Of Ghosts in the Machine: The Peril of Relying on a “Bought SunGard Asset Allocation Master”

I have seen many institutional investors, from pension fund managers to family offices, fall prey to the same seductive idea: that complex, expensive technology can provide an edge in crafting the perfect portfolio. The phrase “we bought SunGard” or “we use the Asset Allocation Master” was once a badge of sophistication, a signal that an organization was serious about optimizing its investments. After decades of analyzing investment processes and their outcomes, I have reached a contrary conclusion. The purchase of a sophisticated asset allocation software suite is often a costly mirage. It creates an illusion of precision, fosters a dangerous over-reliance on flawed inputs, and can ultimately lead to worse decisions than a simpler, more robust framework. Buying the tool is easy; acquiring the wisdom to use it correctly is the real challenge, and it is one that most organizations fail.

SunGard (now part of FIS Global) is a leading provider of financial software, and its asset allocation tools are industry standards. They are powerful engines capable of running thousands of Monte Carlo simulations, optimizing portfolios across hundreds of asset classes, and producing beautifully detailed reports filled with efficient frontiers and probability distributions. The problem is not the software itself, but the way it is typically used. Garbage in, gospel out.

The Illusion of Precision and the Garbage-In-Gospel-Out Problem

The most dangerous output of these systems is a false sense of certainty. The software generates numbers like “a 22.7% allocation to emerging market equities is optimal” or “this portfolio has an 87% probability of achieving your return objective.” These precise figures are based on two highly unstable and unpredictable inputs:

1. Expected Returns: The user must input expected returns for every asset class. Where do these numbers come from? Often, they are based on long-term historical averages or analyst forecasts. Historical averages may not be a reliable guide to the future, especially in a changing macroeconomic regime. Analyst forecasts are notoriously inaccurate. A difference of just one percentage point in the expected return for US large-cap stocks can completely reshape the “optimal” allocation the software spits out.
2. Correlation Assumptions: The software requires a correlation matrix—a prediction of how different asset classes will move in relation to each other in the future. This is perhaps the most treacherous input. Correlations are not stable; they are dynamic and can change dramatically, especially during market crises. The software that told you that international bonds were a great diversifier in a 60/40 portfolio may not account for the fact that in a global “risk-off” panic, all risky assets can become highly correlated and fall together.

When you feed these speculative guesses into a hyper-precise engine, it returns what looks like scientific fact. It sanctifies guesswork with the aura of mathematical certainty. An allocation of 22.7% feels more reasoned and defensible than “about a fifth,” but it is no more reliable. It simply gives the investment committee a false comfort that their decisions are data-driven.

The Neglect of the Real World: Taxes, Costs, and Behavior

Sophisticated software often optimizes for a theoretical, pre-tax, frictionless world. It ignores critical real-world constraints that ultimately determine investor success.

• Tax Impact: The software might suggest a significant allocation to high-yielding bonds or REITs. But if this portfolio is held in a taxable account, the resulting income will be taxed at ordinary income rates, severely eroding the net return. The “optimal” pre-tax allocation is suboptimal after taxes. The software rarely models this effectively.
• Fund Costs and Implementation: The model might call for a 10% allocation to frontier markets. But can this be implemented with a low-cost, liquid fund? Or will the investor need to use an expensive active fund or an illiquid separate account? The friction and cost of implementation can wipe out any theoretical advantage the allocation was supposed to provide.
• Behavioral Realism: The most optimized portfolio in the world is useless if the investor cannot stick with it. A software-generated portfolio might be highly efficient on paper but incredibly volatile in practice. Will the human investors panic and sell at the bottom? The software cannot model human emotion, which is the greatest risk of all.

A Simpler, More Robust Framework

I advise clients to use technology as a tool for exploration, not prescription. Instead of seeking one “optimal” output, use the software to run stress tests and see how different allocations might behave under various scenarios. Then, make a decision based on a simpler, more durable framework.

1. Focus on What You Can Control: You cannot control market returns or correlations. You can control your savings rate, your costs, your asset allocation (in broad terms), and your behavior. Direct your energy there.
2. Embrace Broad Allocations: Instead of 22.7%, think in terms of 20% or 25%. Instead of trying to finely slice eight different equity sub-classes, consider a core-satellite approach: a core of a global stock index fund and a global bond index fund, with small, intentional “satellite” allocations to express specific views.
3. Build a Resilient Portfolio: Seek robustness, not optimization. A robust portfolio performs adequately across a wide range of future scenarios. An optimized portfolio performs excellently in one specific predicted future and poorly in all others. Ask: “What allocation can I hold through a bear market?” not “What allocation will give me the highest Sharpe ratio based on the last 20 years of data?”
4. Implement with Low-Cost Vehicles: However you decide to allocate, implement it with the lowest-cost index funds or ETFs available. This is a certainty. It is a guaranteed boost to your net returns that no software optimization can reliably provide.

Buying the SunGard Asset Allocation Master is not a strategy; it is an expense. It can be a useful tool in the hands of wise investors who understand its profound limitations. In the hands of most, it is a crutch that substitutes complex calculation for simple wisdom. The master of your asset allocation should not be a software program; it should be a clear understanding of your goals, your risk tolerance, and the undeniable truths of financial markets: that costs matter, that the future is unpredictable, and that the simplest plan is often the one you can stick with. Do not be impressed by the software a firm has bought. Be impressed by the humility and discipline with which they use it. The most important allocations are not found in a software output; they are the allocation of your time to understanding these principles and the allocation of your capital to low-cost, diversified investments you can hold forever.