Goal-Based Reporting and Traditional Metrics

A principal preoccupation of traditional performance reporting is calculating a portfolio’s rate of return either in absolute or relative terms, with the emphasis on relative comparisons: measuring returns against some generally accepted benchmark, peer group, or risk-adjusted return.

Consequently, the performance metric for the individual investor is the portfolio’s return relative to an index or median manager’s performance in a similar investment style. A major goal of the investor and designated investment manager is to create alpha or excess return of the portfolio relative to the benchmark, with success defined as beating the benchmark.

Although investors generally focus on portfolio relative returns, the advent of behavioral finance suggests that a larger spectrum of investor behavior should be embraced. Rather than the narrow focus of portfolio allocation based on risk–return calculation, there is the ongoing realization that investors have more experiential, real-world goals than those accommodated by standard risk–return models.

For example, a highly desirable goal for a retired or near-retirement demographic is to have a spending stream or target spend rate that keeps intact the principal of the investment portfolio and that, at the same time, affords a realistic spending stream of income in the retirement years. An important concern of goals-based reporting is avoiding the twin fears of exhausting retirement income prematurely or not leaving a financial legacy to family members.

The standard metric used by traditional performance reporting is incomplete in measuring the attainment of such goals. This is not to say that the retired investor is totally indifferent to their portfolio’s return relative to a benchmark. Rather, a complementary performance metric is required in assessing the achievement of a retiree’s goal.

Goals-based reporting is the missing element in the performance story and represents a true understanding of an investor’s experiential preoccupations, worries and dreams. For that reason, the industry should move to goals-based performance metrics and reporting, which enables investment managers to produce performance reports that reflect the true aspirations of each investor.

Disciplined spending and its associated depletion of accumulated assets in retirement can be a challenge. As James Tobin, a Noble Prize–winning economist, noted in the context of endowment spending, there is a trade-off between current spending and the growth of the endowment’s principal. This trade-off applies to the retiree’s situation as well. By spending in excess of some targeted spend rate, the retiree runs the risk of depleting assets and reducing the intergenerational wealth transfer to family members. Investors must therefore be sensitive to their spending habits and establish an asset structure or asset allocation that permits the realistic possibility of maintaining or growing portfolio value.

The purpose of traditional performance metrics is assessing the growth of the portfolio and the success of the investment manager. Knowing your small-cap manager beat the Russell 2000 by 150 bps is reassuring. In addition, a Sharpe ratio higher than the median manager in a peergroup ranking reduces fears of unacceptable risk for this 150 bps alpha return. All of these traditional metrics serve a very useful and informative purpose. I do not suggest discarding these performance tools. Instead, they are indispensable complements to goals-based performance reporting. But a different metric is required to monitor behavior and ensure that current spending habits do not exceed the pre-defined targeted spend rate.

Consistent with Tobin’s suggestion, an optimal spending rule or targeted spend rate is one that combines stable elements with market elements. Specifically, the stable term is a percentage of the previous year’s spending plus an adjustment for inflation. In addition, the spending rule incorporates a market term for a long-run sustainable rate of distribution multiplied by the market value of the portfolio. By varying the proportions between the two terms, investors can influence how sensitive their spending is to market variation. For example, more risk-tolerant retirees could select a higher proportion for the market term in the spending rule, which would make current spending more sensitive to market fluctuations. Overweighting the market term might be enjoyed during bull markets but could lead to an anxiety-inducing and belt-tightening scenario in bear markets.

Spending requires cash, and a targeted spend rate requires a predefined amount of available cash. Without adequate cash, a steady spending stream as mandated by a spending rule is impossible.

In addition to cash, goals-based reporting can have additional layers or asset classes, such as stable and growth assets differentiated by their liquidity properties and variability of returns. Because cash and cash equivalents have zero or minimal variation, they occupy the foundation of the asset layering. Stable and growth assets are less liquid and experience varying degrees of return variability. Consequently, they account for a smaller proportion in the layering of assets.

The spending rule in general (and the weights associated with the stable and market terms in particular) determine the amount of cash and cash equivalents required for the investor’s targeted spending. The remaining stable and growth assets are determined by a client’s risk exposure. The stable assets would “sit above” the foundational layer of cash and usually account for a large share of portfolio value.

Finally, growth assets would add the top the layer and usually would constitute the minority of the asset mix. Notice that the asset mix is viewed from the perspective of liquidity and the requirements for a stable spending stream as opposed to traditional view of asset allocation (namely risk diversification).

Cash does not fall from the sky but must be raised by selling other assets. Moreover, knowing when to sell assets requires some forethought and rule generation. This raises the challenge of the optimal, market-timing trading rules to refill the cash bucket and to maintain the targeted spending rate. Trading rules are developed to satisfy the various types of markets (i.e., range bound, rising, and falling). For example, it is better to replenish the cash bucket in a bona fide bull market than to sell assets at distressed prices in a raging bear market.

A minimum floor of cash (e.g., three months of cash to satisfy targeted spending) is established and automatically replenished when it falls below the minimum regardless of market conditions. For other amounts of cash, using technical trading indicators (i.e., moving averages, mid- to long-term trend analysis, etc.), sell signals are triggered in order to refill the cash bucket. In turn, the “freed up” cash flows to spending in alignment with the targeted spend rate. Hence, the foundational layer of the asset model (that is, cash) supports the spending habits of retirees and provides a very different depiction of portfolio allocation than typical variance of return model. In a behavioral sense, assets are chosen not necessarily for their expected return relative to their risk but rather as a conduit of cash flow to support distribution and spending behavior.

The spending rule and ensuing spending behavior are sensitive, by varying degrees, to a market term. Statistical methods can be used to estimate the impact of the market term on spending. Monte Carlo simulation is used to produce statistical estimation of various market scenarios and their impact on spending. Specifically, for various parametric values of the stable and market terms within the spending rule, Monte Carlo simulation can estimate the portfolio returns and spending scenarios and can provide a measurement of important life-metric signals, such as the number of years the current spending stream can continue before an investor’s assets are exhausted.

A more immediate and compelling performance metric is the comparison of a historical current spend rate with the theoretical target spend rate. The current spend rate can be a moving average of historical spending or a projected spend rate based on current spending behavior. By developing and including additional rules that affect the functional interplay between the current and target spend rate, it is possible to provide investors with advisory signals when their spending exceeds the target spend rate.

These life signals are not intended to replace the traditional performance metrics of portfolio analysis. Clearly, investors should be concerned about the upper tiers of their asset mix. As noted, the market term of the spending rule can have an important and decisive impact on a spending stream depending on an investor’s risk tolerance. Investors need to know if their portfolio or investment manager achieves excess return relative to some benchmark. Not surprisingly, when investors open a monthly or quarterly investment statement, they appreciate the plethora of traditional performance metrics: alpha, Sharpe ratios, Treynor ratios, time- and money-weighted returns, and attribution analysis. Performance life metrics will experientially resonate with the investor in a different way than the traditional tool set of performance metrics.

An effective way of putting the investor first is to empower them. This means creating goals-based reporting tools that resonate both objectively and subjectively with the investor. In addition, these tools should promote proactive investor behavior. Reviewing a monthly or quarterly investment statement and noticing a “spend-limit violation” —the penalty of which is facing the retirement years with quickly dwindling financial resources—is sufficient reason to reassess one’s spending habits and to initiate a portfolio review with the investment manager.

Such a review should encompass both personal spending behavior as well as noting excess returns relative to benchmarks as a result of the choice of asset buckets or investment manager selection. This approach is a win–win for the investor and investment manager. Combining this client-centric focus with traditional and goals-based performance metrics can truly optimize an investor’s reporting experience.

Charles M. Opincar is a senior reporting analyst at Fiserv in Jersey City, New Jersey.