Why Beating the Market Isn’t Enough for Investment Managers | Corey Hoffstein

Episode Summary

Executive Summary: Corey Hofstein argues that successful investment products must solve a client problem, not just promise to beat the market. The discussion covers how to judge quant/systematic strategies by breadth, repeatability, and risk premium logic; why market timing and low-breadth signals are often luck-prone; how product wrapper, distribution, and compliance shape asset-management businesses; and why return stacking/portable alpha can improve adoption by fitting investor behavior and constraints.

Main Topics: Defining quant vs. systematic investing (Priority: 5/5): Hofstein distinguishes broad quantitative work from systematic investing, arguing that 'quant' spans many roles, while systematic investing specifically means mathematical models applied via computer programs in a repeatable way. How to judge strategy quality: breadth, repetition, and edge (Priority: 5/5): He says the best test of a strategy is breadth—how many independent bets it makes—because low-breadth approaches like market timing are hard to validate and vulnerable to luck, while diversified strategies like merger arbitrage are more plausible. Risk premia vs. anomalies and market structure change (Priority: 5/5): The conversation contrasts persistent risk premia (e.g., merger arbitrage) with more faith-based anomalies (e.g., momentum), and argues that investors must continually reassess whether old premia still exist as market structure evolves. From research firm to asset manager (Priority: 4/5): Hofstein recounts how Newfound Research evolved from licensing research to managing products, driven by client demand, business realities, and the need to control distribution rather than just sell ideas. Distribution, wrappers, and the economics of asset management (Priority: 5/5): A major theme is that distribution strategy can matter as much as investment strategy. He explains how ETF, mutual fund, hedge fund, and private-fund wrappers each align differently with strategy, regulation, fees, and client access. Return stacking / portable alpha as product design (Priority: 5/5): He describes using portable alpha concepts to create ETFs that let investors keep core stock/bond exposure while adding diversifiers or leverage overlays, solving behavioral and operational problems for advisors and clients. Content, branding, and compliance as growth tools (Priority: 4/5): Hofstein sees research, podcasts, and social media as top-of-funnel brand-building that supports sales education and retention, while noting that compliance limits direct product promotion in public channels.

Key Arguments: Quant is a very broad category; systematic investing is the narrower practice of applying mathematical models through computer programs in a repeatable way. Breadth is the best indicator of whether a strategy reflects genuine edge rather than luck: many repeated bets are more credible than a single high-conviction call. Market timing is especially hard to validate because it is low breadth, low frequency, and often judged only after the fact. Merger arbitrage is a more believable persistent risk premium because the risk is identifiable, the spread is repeatable, and the strategy can be diversified across many deals. Momentum is a powerful anomaly across asset classes, but its explanation is weaker and its persistence is harder to prove; thus it requires more faith. Investors must continually reassess old premia because passive flows, IPO decline, and other structural shifts can alter the conditions that made a strategy work. An asset-management business needs a distribution strategy that fits the product; good ideas fail if they cannot reach the right channel or wrapper. Product design should solve a client utility problem, not merely aim to outperform; behavioral comfort and portfolio fit matter as much as raw return. Return stacking works because it lets clients add diversifiers or leverage without forcing them to abandon a core 60/40 allocation or manage leverage operationally themselves. Content creation is valuable not only for awareness but for educating advisors, answering recurring questions, and supporting retention after clients are onboarded. Public research often doubles as marketing; readers should ask who the target audience is and why the piece was written. AI/ML is already used heavily by quant firms as a research and analysis tool, but fully autonomous AI portfolio construction remains uncertain and early-stage. Data Points: Newfound Research founding year: 2008 - Hofstein says the firm was founded in 2008 as a research/IP business. Undergrad/grad school timing: 2009 - He graduated undergrad in 2009 and went directly into graduate school. Old model-portfolio pricing: 80-100 bps - He says actively managed model portfolios could charge this in the early 2010s. Current active equity product fees: 40-60 bps - He notes active equity products have fallen substantially in fee level. Index provider compensation: 5-10 bps - He says long-only index providers are now often lucky to get around this amount. Advanced index compensation share: 20% of overall fee or less - He estimates index providers often receive a minority share of product fees. AUM growth after product launch: 0 to almost $1 billion - He says the business quickly grew when assets moved into the new product. Client mandate lost in one call: $750 million to zero - A Goldman Sachs acquisition led to the firing of managers and immediate asset loss. Product suite flows: almost $1 billion in 2.5 years - He says the return-stacking suite attracted nearly a billion dollars of flows in a relatively short period. Liquidity Cascades paper downloads: 35,000-40,000 - He cites this as an example of a paper that went viral in finance circles. Advisors charging for model portfolios: ~80 bps - He mentions this as a historical pricing level for active models in the early 2010s. Public company deal example: $40 acquisition price - Used as an example of merger-arb spread mechanics when a stock jumps toward the announced deal price.

Pivotal Quotes: "It can't just be my value proposition as a product is I beat the market. That's a commoditized value proposition." — Corey Hofstein: Explaining how he thinks about product positioning and why client utility matters beyond performance. "Breadth as being like the number one way of saying, Do I think that this is something that is repeatable or not?" — Corey Hofstein: On evaluating whether a systematic strategy reflects real edge or just luck. "Our value proposition of a product is yes, we do think over the long run, this has the possibility to beat the market, but it does all this other really important stuff from a client sustainability perspective that makes it really unique." — Corey Hofstein: Describing the logic behind return-stacking products and the emphasis on behavioral and portfolio benefits.

Implications: Listeners should assess strategies by repeatability, breadth, and client fit, not just headline returns. For the industry, product success increasingly depends on distribution, compliance, and behavioral design—not only alpha claims.