In this episode, Future Standard’s Investment Research team members Alan Flannigan and Andrew Korz sit down with Scott Burr, Senior Portfolio Manager at Future Standard, to discuss how multi-strategy investing may help investors navigate a changing macro regime.
1. Executive Overview & Speaker Profile
Scott Burr introduces himself as a senior portfolio manager at Future Standard who manages a liquid alternative absolute return strategy. [00:01:40]
Scott shares his origin story as a native New Yorker who grew up reading the tiny-font stock tickers in the back pages of the business section, despite his parents having no professional background in finance or markets. []
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In the year 1992, while in middle school, Scott's father put $1,000 into an E*Trade account for him. Based on his early analysis that computers were going to be a major secular shift, Scott executed his first trade by buying Comp USA. While the electronics retailer eventually went bankrupt years later, the macro thesis on computing proved correct. [00:03:55]
Scott attended Stuyvesant High School, an elite and intensely competitive public math and science high school in New York City with approximately 800 kids per graduating class and an average SAT score of 1450. [00:04:27]
The high school published an annual matriculation matrix detailing exactly how many students applied to each college, how many were accepted, and explicitly stating the lowest Grade Point Average (GPA) accepted to that specific university, which structurally intensified student competition. [00:05:01]
Scott details that entering an environment where you are no longer automatically the smartest individual provides the ultimate training ground for financial markets. It forces an investor to realize that a durable edge cannot be built on raw intelligence alone; instead, it requires developing a systematic "variant approach" to generate a "variant perception." [00:05:17]
2. The New Macro Regime and the Structural Flaws of 60/40
Host Alan notes that macroeconomic, geopolitical, and policy "uncertainty" has transitioned from an exogenous disruption to an endogenous characteristic embedded directly inside the global market system. [00:00:10]
The global economy has experienced six systemic shocks in a brief six-year window: a global pandemic, severe inflation, systemic bank failures, two major geopolitical wars, and an absolute upending of the international trade network. This frequency indicates a structural macro regime change. [00:00:52]
Scott highlights that traditional asset allocation frameworks, specifically the standard 60/40 portfolio (60% equities, 40% bonds), are structurally ill-equipped for the forward-looking regime. The 60/40 portfolio historically anchored institutional wealth because bonds provided reliable risk mitigation against equity beta. [00:07:08]
The year 2022 operated as the structural "canary in the coal mine" for asset allocation. Portfolios that appeared superficially diversified across multiple line items suffered severe drawdowns because equity beta and bond beta (duration/interest rate sensitivity) decoupled, causing both asset classes to crash simultaneously. [00:09:57]
Liquid alternatives must serve as a true "third leg of the stool." To achieve an all-weather profile, an absolute return strategy must explicitly strip out underlying equity beta and bond duration risk, deriving the vast majority of its returns from alternative risk premia. [00:08:57]
Investors suffer from recency bias due to a spectacular 10-to-15-year bull market run in equities, making structural diversification feel unnecessary. [00:10:41]
Historical data demonstrates that rolling 10-year equity periods frequently experience "lost decades." For instance, from 2001 to 2010, the U.S. equity market failed to sustainably eclipse its peak dot-com bubble all-time highs for roughly 10 to 12 years. [00:11:12]
3. Liquid Alternatives vs. Institutional Multi-Strategy Pod Shops
Co-host Andrew notes that institutional multi-strategy platforms (popularly termed "pod shops") utilize small, siloed portfolio management teams running distinct sub-strategies with a massive risk overlay deployed on top. [00:12:05]
Scott breaks down the structural differences between his liquid alternative fund and large pod shops. Structurally, liquid alternatives operate with tighter regulatory leverage limits, but they act as low-fee providers of pure alpha. In contrast, institutional pod shops carry an notoriously heavy fee load driven by pass-through expenses and steep performance fees. [00:12:56]
Large multi-strategy pod shops are often highly relaxed regarding their underlying structural beta loads. If an alternative fund carries a hidden 0.2 or 0.3 equity beta to generate headline returns, scrubbing the portfolio analytics reveals that the overwhelming majority of its risk is actually a basic levered bet on equity beta. [00:13:25]
Multi-strategy investing can be modeled mathematically as a balancing act between Breadth and Depth:
Breadth: Universal access to the entire global menu of liquid asset classes, paired with a wide net of technical absolute return strategies to source opportunities. [00:14:52]
Depth: The deep, specialized domain knowledge and technical skill required to extract durable alpha from each market. [00:15:04]
While institutional pod shops attempt to buy depth by placing active teams across every single market simultaneously, Scott's strategy focuses on selectivity. The fund dynamically rotates its capital and balance sheet to lean specifically into alternative sub-strategies that possess the most durable medium-to-long-term tailwinds. [00:15:26]
4. Investment Hardwiring, Decisive Processes, and Diversification Math
Scott explains that an investor's execution framework is directly linked to their personal behavioral hardwiring, sharing four specific personal anecdotes: [00:17:35]
He will actively drive out of his way to fill his car at the cheapest gas station; it is a foundational principle of successfully extracting transaction alpha from a risk-reward situation, rather than a matter of saving $7 or $10. [00:17:55]
When relocating from New York City to the suburbs, he discovered a structural property tax arbitrage. Due to local municipal classifications, a townhome incurred exactly half the ongoing property tax expense of an identically priced, free-standing house right across the street. [00:18:16]
He successfully "bottom-ticked" macro interest rate duration by locking in his home mortgage at a fixed rate of 2.5%. [00:18:57]
He systematically takes his elementary-school-aged children out of school one week early for December winter vacations. Running the future-value numbers of the trade reveals that executing a holiday one week early drops flight costs by 3x and cuts hotel rates by exactly 50%, avoiding highly inefficient peak pricing. [00:19:11]
When querying Large Language Models like ChatGPT, the AI recognizes his systematic behavioral pattern, frequently prefacing responses with, "Because you're such an analytical person, let me break it down to you this way." [00:20:43]
Scott aligns his allocation philosophy with Ray Dalio's "Holy Grail of Investing" framework rather than Warren Buffett's concentrated conviction strategy. [00:21:27]
He outlines the absolute mathematical reality of diversification: combining two separate assets with identical volatility profiles that are completely uncorrelated (0.0 correlation coefficient) automatically slashes total portfolio risk by 30%. Integrating a third completely uncorrelated asset drops total portfolio risk by an additional 15%. This statistical behavior remains the only true "free lunch" in finance. [00:22:14]
To overcome analysis paralysis in highly analytical environments, Scott implements Howard Marks’ core philosophy: you cannot judge the quality of an investment decision solely by its immediate historical outcome. Because the future is uncertain, an elite manager focuses strictly on the repeatability of a quality process; a high volume of quality decisions will naturally compound into highly profitable outcomes over the law of large numbers. [00:23:22]
5. The Trade Filter System: Signal Agreement & Implementation Alpha
Future Standard allocates a portion of its corporate balance sheet externally to specialized, niche manager strategies including convertible arbitrage, merger arbitrage, and long-short credit. Deployed capital requires matching specific regime tailwinds (e.g., tracking corporate issuance volumes for convertible arb, or global deal volume for merger arb). [00:30:30]
To prevent drinking from an unvetted fire hose of ideas, Scott filters internal, opportunistic absolute return trades through a precise three-pronged framework: [00:31:37]
Signal Agreement: An idea must achieve simultaneous alignment across independent underlying variables, acting as an asymmetric checklist across fundamentals, market positioning data, macroeconomic factors, and hard catalysts. [00:32:06]
Historical Case Study: In late 2021 and early 2022, high-growth, non-profitable technology names (exemplified by Kathy Wood/ARK type assets) exhibited hyper-extended valuations alongside extreme positioning congestion. When this positioning squared up against the macroeconomic catalyst of an aggressive Federal Reserve interest rate shock, it created a highly profitable long-reflation vs. short-unprofitable-tech value spread trade. [00:33:00]
Historical Case Study: The systemic widening of the mortgage basis when the Federal Reserve explicitly pivoted its monetary policy from Quantitative Easing (QE) to Quantitative Tightening (QT). [00:34:02]
Implementation Alpha: Discriminating aggressively between different execution methods to construct a trade. Rather than utilizing a vanilla interest rate curve steepener trade (manually buying front-end treasuries and selling back-end duration), Scott leverages volatility and skew markets. He constructs the exposure by selling a payer option on the front end of the curve and purchasing a payer option on the back end, extracting superior portfolio carry and capturing structural convexity. [00:34:12]
Risk-Return Determinism: Differentiating "fuzzy math" directional forecasting from highly deterministic trades. For instance, a classic merger arbitrage position presents a highly tangible risk-return profile; if a corporate deal completes, the final transaction price and the explicit downside boundary are mathematically bounded and highly reliable. [00:35:56]
6. Exploiting the AI Regime Shift via Cross-Sectional Alpha
Andrew outlines Future Standard’s Q2 Economic Outlook, emphasizing that while the U.S. economy remains resilient, supply-side macro shocks are increasing in frequency due to a global shift away from pure economic efficiency toward nationalistic competition. [00:37:28]
Scott notes that a low-beta alternative strategy thrives during periods of market tumult, fear, and asset mispricing, whereas a low-volatility, sleepy environment like 2017 presents fewer active management opportunities. [00:41:43]
Maintaining a structurally low-beta portfolio means that when severe market shocks occur, the fund avoids risk mitigation or liquidating positions. Instead, it plays offense and deploys capital into deeply discounted assets from a position of strength. [00:42:20]
Scott directly challenges the common institutional narrative that "equity beta is now entirely AI beta." While concentrated mega-cap capital expenditure (capex) spending has driven headline S&P 500 indexing higher, the median stock within the S&P 500 index has actually trended flat to negative year-to-date. [00:44:09]
The genuine absolute return opportunity in the artificial intelligence revolution is found entirely within cross-sectional dispersion rather than broad equity beta. As a stark example, the year-to-date performance spread separating semiconductor hardware companies (semis) from enterprise software companies reached an astonishing 60%. [00:45:56]
Big Tech hyperscalers are deploying massive capex into highly cyclical businesses that carry heavy operating leverage. Wall Street models project a flatlining of hyperscaler capex next year under the assumption that these technology firms can stop spending and harvest immediate cash flows. However, the current environment is defined by structural compute scarcity. Scott views buying hyperscalers at current valuations as a difficult proposition until forward capex estimates stabilize. [00:47:15]
The structural paradigm can be mapped across decades: the 2010s represented the decade of the consumer subsidy (where venture capital heavily subsidized consumer services like ridesharing), whereas the 2020s represent the decade of the enterprise subsidy. Major foundational AI model labs are losing significant capital to supply enterprise clients with artificially underpriced tokens. [00:49:44]
To capture the structural AI infrastructure thesis without taking on expensive equity valuation risk, Scott’s fund is shorting equity valuations and is long the credit side of the digital infrastructure buildout. The massive financing demand required to construct modern data centers has created a major wave of new asset supply inside the ABS and CMBS credit markets. Consequently, data center credit structures are trading at significantly wider spreads relative to identically rated corporate bonds in the public market, offering high-yielding structural alpha. [00:50:00]
7. The Symbiosis of Liquid Alternatives and Private Markets
Scott explains that liquid alternatives and expanding private market structures (such as evergreen vehicles or private credit drawdown funds) must not be viewed as competing allocations, but as highly symbiotic components of an institutional portfolio. [00:53:30]
He rejects static, "set-and-forget" allocation mandates that bifurcate wealth into entirely liquid or entirely illiquid sleeves. Portfolios require liquid alternative lines to operate as strategic liquidity levers. [00:54:47]
When illiquid private markets experience structural distress or severe valuation drawdowns, an active allocator can efficiently harvest capital from their resilient, absolute return liquid alternative allocations to fund distressed private market drawdowns. Conversely, when private market distributions materialize during peak periods, the liquidity can be parked in liquid alternatives rather than diluting returns in low-yielding cash. [00:55:12]
From a risk management perspective, true financial risk is not short-term mathematical volatility, but the absolute permanence of a structural drawdown. The primary purpose of injecting uncorrelated alternative streams is to structurally transform the mathematical skew of a portfolio by curtailing extreme downside tail events. [00:57:17]
Scott concludes with a foundational institutional distribution anecdote from his early days at Future Standard. While trying to explain complex asset correlations, mathematical betas, and the technical laws of diversification to the distribution team, an institutional salesperson cut through the quantitative jargon, asking: "Are you saying that this strategy is going to be there for you exactly when you need it to be?" Scott confirms that this statement remains the accurate definition of a true absolute return diversifier. [00:59:21]
"The game is not over until I win." Kunal Sabnis 00:08:10 http://www.youtube.com/watch?v=oVODogtstTA&t=00m08s "Any mishap cannot happen unless you are debt levered." Kunal Sabnis 00:11:14 http://www.youtube.com/watch?v=oVODogtstTA&t=11m14s…