Executive Summary
In this Q&A, Kyle Birmingham, CFA, Head of Portfolio Management at Quorus, explains how Quorus builds custom tax overlays for actively managed portfolios. He breaks down our approach to daily, tax lot–level optimization and why active strategies require fundamentally different tax management than passive ones.
Q: Before we dive in, can you introduce yourself and your role at Quorus?
Sure. I’m Kyle Birmingham, the Portfolio Manager at Quorus. My focus is on designing and managing our custom tax overlay strategies, particularly for active investment managers. I work closely with both the asset managers and our internal teams to ensure that the portfolios we implement align with the manager’s strategy and deliver meaningful after-tax value for clients.
Q: Quorus has intentionally focused on actively managed portfolios. Can you quickly discuss why active portfolios require a different approach than passive portfolios?
Absolutely. Passive portfolios, like index-based strategies, are relatively stable and predictable. They follow a predefined set of rules, have lower turnover, and typically hold a broad set of securities. That makes it easier to apply a standard tax management process.
Active portfolios are different. Every manager has a unique philosophy and approach. They select securities based on conviction, and those views can change quickly. Turnover can be less predictable, and the portfolio may be more concentrated. Designing a tax management program that fits the manager's style is critical. You can’t just apply a one-size-fits-all overlay. Instead, you have to tailor it, strategy by strategy, to ensure you're not disrupting what makes the active manager successful in the first place.
This process of fine-tuning an overlay for active strategies is not trivial. We believe that by focusing on working specifically with active managers, we can be the best in the world for our clients.
Q: Diving in then, can you provide an overview of how Quorus approaches portfolio management?
We approach portfolio management through an “inputs and outputs” lens. Our optimization process involves three key inputs: client-specific data, the asset manager's strategy, and market data.
Client-specific data includes tax lots, purchase prices, and any account-level restrictions or preferences, such as ESG filters or held-away assets. The second input is the asset manager's target strategy, including their top investment ideas and how they weight those ideas. Finally, we factor in real-time market data to determine optimal trade execution.
We combine these inputs daily and run them through our optimizer, which evaluates the best possible portfolio for each client that day. Sometimes, that results in trades; sometimes, the optimal move is to hold tight.
Q: What makes running this process daily so valuable?
The biggest benefit of daily optimization is ensuring clients capture as many tax-loss harvesting opportunities as possible. If you only check portfolios monthly or quarterly, you might miss windows where a position dipped into a loss and then rebounded. Daily checks give us the chance to act immediately when those opportunities appear.
It’s also critical to stay aligned with the portfolio manager’s strategy. In active management, a manager can lose conviction in a name and drop it from the model anytime. If you’re not checking portfolios daily, you risk holding a position the manager no longer supports, or missing the chance to exit a name at a loss before it rebounds. That’s not just a missed opportunity for tax alpha, it’s a drift from the intended strategy.
Finally, running this process every day says a lot about our infrastructure. Many firms don’t offer daily optimization because their systems can’t handle it. Our ability to do this at scale, with flexibility across different strategies and client constraints, reflects how purpose-built our tech stack is for this kind of customization.
"If you’re not checking active portfolios daily, you’re missing both tax opportunities and the chance to stay aligned with the manager’s signal."
Q: Using highly granular building blocks to construct portfolios is an important foundation for Quorus. Can you discuss the value this provides in the portfolio management process?
At Quorus, we make decisions at the individual tax lot level for every portfolio. That level of granularity is essential because it lets us be precise in managing gains and losses. When we're rebalancing or transitioning a portfolio, we can choose not just which security to trade but which specific lots to sell or avoid selling altogether.
This approach allows us to harvest losses more effectively by targeting the lots with the highest loss potential. It also allows us to avoid realizing significant gains when clients have low basis shares or specific tax concerns. We can implement rules like “don’t sell any lots with more than a 100% gain” or “don’t touch this specific holding” and honor them at the lot level.
The result is a portfolio that not only reflects the client’s preferences but also fully takes advantage of tax-loss harvesting opportunities without triggering unnecessary gains. That kind of control simply isn’t possible without lot-level decision-making.
Q: What makes tax management different for active strategies versus passive?
Tax management for active strategies is fundamentally different because every active manager is unique; we often say, "every active manager is a snowflake." Unlike passive portfolios, which follow predefined index rules and experience low, predictable turnover, active strategies can change rapidly based on the manager’s conviction.
This variability means we can’t apply a one-size-fits-all approach. Instead, we work closely with each asset manager to design a tax overlay that reflects how they manage money. That might mean setting different tracking error tolerances, handling short-term gains differently, or choosing how proceeds from tax-loss harvesting are reinvested.
For example, with a fundamental manager, if we sell a stock like Apple, they might prefer we spread that capital across their other top ideas rather than using a single like-kind replacement. On the other hand, with a quant strategy, we may focus on maintaining precise factor exposures, so we’ll harvest losses in a way that preserves the statistical characteristics of the portfolio.
It's not just about protecting tax alpha; it’s about making sure the tax strategy complements the manager’s investment process. Because these portfolios are often run at scale, we need to lock in the right methodology up front so it can be consistently applied to every client who’s invested in that strategy.
Ultimately, tax management for active investors is as much about understanding the strategy and building trust with the manager as it is about optimizing portfolios. That alignment ensures we’re delivering value without diluting the investment thesis.
"Every active manager is a snowflake. You can’t use a one-size-fits-all tax strategy and expect to preserve their investment intent."
Q: How do you build a tax management program for an active manager?
We begin by digging into the manager’s investment philosophy and process. Are they a value manager? And if so, is it deep value, relative value, or intrinsic value? Or are they a quant shop focused on factor exposures? Understanding how they identify and implement investment ideas helps us determine what kind of customization will work best.
From there, we spend time with the portfolio management, sales, and product teams to learn how the strategy is positioned, sold, and used by clients. That context is essential because it shapes expectations around turnover, concentration, and how much deviation from the target model is acceptable.
Next comes the backtesting. We run the strategy through various tax overlay configurations to see how different approaches would have impacted performance over time. We look at metrics like tracking error, turnover, and whether we’re unintentionally selling the manager’s highest-conviction positions to harvest losses. That helps us understand the fundamental tradeoffs between tax alpha and investment alpha.
Based on that analysis, we start dialing in the parameters, adding constraints where needed, or relaxing them if the strategy can tolerate more flexibility. For example, a higher-turnover strategy might be acceptable, realizing short-term gains to stay aligned with the manager’s signal, whereas a lower-turnover strategy might avoid them altogether.
It’s a collaborative process from start to finish. The goal is to create a program that reflects the manager’s strategy while optimizing for after-tax results across every client account.
Q: How do you think about tracking error in this process?
We see tracking error as more of an output than a constraint. We start by trying to build the most tax-efficient portfolio and then see how far that takes us from the manager's model. If the tracking error is too high, we adjust.
It's about finding the right tradeoff between investment alpha and tax alpha. That means setting optimizer rules that fit the strategy. We might allow selling 50% of a target position for a concentrated portfolio. For a diversified strategy, the harvesting might be finer-grained. Again, the key is alignment with the manager's investment approach.
"You can have the best methodology in the world, but if you can’t run it consistently across every client and every strategy, it doesn’t matter. Scalability is everything."
Q: What role does scalability play in all of this?
Scalability is everything. You can have the best methodology in the world, but it doesn't matter if you can't consistently run it across hundreds or thousands of accounts.
What sets Quorus apart is our ability to apply custom optimization logic, manager by manager, client by client, daily. If there's a portfolio update, strategy change, or even a single client preference shift, we catch it right away. Missing that is not just a missed opportunity for tax alpha; it introduces unwanted drift from the investment strategy.
Q: Final thoughts on Quorus's active overlay approach?
The real differentiator is how deeply we partner with asset managers. It's not just about running an optimizer. It's about understanding each strategy, building trust, and designing tax programs that respect the investment process. Index providers don't care if you harvest losses or exclude a name. Active managers do, and we make sure they're comfortable with every aspect of the overlay.
Ultimately, we aim to make active SMAs more tax-efficient without compromising their core strategy. That combination is rare; we think it's game-changing for advisors and their clients.
Disclosures
All investing is subject to risk, including possible loss of principal.
Quorus Inc. (“Quorus”) is an advisor registered in the states of Connecticut and Pennsylvania. The material presented is for informational purposes only and should not be construed as investment advice. It is not a recommendation of, or an offer to sell or solicitation of an offer to buy, any particular security, strategy, or investment product. Investing in securities involves risks, including the potential loss of money, and past performance does not guarantee future results. Historical returns, expected returns, and probability projections are provided for informational and illustrative purposes and may not reflect actual future performance. Product images shown are for informational and illustrative purposes only, and may not reflect how they will actually appear within the product. Nothing in these materials should be construed as personalized investment advice, which can only be provided in one-on-one communications
.webp)
