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 outperformance. He distinguishes quant from systematic investing, emphasizes breadth, risk premia, and regime awareness, and explains how distribution, wrapper choice, compliance, and education shape asset-management success more than pure strategy quality.

Main Topics: Quant vs. systematic investing (Priority: 5/5): Hofstein clarifies that 'quant' is a broad umbrella covering many quantitative roles, while systematic investing is a narrower subset using mathematical models and computers in a repeatable way. Breadth, market timing, and strategy quality (Priority: 5/5): He argues that low-breadth bets like market timing are difficult to prove, hard to repeat, and often reflect luck, while high-breadth strategies with clear economic logic are more believable. Risk premia vs. anomalies and regime change (Priority: 5/5): The conversation contrasts persistent, explainable risk premia (like merger arbitrage) with faith-based anomalies (like momentum), and stresses the need to reassess old assumptions as markets evolve. Building Newfound and the shift from research to asset management (Priority: 4/5): Hofstein recounts founding Newfound as an IP business, then moving into funds and ETFs after client demand and market events changed the business landscape. Distribution, wrappers, and business model fit (Priority: 5/5): He explains that strategy alone is insufficient; the vehicle (ETF, mutual fund, private fund) must fit both the investment process and the distribution channel. Return stacking and solving client utility problems (Priority: 5/5): The firm's current products are designed to overlay diversifying exposures onto existing portfolios, making alternatives more usable for RIAs and investors who face compliance or operational constraints. Content, education, and brand-building (Priority: 4/5): Hofstein describes research, podcasts, and social media as top-of-funnel tools that educate advisors, build trust, and support sales rather than directly driving measurable ROI.

Key Arguments: Quant is a very broad category; systematic investing is specifically the application of quantitative models via computer programs in a repeatable way. Market timing is usually low-breadth, making it hard to establish statistical skill and highly vulnerable to survivorship bias. Broad, repeatable strategies with an identifiable economic rationale are more credible than one-off calls or opaque patterns. Persistent risk premia can survive even when crowded, but their attractiveness depends on current market structure and investor behavior. Many lower-frequency anomalies require faith because there is not enough data to know when a regime has truly changed. Investment businesses fail when product wrapper and distribution strategy do not match the strategy and target client. Advisors and investors buy products for utility, not just expected return; behavioral and operational convenience matter. Return stacking works because it lets clients add diversifiers without abandoning a core 60/40 allocation, reducing behavioral friction. Research and content are valuable for awareness and education, but they must be understood as part of a marketing and distribution funnel. AI and machine learning are already useful as research tools, but standalone AI investment theses remain unproven and likely to emerge first in high-fee institutional or hedge-fund settings.

Data Points: Newfound founded: 2008 - Hofstein says the firm began as an IP/research business in 2008. Graduate/job-market backdrop: 2008 crisis / 2009 graduation - He finished undergrad in 2009 and entered grad school as Wall Street hiring collapsed. Model portfolio fees (early 2010s): 80-100 bps - He says actively managed ETF model portfolios could command 80 to 100 basis points early in the decade. Model portfolio fees (later): down dramatically / 0 for some models - Fees fell as BlackRock and State Street offered models for free. Active equity strategy fee: 40-60 bps - He cites current fee levels for active equity products. Index/provider fee share: 5-10 bps for long-only, 20% of fee or less in many cases - He describes current economics for index licensing and advanced indices. AUM growth from client event: zero to almost $1B - He says Newfound quickly gathered assets when money moved away from a client that had committed fraud. Client mandate lost: $750 million to zero - Goldman Sachs acquisition led to a mandate termination via a phone call. Almost $1B of flows: almost a billion dollars in flows - He says the return-stacking suite attracted nearly $1B in two and a half years. Return-stacking suite launch to flows period: 2.5 years - Flows accumulated quickly after launch. Research paper downloads: 35,000 to 40,000 - He estimates 'Liquidity Cascades' was downloaded roughly this many times. Small-cap premium reassessment: 20 to 30 years - He notes it took decades for investors to question whether the small-cap premium truly existed. Compliance layers for public product discussion: 13 layers - He jokes that discussing a ticker publicly would require multiple compliance approvals.

Pivotal Quotes: "When I talk to people about bringing products to market, it can't just be my value proposition as a product is I beat the market." — Corey Hofstein: He explains that product design must solve a client need beyond simple outperformance. "What's the breadth of the strategy?" — Corey Hofstein: His core framework for judging whether an investment approach is likely real and repeatable. "The way I think about running the business from being someone who cared about investment management to being someone who has to spend a lot of time focusing on asset management." — Corey Hofstein: He describes the mindset shift required when moving from researcher/PM to CEO.

Implications: For investors and asset managers, the lesson is that strategy quality is necessary but not sufficient. Success depends on breadth, adaptability, client utility, wrapper fit, and distribution. Future product winners will likely combine investment edge with operational and behavioral advantages.