit-4 (below) looks at patterns of relative performance across the 20 most recent ad-hoc quarters (three-month periods, not calendar quarters). Shown is the net difference between the PF Composite Index and the benchmark.  Frequency of relative performance together with average excess, or shortfall are also shown in numerical form.

If decisions to differ from the benchmark were to be taken by means of ‚coin-flipping’, one would expect a 50:50 pattern to emerge, with equal values for average positive and negative performances. Clearly, the record is worse than what mere change would suggest. Similar analyses can be shown using monthly and annual data.

The poor success ratio suggests widespread lack of functioning decision making methodologies among pension funds and their service providers.

Exhibit-04
Exhibit-05

Taking a step back and in order to look at a broader canvas, Exhibit 5 (above) shows the benchmark together with aggregate pension fund benchmarks, rebased to 120 months ago. The chart is a stark reminder how the negative pattern described above accrues meaningful value differences as time progresses.

Exhibit-6 (below) emphasises the relative performance of pension fund aggregates to the benchmark.  Of all exhibits shown so far, Exhibit-6 best describes the second meaningful pattern arising from this analysis: Large pension funds appear to have noticeably better performance relative to their smaller peers. While most industry observes will argue that this is explained by a cost advantage that large pension funds have over small ones, I suspect that the reason behind this discrepancy are more complex.

Exhibit-06
Exhibit-07

In Exhibit-7 (above) trailing annualised returns over 36 months is shown, comparing pension fund aggregates with LPP-C40. During the ten years of history covered by this chart, no pension fund aggregate’s trailing return has ever exceeded that of the benchmark, except when the benchmark’s trail was travelling in negative territory.

Matching the approach behind the previous chart, Exhibit-8 (below) depicts ex-post risk, also calculated over trailing 36 months. As much as returns of pension fund aggregates are below the benchmark, as much their risk is also noticeably lower, confirming an observation made in the comments on Exhibit-3. This may indicate success in pension funds’ attempts to avoid risks. However, other aspects of the analysis give an altogether different angle of interpretation.

Exhibit-08
Exhibit-09

In Exhibit-9 (above), the values for trailing risk have been deducted from the values for trailing returns, showing the net result, or the risk-adjusted rate of return. In interpretation of this metric, historic comparisons and cross-comparisons of different investments, or portfolios, at identical points in time matter most. Between any two otherwise identical, or similar rates of return, the one achieved with less risk is of higher worth.

By and large, risk-adjusted returns in the recent past have been quite decent.

A numerical approach was taken in Exhibit-10 (below) to emphasise the data from the previous chart. In addition to delineating the adjusted rate of return, Exhibit-10 shows supplemental statistics to give a more comprehensive profile of risk and return. Attention is drawn to ‚Horizontal Distortion’ which indicates by how much monthly values differ from ‚normal distribution’. Large distortions (highlighted when exceeding 10%) render the concept of ‚volatility’ obsolete, a very popular metric, which is wrongly used as a measure of risk.

Exhibit-10
Exhibit-11

Considering that pension funds are under a legal obligation to seek minimal risks in their investment strategies, it is more than odd, that they have collectively opted to invest extremely close to their/a performance benchmark, or even to outright clone it. This philosophy is entirely incompatible with risk management. The degree to which this hazardous pseudo-strategy is being implemented is revealed by measures of congruency.  R-squared is the statistical measure of dependence from an independent variable, here LPP-C40.  Exhibit-11 (above) shows scatters of the most recent 120 months of paired returns for the Credit Suisse and one UBS Pension Fund Index. Both show an extremely high degree of dependence to LPP-C40, with the UBS Index being slightly higher than the Credit Suisse Index.

Put differently: the negative performance differentials illustrated in previous exhibits are generated with merely 3% of ‘discretion’ exercised in deviating from the benchmark. The cumulative performance differentials of both aggregates to the benchmark are negative That suggests that whatever genuine investment decisions are being taken, they have a very diluting impact on performance, since in view of the very high congruence, any ‘active’ residue would be peripheral in nature. At this point readers are reminded of the comments made on pension funds seeming lower risk. It is conceivable that the true cause of seemingly lower risk readings is that pensions funds raise cash after having suffered losses After all, over the long run, the lower risk benchmark index has meaningfully outperformed the higher risk benchmark index. For details of benchmark performance, click here.

Exhibit-12 (below) shows the intercept (Alpha) and slope (Beta) of the regression line, and the degree of dependence (R-Squared) of all pension fund aggregates from LPP-C40. While all but small pension funds are able to generate a mildly positive ‘alpha’, the corresponding sensitivity to moves in the benchmark (Beta) are so low, that the cumulative differences in performance remain negative.

Put differently, pension funds either take fewer risk than is advisable, and/or they invest too frequently in ‘expensive’ risk, reaching insufficient reward in return. The root cause for this may be found in poor timing of tactical asset allocation decisions, or be the result of poor selection within asset classes.

Exhibit-12
Exhibit-13

Exhibit-13 (above) shows the failure of Swiss pension funds to create value from selective investing with near brutal clarity.

The upper portion lists, across a variety of time horizons ‚success ratios’, the frequency of performance better than LPP-C40.  Readings below 50% (equal to coin-flipping) are shown in red, those above 50% in green.

The lower section shows cumulative performance differentials for the same periods as above. The same colours are used to highlight results. Green (depicting positive performance differentials) is not seen in that part fo the table.

Conclusion

Benchmark indices (such as LPP-C40) are a very crude and rather simplistic reference to describe developments in a given investment environment. Nothing more, nothing less. Such benchmarks are meant as a representation of possible choices but they are not reflective of investment selection of any kind. Thus, benchmarks are free from value creation.

Matching benchmark performance requires no genuine investment expertise. They are fairly easily replicated, requiring no more than basic skills in arithmetics, and statistical methods.

Yet, Swiss pension funds, as represented by the various aggregate indices used in this analysis collectively fail to match, much less exceed such a value-free measure. While obviously painful for all involved, this must be taken as evidence for structural and systemic deficiencies.

Considering the enormous organisational efforts and running costs involved in the alleged selection, and supervision of professional expertise for the management of the nation’s retirement capital, the data presented above is deeply concerning.

Data Sources

Raw data underlying all calculations and illustrations was sourced from:

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