Latest research
After-Tax Alpha: Why Tax Management Became the Battleground
When beta is free, after-tax outcome is the last reliable edge — and it rewards computation over intuition.
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What "Institutional-Grade" Actually Means for an Optimization Engine
The five testable properties that separate the real thing from the brochure — and the questions that reveal which you're looking at.
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The Personalization Wave: Why Direct Indexing Is Eating the SMA
The market is shifting from pooled funds to personalized, tax-managed accounts faster than almost anyone is operationally ready for.
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The Overnight Batch: Pricing a Whole Book Before the Open
Why nightly rebalance batches break at scale — and why deadlines are governed by tails, not averages.
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A Practical Taxonomy of Portfolio Optimization Methods
Convex, integer, first-order, heuristic, quantum — a vendor-neutral guide to what each family is good at and where it breaks.
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Wash Sales, Lots, and the Hidden Complexity of After-Tax Investing
Why tax-loss harvesting is a constrained optimization problem, not a spreadsheet exercise.
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Build vs. Buy: The True Cost of an In-House Optimization Stack
The prototype is the cheap 20%. Scale, validation, audit, and years of maintenance are the rest.
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Determinism, Reproducibility, and the Coming Audit Standard
Why reproducibility is becoming a compliance requirement — and what it takes to re-derive any trade on any date.
Read postReading Solver Benchmarks Like an Adversary
A buyer's checklist for tearing an optimization benchmark apart — and the questions the slide was built to skip.
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GPU Computing in Quantitative Finance: A Sober Look
Where massively parallel hardware genuinely helps in finance — and where it quietly makes small problems slower.
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Quantum Optimization for Portfolios: Hype, Reality, and an Honest Roadmap
Where quantum methods might eventually help portfolio construction — and why honesty about the timeline is the credible posture.
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Risk Models Meet the Optimizer: How Factor Structure Shapes Real Portfolios
How factor structure flows into construction, and why the risk model and the optimizer have to be co-designed.
Read postMore from the library
How to Read Portfolio Optimization Benchmarks Without Being Misled
Cold starts, repeated runs, quality gaps, and why matched workloads matter more than headline speedup.
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Why Direct Indexing Needs Optimization Infrastructure, Not Just Screens
Personalized portfolios become an operations problem once taxes, lots, turnover, tracking error, and scale arrive together.
Read postWhat a Matched-Workload Pilot Should Prove
A practical checklist for evaluating any optimization engine against your current production workflow.
Read postTax-Loss Harvesting Latency Is a Product Constraint
Why harvesting quality depends on solving fast enough to evaluate lots, wash-sale risk, tracking error, and turnover together.
Read postWhen Portfolio Optimization Crosses the GPU Boundary
The practical case for GPU-native optimization once asset count, scenarios, and account batches stop fitting overnight workflows.
Read postWhat Quantum-Ready Means for Portfolio Construction
A grounded view of the research frontier for position limits, cleanup, and hard combinatorial portfolio edges.
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