Common beliefs in the wealth management industry that are untrue — and potentially harmful.
We know something you (might not) know. There are three common beliefs — conventional wisdom even — in wealth management that are not true. It’s not so much that they’re just made up. It’s more that they’re out of date — cases where technological innovations have rendered conventional wisdom obsolete. What are these myths from the past? Here’s our list:
Myth 1: Models-based wealth management results in cookie cutter solutions, and the same is true for centralized rebalancing.
“Models-based wealth management” means that client portfolios follow one of a limited set of model portfolios. You might have a Conservative Model Portfolio, an Aggressive Growth Model Portfolio, etc. You might create variants for taxable and non-taxable clients, low net worth and high net worth clients, etc. A model portfolio can be as simple as, say, five ETFs, or it can have a complex multi-tiered asset allocation, with combinations of individual equities (typically for US large-cap), mutual funds and ETFs (typically for peripheral asset classes).
Common wisdom has it that models-based wealth management is great for efficiency, consistency and compliance, but, almost by definition, means every portfolio in the same category (e.g. “high net worth, taxable conservative”) is managed the same. And if you really want customization, you need to create a new model for each account, which undoes all the efficiency, consistency and compliance gains that models were created for in the first place. So adopting “models-based” portfolio management comes at the cost of sacrificing customization and tax management. Great for small accounts, but unsuitable for large, customized accounts. The alternative to models-based portfolios is a traditional “one trade at a time” approach where you start with a buy list and some diversification guidelines but make each trade decision individually based on market beliefs, client preferences, tax considerations, security rankings, etc.
Very similar logic holds for centralized rebalancing. (“Centralized rebalancing” meaning portfolios are rebalanced by a small, dedicated trading group within a firm, not by client-facing advisors). Sure, common wisdom would have it, like a models-based approach, centralized rebalancing is great for efficiency and consistency, but it can’t support high levels of customization and tax management, attributes that are required to serve wealthier clients.
Reality: Done well, models-based, especially models-based centralized rebalancing means more, not less, customization and tax optimization.
How is this possible? The key idea is that with models-based approaches, customization and tax management can be automated, which makes customization and tax management incrementally free to implement. And when you make something free, folks consume more of it. (See The Art of Centralized Rebalancing and Choose Your Words Carefully).
With a models-based approach, customization is not implemented as an on-the-fly adjustment to the default trades. Instead, you store customization and tax management preferences for each account — “parameter-based customization.” These preferences are then automatically incorporated into the rebalancing system’s recommendations. Common customization/tax management preference options include:
- ESG/SRI screens
- Security and sector constraints
- Custom asset allocation requests (e.g “no Real Estate exposure”, “overweight small cap”)
- Custom investment vehicle selection (e.g. “I want a direct index for US large cap, an ETF for everything else”)
- Tax-sensitive transition
- Year-round loss harvesting
- Capital gains avoidance
Using data from our own clients, we can measure the improvement in customization and tax management that you get with models-based approaches (we would expect results from other automated customization systems to be similar). The average dispersion goes down by about 60%, which is what you’d expect from a models-based system, but the average client capital-gains tax bill also goes down by 60%. And the percentage of accounts with social screens and other constraints jumps by similar amounts.
Myth 2: Tax loss harvesting is the core of tax management.
Tax loss harvesting means selling securities that, but for tax considerations (realizing a capital loss), you’d otherwise hold onto. For many, tax loss harvesting isn’t just the core of tax management, it *is* tax management. There are debates about how valuable tax loss harvesting is (see Why Tax Loss Harvesting Really Matters), but rarely does anyone question its central role.
Reality: Gains deferral, not loss harvesting, is the core of tax management.
Gains deferral means holding onto a position that, but for tax considerations (not realizing a capital gain), you’d otherwise sell. In and of itself, gains deferral is easy — just don’t sell appreciated positions, but this simple approach would create excessive risk and drift. The hard part of gains deferral is balancing tax and risk consideration, mitigating excess risk as much as possible by carefully counterbalancing overweighted positions. For example, if you’re holding onto extra shares of IBM with low basis, you might be able to counterbalance this by underweighting correlated securities, say HP. That way you keep the overall characteristics of the portfolios — beta, P/E, average capitalization, sector exposure, industry exposure, etc — roughly constant.
Loss harvesting is important, but the data is overwhelming: in the long run, gains deferral is a much greater source of value. Based on an analysis of portfolios managed on our system, more than ¾ of the value comes from gains deferral, not loss harvesting (See Gains Deferral: The Core of Tax Management)
Why does tax loss harvesting get all the attention? We’re not sure, but we think it’s simply because, until recently, gains deferral was too difficult for most firms to do systematically and well.
Myth 3: Though they may differ in exact features, rebalancing systems are pretty similar.
Folks don’t necessarily believe that all rebalancing systems are the same — they suppose that some are better than others — but they do believe that they’re all trying to do the same thing, which is to, well, rebalance portfolios.
Reality: Rebalancing systems differ in their fundamental objectives.
It’s not that some rebalancing systems are good and others bad (though that may be so). Rather, they’re built to do different things. There are really four types of systems. The key distinctions are sleeves vs. sleeveless and advisor-assist vs. automated.
Sleeves vs. Sleeveless
Sleeves are virtual subaccounts (sometimes called partitions) of a main account. Like a real account, sleeves can be traded independently of each other and you can report the return performance of each individual sleeve. Sleeve-based systems create and maintain these virtual subaccounts. Typically, users will create one sleeve per model (for models-based systems) or one sleeve per manager (when discretion over an account is distributed).
Sleeveless systems bypass sleeves and look at entire portfolios holistically. This holistic approach is more efficient and results in both lower overall dispersion and greater tax efficiency. However, you give up access to sleeve-level performance reports. (See The Case Against Sleeves and Q&A: The Case Against Sleeves.)
Advisor Assist vs. Automated
Advisor assist systems are designed to make advisors either more efficient or more effective at rebalancing portfolios. With advisor assist systems, workflows are centered on “alerts” that notify advisors of problems that need to be addressed.
In contrast, automated systems are, at heart, designed to entirely free client-facing advisors of the need to rebalance portfolios, delegating this task to a central rebalancing group. Automated systems also have alerts but, critically, the alerts are always accompanied by solutions — specific, customized, compliant trades for each account that set things right. (See An Inside Look at Automated Rebalancing)
Why the exercise in “myth-busting”? Well, partly because it’s fun, but mostly because myths can be pernicious, causing firms to build around imaginary barriers (or, more precisely, previously existing barriers), making wholly unnecessary compromises between, say, efficiency and customization. And that’s a shame. It shortchanges both wealth management firms and their clients. That is to say, myths can be dangerous.