There have been a number of articles written recently which speculate that while ETFs will continue to grow as a group, there is a looming offering that is bound to disrupt the ETF industry.
That monster hiding under the bed? It’s advisors using technology platforms to build their own custom direct indexing solutions.
While current thought leadership on this topic is going in the right direction, it is on the wrong path1. Direct indexing is only half the story.
Finding a Solution for the Problem of Mass Customization
The media is missing that this is not solely a “Direct Indexing” story; it is a story about the ability to create custom SMA portfolios in an efficient and scalable way. Put another way, the story is in finding a solution for the “Mass Customization” problem that everyone is striving to solve.
While custom direct indexing strategies will take assets from some ETFs, in order to provide the “Mass” in Mass Customization ETFs will continue to play a necessary role in some portfolios. Without ETFs, there is not an efficient way to gain certain exposures in a pure SMA wrapper for accounts below specific thresholds.
The good news is that advisors do not need to wait for technology to catch up to the promise; there are solutions in the marketplace today that can accomplish mass customization at various levels of sophistication. In fact, Orion has developed the ASTRO platform specifically to address this problem2.
Setting up a custom SMA portfolio in ASTRO involves four basic steps:
- Define your set of target exposures
- Set your broad constraints
- Input Client-specific considerations
- Select your security universe
Once these four steps have been completed by an advisor, ASTRO completes the rest of the portfolio construction.
The platform will construct a portfolio with the goal of minimizing the tracking against target exposure(s) while meeting all of the constraints and considerations that have been set within the system.
Advisors do not have to worry about equivalences for security restrictions or for the purpose of tax loss harvesting, because ASTRO handles all of it.
How ASTRO Constructs Custom SMA Portfolios
Let’s review an example of how the four steps previously identified would work in action.
- Define Your Set of Target Exposures
Broad Domestic exposure that captures Large-, Mid- and Small-cap securities. - Set Your Broad Constraints
Target a 2% tracking error with a maximum security weight of 5% and own a maximum of 200 securities. - Input Client-Specific Considerations
Client A works at Microsoft and doesn’t want to own Microsoft (MSFT). Client B works at Deloitte and is not allowed to own a list of 200 securities. Client C doesn’t want to own any company that deals with Tobacco or Alcohol. All three clients expect to pay 37% Short-Term Tax rate and 20% Long-Term Tax Rate. - Select Your Security Universe
Assign a broad list of US Equities to the model, alternatively a suite of ETFs could be used instead. You can even get creative by using individual equities and a curated suite of ETFs.
Once all of the information is entered into ASTRO, you can construct portfolios for all three clients at the same without individually and manually addressing each of their specific considerations3 .
ASTRO not only handles all of each client’s security-related constraints, but it also does it all in a tax-efficient manner. All the details around security selection, capital gains restrictions, and portfolio construction are handled without any further advisor intervention4 .
While “Direct Indexing” is part of this story, it is much more than a single use case.
There now exists a platform that allows firms to create custom solutions to meet their clients’ varied demands in an efficient and scalable manner.
Ready to see what ASTRO can do for your clients? Click here to attend a webinar and see how you can customize portfolios at scale.
1 An issue of mine is the lack of a common definition for “Direct Indexing”. A number of firms say they provide Direct Indexing while their offerings differ significantly.
2 Yes, I may be partially biased since I lead this effort here at Orion. While I tend to think ours is the best, there are other platforms that can do similar things.
3 Technically, ASTRO is leveraging a sophisticated optimization engine to independently optimize each account.
4 It’s important to remember that there is a tradeoff between the number and level of restrictions and the expected tracking error.
0262-OAS-3/25/2019
Leveraging ASTRO to Better Transition Clients to Your Target StrategyIntroduction to Transition Management
While you may recognize the term ‘Transition Management’ in succession planning, it is also known as a strategy to optimize portfolios. Specifically, in the RIA world, transition management refers to the transitioning of a client’s portfolio from the current allocation to an allocation that the advisor believes is more suitable.
Most institutional custodians offer transition management services for their large institutional client base. Typically, an asset owner fires an outside manager and looks for a service to transition that part of the portfolio to the new manager’s positions in the most effective way.
Transition management, however, is not unique to the institutional space. In fact, this service is probably more desirable in the RIA channel, as incorrectly transitioning a portfolio likely has a larger effect on a client than a large asset owner. Since there are more variables to consider when working with clients—such as taxes, exposures, and costs—generally more is at stake.
The truth is, financial professionals have historically lacked advanced tools to accomplish transition management in a scalable, cost-effective manner. Most firms do this in a very manual process—using a combination of trade restrictions, spreadsheets, and one-off notes. Many RIAs transition clients over four quarters in order to spread out the capital gains hit over two tax years. With this strategy, these advisors sell 25 percent of the portfolio and invest the proceeds into a model allocation each quarter. While this allows firms to scale the process to an extent, the strategy ultimately treats all clients the same, ignoring their current allocations and tax sensitivities.
Transition Management: ASTRO in Motion
Orion’s ASTRO empowers advisors to implement transition management—while optimizing for risk factors, tax considerations, and more. At its core, ASTRO is a portfolio optimizer that uses a risk model to decompose portfolios into a series of factor exposures. One of the unique attributes of ASTRO is that it allows advisors to enter unique client-specific constraints that persist throughout the life of the account until they change it.
For example, a new client has an existing portfolio of 200 individual stocks, two of which have very low-cost basis. The client is overweight in the technology sector and does not have any exposure to fixed income. Additionally, the client does not want to realize more than $50,000 in capital gains this year and $100,000 in capital gains next year.
After reviewing the client’s comprehensive plan—including goals tied to risk tolerance—you’ve determined the client should be in a more moderate diversified strategy consisting of domestic and international equity exposure, along with a 40% allocation to fixed income. The model that fits this description contains a suite of ETFs.
Through the optimization process, ASTRO deconstructs both the client’s current holdings and the ETF model portfolio into a series of factor exposures. Next, it calculates each security’s unique risk contribution relative to your model portfolio. Essentially, ASTRO determines which trades have the highest impact in order to move the client closer to your model. Given the example, ASTRO would most likely recommend selling positions in the technology sector and add positions in the Fixed Income ETFs.
As part of this contribution calculation, ASTRO takes into account whether the securities have unrealized gains or losses. It favors selling losses first in order to harvest those losses. ASTRO iterates over suggested trades until it hits the client’s capital gain budget—which can be inputted into the system and broken out by quarterly capital gains realization targets (e.g. realize 40% of annual capital gains budget in Q1). You can then reoptimize the client next quarter when the capital gains budget increases—or when there is an opportunity to harvest more losses in order to offset gains while staying within the client’s budget.
Conclusion
While the above example paints a clear picture of how to optimize a single account, ASTRO really thrives in batch client optimization. Once you set your clients’ unique constraints—like legacy ‘do not trade’ positions, tax brackets, and security-specific allocation percentages—ASTRO enables you to batch multiple clients together and optimize that group in a single workflow.
To learn more about how ASTRO can help you better transition clients to your target strategy, sign up for one of our upcoming ASTRO demos.
0081-OAS-1/31/2019
Replacing the Difficulty of Stock Picking: An Ode to Direct IndexingThe financial world is buzzing with stories on how stock picking has become increasingly more difficult. Whether this challenge is the result of broad market cycles, the growth of ETFs, or the addition of more quant-based strategies, stock selection continues to have massive implications for investors’ financial health.
But what if you could offer a tax-managed stock strategy to your clients without having to worry about stock selection? In 2018, Orion created ASTRO, a portfolio optimization and risk modeling tool, to give advisors an opportunity to do just that.
ASTRO sees the world differently than most tools. Instead of viewing a portfolio as a collection of securities, it views it as a collection of risk factors. This subtle but powerful difference enables advisors to build stock-based SMA strategies for their clients. Let’s see how.
Direct Indexing: ASTRO in Motion
You may be familiar with the term ‘direct indexing,’ or replicating the performance of an index by purchasing the underlying shares. Let’s assume that you’d like to replicate the risk and return profile of the S&P 500; however, instead of owning all 504 securities, you want to replicate the index with only 100 securities.
First, ASTRO will decompose the S&P 500 into a series of factor exposures based on the underlying securities. Some examples of these factors include Beta, Market Capitalization, EPS growth rates, and Relative Strength1.
Then, ASTRO will look at the factor exposures of the securities currently held within the client’s portfolio—taking into account any unrealized gains or losses associated with each position. The optimization engine will build a portfolio of stocks from the S&P 500 and the client’s account to replicate (as close as possible) the factor exposure of the S&P 500—given the constraint that it can only use 100 securities. ASTRO will tell you how close it expects the portfolio to track the S&P 500 by providing you with Tracking Error and R-Squared2 statistics.
Let’s take the above example one step further. Now, you’d like to replicate your favorite mutual fund manager’s strategy—allowing your client to hold individual securities while accounting for tax sensitivity and a similar risk/return profile as that fund. ASTRO will decompose the fund’s factor exposures and then build a portfolio of individual equities that gives the client a similar factor exposure as that fund.
Conclusion
Historically, stock-based SMA strategies have only been available to large institutional firms—and at an expensive price point. With ASTRO, RIAs can cost-effectively enhance their client offerings with direct indexing—without having to sweat over stock selection.
To learn more about how ASTRO can help you implement direct indexing strategies for your clients, sign up for one of our upcoming ASTRO demos.
- For a complete list of actual factors, please reach out to the ASTRO team astro@orionadvisor.com
- Tracking Error indicates how closely a portfolio follows the index to which it is benchmarked. For example, a tracking error of 1% means that a portfolio’s return should be within 1% of the index’s return 2 out of 3 years. R-Squared measures how closely each change in price of the portfolio is correlated to the index. An R-Squared of 1 means they are perfectly correlated.
0078-OAS-1/30/2019