Manage Money Like a Pro: Decisions That Drive Investment Portfolio Performance
Word count: ~1,450
Time to read: ~7 minutes
Introduction
When I reviewed the Brinson, Hood and Beebower’s research, I found something that fundamentally shapes how I manage client money: the core investment policy of a portfolio explains roughly 90 percent or more of its long term return variability, while traditional active management decisions like stock picking and market timing contribute little and often subtract value instead.
Why it matters: Most investors spend time on the 10 percent that matters least and neglect the 90 percent that matters most.
The study examined 91 pension plans over a decade and decomposed returns into four components: the benchmark policy return, the effect of market timing, the effect of security selection, and the total actual portfolio return. What jumped out at me was how clearly the numbers showed it: the benchmark policy portfolio, defined simply by asset class weights across stocks, bonds, cash, and other assets, explained 93.6 percent of the variability in returns, while the active decisions collectively reduced performance by about 1.1 percentage points versus the benchmark.
This research shifted how I think about my work with clients. Instead of asking "What will outperform next year?" I focus on "What long term mix of assets is appropriate for your goals, risk profile, and time horizon?" It reframed the value I provide, moving away from chasing winners and toward designing and maintaining a durable investment policy.
The Four Decisions Every Investor Makes
The paper's implications section breaks down portfolio design into four steps that I use with every client: deciding which asset classes to include, choosing long term target weights for those asset classes, tactically shifting those weights to time markets, and selecting individual securities within each asset class. The first two are investment policy, the last two are investment strategy.
Why it matters: You cannot avoid these decisions; you only choose whether to make them explicitly and thoughtfully or by accident.
For most clients, "what asset classes to include" usually translates to a mix of domestic stocks, international stocks, investment grade bonds, cash, and possibly real estate or other diversifiers. The second decision, normal long term weights, defines the strategic allocation: for example, a 70 percent stock and 30 percent bond portfolio for a growth oriented investor, or a 40 percent stock and 60 percent bond portfolio for someone closer to retirement.
The third and fourth decisions, timing and security selection, are what occupy most investing news and a lot of advisory marketing. When I looked at the data, it showed me that these activities did not just fail to help on average; they actually reduced returns compared with sticking to the policy benchmark, after accounting for the full period results.
What This Means for Different Types of Investors
Although Brinson examined institutional pension plans, I have found that the mechanics of risk and return apply across investor types, from DIY investors to retirees to business owners. My job is to translate the four steps into practical policy choices that reflect real world constraints, tax situations, and cash flow needs.
For young accumulators with long horizons, it can mean spending more time defining an equity heavy, low cost, broadly diversified policy portfolio and much less time trying to find the next hot sector or trading in and out of the market.
For pre retirees and retirees, the emphasis shifts to calibrating stock, bond, and cash allocations so that volatility, standard deviation of returns, and withdrawal needs can coexist without forcing desperate selling after market declines.
For small business owners or self employed professionals, investment policy has to integrate business risk as an implicit asset class. I often work with entrepreneurs whose income and net worth are already tied to a single private business, and they may need a more conservative financial portfolio, with lower equity exposure, than their age alone would suggest.
Risk, Volatility, and Staying Invested
When I reviewed the dataset, I paid close attention to not just average returns but also minimum, maximum, and standard deviation of returns for each asset class and for the policy portfolios built from them. What I emphasize with clients is that standard deviation is a statistical measure of volatility across time and is central to risk adjusting returns in investment management.
Why it matters: Policy is not just about expected return; it is about choosing a level of volatility you can live with through full market cycles.
In practice, higher equity weights increase both average returns and the range between worst and best outcomes, while larger bond and cash allocations narrow that range but lower long run return expectations. For investors drawing income from their portfolios, this volatility interacts with withdrawal patterns to create sequence of returns risk, where poor early returns can damage sustainability even if long term averages look acceptable.
Why it matters: A good policy portfolio reflects both your mathematical risk capacity and your emotional risk tolerance, so you can stay invested during inevitable drawdowns.
This is exactly why I prepare an investment policy statement with every client I work with. It codifies target allocations, rebalancing rules, tolerances for drift, and the role of cash reserves so that market events trigger pre agreed actions instead of improvised reactions.
Why it matters: Having a clear, written policy in advance replaces panic decisions with disciplined responses when markets move.
How to Build and Implement a Policy Driven Portfolio
I use the this framework as the foundation for how I construct portfolios for clients, and it suggests a concrete order of operations that applies to both institutional and individual investors. I start with defining goals and constraints, then map those to an appropriate mix of asset classes, specify normal long term weights, and only then decide whether and how to incorporate any limited active tilts.
Why it matters: A repeatable process translates abstract research into daily portfolio decisions.
First, I define objectives in terms of real world outcomes: retirement income, college funding, financial independence, or legacy giving, as well as time horizons for each goal. Alongside that, I document liquidity needs, tax considerations, and any legal or behavioral constraints, such as concentrated holdings that cannot easily be sold.
Second, I choose asset classes that together provide broad exposure and diversification: major equity markets, high quality bonds across maturities, and sufficient cash to meet short term obligations and near term spending. Then, I set normal weights that reflect growth needs and risk capacity, understanding that these weights are the primary driver of outcomes and should change only for structural reasons, like entering retirement or a permanent shift in income stability.
Third, I treat market timing and security selection, if used at all, as minor, constrained decisions within the policy framework. Given the evidence that active timing and selection produced negative active returns in the Brinson sample, any active tilts should be modest, cost aware, and evaluated against the policy benchmark rather than against anecdotes.
Finally, I formalize the entire structure in an investment policy statement that can be shared among decision makers, whether that is a household, a business retirement plan committee, or our advisory relationship. That document defines the benchmarks for each asset class, the standard for measuring results, and the process for reviewing and updating the policy as circumstances change.
