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David Sargent Wood, Ph.D., is Co-Chief Investment Officer and Chief Quantitative Strategist, Senior Managing Director at Nuveen Brooklyn, where he leads portfolio technology development and runs the portfolio management team, including the firm's day-to-day systematic investment processes. Before Nuveen's 2025... more
Positions
- Co-CIO and Chief Quant Strategist, Senior Managing Director, Nuveen Brooklyn (2025–)
- Chief Quant Strategist and Co-CTO, Brooklyn Investment Group (2022–2025, acquired by Nuveen)
- Head of Quant Strategies, Hum Capital (2020–22)
- Quant Researcher, Credit Suisse (2018–20)
Education
- Ph.D. in Statistics & Econometrics, The University of Chicago (2018)
- M.B.A. in Finance, The University of Chicago (2017)
- A.B. in Economics, The University of Chicago (2010)
- Ultracode
- Fatal strategies: the half-life of fortune and the gradient of complexity
- zzHELP: a dispatch from inside the swarm
- Should you buy a home with a box spread?
- Bull herding and bullshitting: why judgment matters more than intelligence, models, or machines
- The financial clinic: interaction engineering in financial services
- LLM internals specimen sheet
- The Bauhütte Standard: reality before loyalty
- Co-Brain: l’approche de la mer, and why AGI may never emerge from LLMs
- Deep persuasion: grokking, storehouse, and weights
- Hiring against the room
- Bend the chimney; move the firewood
- Worse is better and the right thing
- Good companies and good-looking companies: lost dimensions of work
- Cognitive resignation: LLM and the hollowing of expertise
- How much customization should a financial platform offer?
- Markov processes and Kolmogorov equations
- Reflections on financial advisory and portfolio management
- Understanding long and short margin mechanics
- Deep learning at scale: lesson from experiments from Perlmutter
- Scalable GPU programming for exascale: multi-node and multi-GPU strategies
- From bricolage to engineering: regularizing complexity
- Bayesian deep learning: uncertainty, inductive bias, and modern theory
- Selling modern financial products: comparing SMAs, SaaS, and asset management
- From physical toil to cognitive burnout: modern labor and the ethics of software design
- Internal states, external worlds: concurrency, consensus, and sociotechnical challenges in computing
- Engineering speak: prolegomena to ideal technical discourses
- Self-healing computation: building resilient financial computational services
- Cognitive mirror: how LLMs compress language and challenge our sense of self
- Basis trade and treasury deleveraging
- The Triffin dilemma and the exorbitant privilege
- Client-side connection pool management
- Zoo keeping: dynamic assembling based on subclass attributes
- Go getters: a monadic way
- Take a walk on the functional side: yes, we need monads
- Working with distributed workers
- Cooperative concurrency with FastAPI: it's the generators, stupid
- Wrapping around wrappers: primer on decorators
- Simple SSL-based encryption
Research Statement
My research operates at the intersection of high-dimensional financial time series, modern applied mathematics, and computational physics. I’ve always gravitated toward non-parametric, structure-seeking techniques—drawing on geometry, spectral methods, and ideas inspired by quantum field theory and statistical mechanics. I view… more
Projects
- Integers and curves: a gentle introduction to MINLP (2026)
- MTS for R—all-purpose toolkit for multivariate time series (with Ruey Tsay and contributions from Jon Lachmann and Renze Dijkhuizen, 2022)