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Multi-Goal Rebalancing: The Best Way to Efficiently Manage Complex Client Portfolios

For many wealth management firms, their portfolio rebalancing software is one of the most critical pieces of technology that they have. While other applications are certainly important – from CRM for managing client relationships, to eSignature for streamlining account opening and eliminating paperwork, to financial planning software that helps guide your clients’ long-term financial plans – arguably no other component has a bigger impact on your clients’ portfolios than rebalancing software. Yet, amongst a sea of vendors offering different sets of features and functionality, almost every rebalancer on the market is hamstrung by one common limitation – they can only review each portfolio a single time during each rebalancing session.

Why is this a limitation?  What is the benefit of reviewing a portfolio more than once?

To answer these questions, we have to understand the differences between single-pass and multi-pass rebalancers.

Single-pass rebalancers are algebraic by nature and their processing is designed to achieve the single goal of aligning a portfolio’s asset allocation to a target model.  Each position in the portfolio is examined once, compared to the model and, if necessary, an order is generated to bring it back to target.

A multi-goal rebalancer is a different animal entirely because it is based on a very different but well-established optimization algorithm.  It reviews each portfolio thousands of times and then selects the solution that is optimized for the chosen client’s goals.

This is a critical distinction between the two systems!

Many clients have multiple goals such as minimizing taxes, reducing portfolio turnover, allocating securities across sleeves or maintaining the current levels of risk. The only way to determine the optimal balance between all of these competing directives is to iterate through the portfolio thousands of times, slightly adjusting each parameter and noting the changes. The system can then choose the most optimized outcome and present it to the advisor.  This is known as pair-wise swapping. This method guarantees to return an optimal portfolio while maintaining multiple mutually-dependent goals.

Going Under the Hood

Pair-wise swapping is an iterative technique that involves reviewing a portfolio anywhere from 100 to 10,000 times, comparing all of the different goals, and adjusting the portfolio until it finds the most optimal solution. Since more than one goal must be achieved, it is necessary for the portfolio to go through multiple “passes” until the best possible solution is discovered by the algorithm.

Pair-wise swapping is also known as “infinitesimal trading” since many very small trades are generated to see how the portfolio is behaving. Following this, the tiny trades are summed up and the actual trades for achieving the portfolio’s multiple goals are suggested by the algorithm.

Some people have confused pair-wise swapping with Monte Carlo simulation, but while these two techniques are both iterative, they are quite different in their output. Monte Carlo simulations assign a probability to each solution and then provides an aggregate of those probabilities.  Pair-wise swapping does not estimate or extrapolate any data, it uses massive iteration in its optimization function.

A portfolio rebalancing engine must be built from the ground up to support multi-goal rebalancing in order for it to operate correctly.  It is not a simple extension feature that a vendor can slap onto their system any time they like.  The software must be designed very carefully to take advantage of the optimization process.  So, beware of any vendor that claims they will be adding pair-wise swapping techniques to their single-pass rebalancer at a later date.

The Advantages

Single-pass, algebraic rebalancers are locked into the target weights of the underlying security positions. A multi-goal rebalancer can be given the flexibility to modify the target weights of any of the securities in the portfolio. This provides it with the immense power to deliver on simultaneous client requirements with fewer compromises in any areas.

For example, if the advisor is trying to minimize trading costs and portfolio turnover, it would be useful to avoid having to calculate a target weight for every position in each asset class. The advisor could assign a large cap sleeve to be 40% of the portfolio and the rebalancer could be given freedom to adjust the weights of the underlying positions to best meet all of the investment goals, while still maintaining 40% large cap exposure.

This would provide numerous advantages for portfolio managers and financial advisors operating as Advisor as Portfolio Manager (APM), since the models do not have to be manually updated.

When you run a single-pass rebalancer, it will return a single answer, which is not always the best one, especially for complex portfolios, with many holdings, multiple sleeves, location preferences and tax issues.  It cannot iterate through the portfolio and generate many different results and then pick the one that satisfies the maximum number of client constraints.

Best Practices

A portfolio should have a minimum value of $250,000 and have a model assigned with at least 12-15 securities for a multi-goal rebalancer to function in the most efficient manner.  These minimums ensure that the rebalancer has room to operate and deliver the greatest benefits.

For smaller portfolios, there may not be a noticeable difference in outcomes when compared to a single-goal rebalancer, since the system is essentially cloning the model onto the portfolio rather than optimizing.

Time to Move on from your Single-Pass Rebalancer

Advisors who utilize a multi-goal rebalancer will see a reduction in the amount of manual work that must be done to support complex portfolios and households.  This is due to the system’s optimizing capabilities that enable it to handle numerous conflicting client goals with subtle adjustments that find the optimal solution.

Multi-goal rebalancers present a tremendous opportunity to provide clients with improved results without having to worry about the size, complexity, or constraints of their portfolio. They are also far easier to manage, enabling advisors to increase scale and manage more assets without worrying about details falling through the cracks.

If you are looking for a multi-goal rebalancing solution that can optimize complex portfolios, reach out to our team at SoftPak for more information.

About SoftPak Financial Systems

One the earliest players in FinTech, SoftPak has developed innovative products at the intersection of business solutions and IT infrastructure since 1994. Our rule-based rebalancing and risk-based optimization software powers some of the largest financial institutions in the world, processing over 500B AUM. Headquartered in Massachusetts, SoftPak has offices worldwide.

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