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Why should planning precede asset allocation choices and manager selection when advisors construct a client’s portfolio?

Landmark studies have shown asset allocation to be the single largest contributor to the overall performance of a portfolio. More meaningful than security selection or market timing, allocation has the potential to affect a client’s net worth in the most significant way.

By choosing a variety of asset classes, and managers who perform differently from one another, the investor can limit volatility and create more stable returns over the long term.

That’s all very well. But it begs the question: If asset allocation and manager selection are so critical, why does planning come first when we develop a client’s portfolio?

Our fiduciary approach to assisting clients begins with a highly focused and customized financial-planning process. Through this approach, we gather the requisite client background data to make recommendations that address this individual’s financial goals and aspirations.

Our objectives as a planning-based firm are:

  1. Build a road map based on clients’ current circumstances and future aspirations.
  2. Assist clients in attaining their goals with the least amount of risk.

We see the data-gathering process as fundamental to developing a financial blueprint. The more information we have about clients, the more likely we can deliver a strategy that fulfills their needs.

And so we gather tax returns, brokerage and bank statements, will and trust information, insurance policies and real estate holdings, among other items. We then build a client-balance sheet detailing assets, liabilities andnet worth.

Next, we review clients’ income and expenses to determine if their lifestyle needs are adequately addressed for the future. We model out to the 80th percentile of mortality rates to address the potential for clients outliving their wealth. Finally, we seek to understand clients’ level of risk tolerance and expectations for Coastal Bridge Advisors.

Once we determine the ideal blend of assets, we turn to a universe of managers and investment vehicles to complete the client portfolio.

This information allows us to determine the required growth and income necessary to execute our strategy. The plan is derived from probabilistic analysis, inclusive of variables and contingencies that may influence a client’s success. By undertaking the planning effort first, we can select a long-term asset mix that is designed to deliver the required results, as opposed to one based on emotion or investments currently in favor.

Our next step is to stress-test different asset allocation models. Here, we utilize a Monte Carlo simulation model. What makes Monte Carlo critical to our process is that it draws from a random and dynamic range of historical returns for the various asset classes and weightings for a prescribed asset allocation.

We then run a sample size of a thousand iterations to yield a probability of success for that allocation, given established cash-flow assumptions. This sample size emphasizes the range of likely returns, rather than the volatility of returns in any given year of the planning horizon.

For an individual, we run multiple asset-allocation prototypes before selecting the one that yields the highest probability of success in meeting the client’s long-term goals, while taking the least amount of risk as measured by standard deviation.

In our view, probabilities in the 80 percent to 90 percent range generally offer the right balance of risk and expense. By regularly reviewing the plan, we can rebalance as necessary in pursuit of the desired outcome.

While asset allocation is the foundation for a portfolio’s performance, it also reflects the liquidity needs, tax efficiency and investment horizon of the individual.

Once we determine the ideal blend of assets, we turn to a universe of managers and investment vehicles to complete the client portfolio. We select managers based upon various criteria, including fees, investment returns, tax implications and experience and investment philosophy.

With the forward-looking component of the Monte Carlo stress test completed and the underlying investments and managers selected, we turn to analytical analysis based on historical performance. By looking at the actual portfolio in a historical context, we can see how the recommended allocation would have performed in various market cycles and interest-rate environments.

By arriving at what we believe is an ideal portfolio following careful testing, we can determine how much risk a client needs to undertake to accomplish his or her goals.

By regularly revisiting the plan to update the client’s asset base, cash-flow assumptions and objectives, we can fine-tune the allocations and investments in light of changing circumstances and help deliver financial well-being.

Investing and the Economy

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