Compounding The Problem

Figure 3 illustrates an example of the compounding effect of the allocation misfit along with gaps in market coverage. Using the benchmarks from Figure 1 and the subasset allocation decisions from Figure 2, the result of these decisions (i.e., ignoring ~500 mid-caps and 1,665 micro-caps) is, after one year, approximately 104 basis points in benchmark misfit. Stated differently, the decision to deviate from the actual market coverage of the asset class benchmark has, in this case, “cost” the investor 104 basis points. Note that the decision is on the part of the investor, who has responsibility for assigning the individual benchmarks and weights. The misfit excludes any “alpha” which, whether positive or negative, is generated by the aggregate decisions made by the managers. This distinction is critical.

Achieving A Zero Misfit Portfolio

Figure 4 illustrates a comprehensive asset class benchmark. The subasset class benchmarks and weights are specified in advance and properly aligned with it.

Under this scenario, investment performance can be directly attributed to each mandate decision without any benchmark misfit. Any mandate that deviates from this baseline opportunity set will then not allow an investor to properly measure the impact of their own decisions on their own portfolio for a given asset class. The benchmark misfit analysis must precede—and remain separate from—the active versus passive decision as well as the decisions on the part of their selected managers in attempting to generate alpha.

The Cost Of Inappropriate Benchmarking

Benchmark misfit is an investment decision that leads to uncompensated risk. Prudent investors do not take uncompensated risks because they do not receive additional return for doing so. Therefore, benchmark misfit needs to be properly measured and monitored.

Using an inappropriate benchmark can result in misleading information being provided to all parties involved in the investment process. If a manager is outperforming the assigned benchmark, which is not an appropriate benchmark, an investor may believe the manager is successful, when in fact they may be under-performing by a material amount. In such cases, an investor may be paying for less-than-expected performance. The investor has spent more and received less while being led to believe by the benchmark misfit that the manager is doing well.

This can also occur in more-subjective benchmark assignments, especially when managers are ranked relative to a peer group. Unfortunately, peer group analysis falls short of being a good benchmark because the average is neither investable nor specified in advance. Further, the peers may actually be a poor proxy for the asset class or subasset class. Finally, the practical implementation of gathering peer group data of sufficient scale and relevance is quite complicated and often incorporates significant biases.

From One To Many

In practice, investors hold more than just equities or any single asset class in their portfolios. They more typically assemble a portfolio with a number of diversifying asset classes (even if just two). However, benchmarking such multi-asset class portfolios is not a straightforward exercise since it is not simply an extension of the single asset class approach. Although the decision to use a given benchmark in both single and multi-asset class portfolios may be driven by similar purposes and mechanics, the process for establishing a multi-asset class benchmark is fundamentally different than that for a single asset class benchmark.

Many single asset classes have a known universe of securities or investment options that constitute “the market” and can be used to establish a nearly definitive single asset class benchmark. Other single asset classes, such as commodities, do not have such a defined market, so reasonable proxies are established and marketed with one or two emerging as the standard.

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