David Stemerman ran one of the largest equity long-short launches in history. Then he walked away and built something entirely different. CenterBook Partners – a buy-side alpha capture platform now managing well over $1bn – is his answer to a structural problem he believes the pod model created but cannot solve.
In 2008, David Stemerman launched Conatus Capital with over $2 billion in assets — the largest equity long-short launch on record at the time, backed by his ex-employer Steve Mandel and Lone Pine. By most measures, it was a career-defining moment. By his own account, it was also the beginning of a longer education in the limits of a model he had grown up believing in.
The Tiger methodology — get your stocks right, one at a time, and the rest takes care of itself – worked brilliantly for a period. It did not work in 2008. It struggled again in years where factor exposure, not stock selection, determined returns.
And as the pod model rose to dominance through the 2010s, the fundamental long-short manager found themselves increasingly squeezed: too directional for allocators, too constrained for pods, and facing a capital-raising environment that had moved the minimum viable launch threshold far beyond where most independent managers could realistically get.
Stemerman watched all this unfold, stepped back, and came back in 2021 with a different idea. CenterBook Partners, the buy-side alpha capture platform he founded and now manages north of $1.3bn, is built on a simple but structurally ambitious premise: isolate the idiosyncratic stock-picking alpha that the best fundamental managers generate, strip out everything else, and deliver it in a return stream that works across a wide range of market environments. In doing so, it aims to rescue something the industry was quietly losing.
What the pod model cannot do
To understand what CenterBook is trying to build, Stemerman told Hedgeweek®, it helps to understand what it is explicitly not. The multi-manager pod model brought quantitative rigour to the problem of factor risk. It recognised that a large portion of what bottom-up stock pickers attributed to skill was, in reality, explainable by factor exposure: growth, momentum, value. Strip that out, manage drawdowns tightly, run many uncorrelated books in parallel, and you have a machine for generating consistent, low-volatility returns.
“Part of what I experienced running Conatus,” Stemerman says, “is that some years the returns were great — we did a great job picking stocks and it showed through. In other years, Conatus was more of a growth-oriented manager. And if it was a year where growth was out of favour, that might have as much to do with our returns as anything else.”
The pod model solved that problem. But it created others. Tight drawdown limits, strict factor constraints, and short investment horizons make it a poor fit for a certain kind of fundamental manager — one whose edge comes precisely from the willingness to hold a position through noise, to be early, and to be wrong before being right.
“There are lots of bottom-up stock pickers that have a hard time in a pod. They have very tight drawdown limits, very tight factor exposures. And some of them want to run their own portfolio, their own way.”
The Africa Bank short he ran at Conatus seems to be the clearest illustration of the point. The thesis was straightforward: the underwriting reminded him of subprime mortgages, the funding model reminded him of Lehman Brothers, and the combination pointed to eventual bankruptcy. The stock did eventually go to zero. But between the initial short and the outcome, it went up — significantly. In a pod, with tight drawdown limits and a short horizon, that position would never have survived long enough to be proved right.
“For some managers, the pod model is a great fit,” Stemerman acknowledges. “For others — and I would count myself among them — it would not be.” The consequence of a decade of capital and talent flowing toward the pod model is that a generation of independent fundamental managers have been left without a viable path. Either they join a pod on terms that compromise their investment style, or they try to launch independently into a capital-raising environment that has moved the goalposts dramatically.
The alpha capture idea
Stemerman is quick to acknowledge the concept he built CenterBook around — alpha capture — is not new. Marshall Wace pioneered it on the sell side, beginning with a bet between the two founders about whether sell-side research contained any actionable signal. It turned out it did. Marshall Wace built a multi-billion-dollar business extracting it systematically.
The innovation here, according to him, is to do the same thing with the buy side. The platform partners with independent bottom-up fundamental stock pickers — currently over 40 managers globally, on the way to 50 by mid-year and 100 beyond that — and aggregates their highest-conviction ideas. The quantitative layer then does what quants do well: sizing, risk management, factor neutralisation. The result, in theory, is a return stream that captures the genuine idiosyncratic stock-picking alpha of a diverse network of fundamental managers, with everything else stripped out.
“We’re a bit like card counters at the casino. We have differentiated insight into which managers to select — both from how they actually performed and from their process discipline.”
The data advantage, Stemerman says, CenterBook has built is central to the pitch. Where a typical allocator sees monthly or weekly returns data and tries to infer whether a manager has skill, CenterBook gets position-level data daily, run through a risk model. That allows a far more precise decomposition: how much of the return came from idiosyncratic stock selection versus factor exposure? Long side or short side? Equal-weighted or conviction-weighted?
The second data source is Alpha Theory, a portfolio management tool that many of the partner funds use to prioritise positions and record price targets, financial forecasts and qualitative judgments. “Managers that are doing the work — that have most of their stocks with price targets, that are updating those price targets frequently — that demonstrates real process discipline and repeatability,” Stemerman says. Combined with the returns decomposition, it gives CenterBook what he describes as a card-counter’s edge in manager selection.
The trust problem
The obvious question — and Stemerman acknowledges it was the central question of whether the model would work at all — is why any good fundamental manager would share their portfolio data, price targets and investment thesis with another fund. The history of alpha capture on the sell side began precisely because hedge funds refused to share that data. Getting the buy side to do it voluntarily was a different proposition entirely.
The answer CenterBook arrived at is a partnership model built around a credible set of protections and genuine two-way value. On the protection side: no trading in hard-to-borrow or high short interest names, strict limits on daily trading volume, T+1 data receipt, a light market footprint, full audit rights for partner funds, and reimbursement for any measurable market impact. “We say we’re looking out for you,” Stemerman says. “And we mean it.”
Beyond the economics, CenterBook shares analytical feedback with partner funds on where their genuine skill lies — sector, position type, long versus short — and how their portfolio construction could better reflect it. The implied promise is that the relationship improves returns in the partner fund itself, not just in the alpha capture strategy. Whether that promise holds at scale is, ultimately, what the next few years will test.
Why now?
CenterBook was designed to be all-weather — built for a range of economic conditions rather than any particular regime. But Stemerman is candid that the current environment is unusually well suited to what the platform does.
The most important shift is the broadening of the investable universe. After years of a narrow market dominated by US mega-cap tech, growth has widened across sectors and geographies. Industrials, healthcare, financials, consumer — all are generating the kind of winners and losers that fundamental stock pickers exist to find. Europe and Japan, long written off, are showing genuine dynamism. “Coming into 2026, if I had been running Conatus, I would be like a kid in a candy store,” he says.
AI is the second factor — not as a narrow TMT theme but as a disruptive force beginning to reshape sector after sector. Caterpillar was among the top-performing stocks in 2025, driven by data centre construction demand. Drug discovery is being transformed. The breadth of disruption, Stemerman argues, is what matters — and it is still widening.
The third is simply time. Five years in, the contributor network has reached the critical mass the multi-manager model requires. The investment strategy has been tested across multiple regimes. “This is perhaps the end of the beginning,” he says. The test now is whether the returns bear that out.
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Manas Pratap Singh | Hedgeweek®
