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Next filing · Form 10-Q · Q3 2026 · 53 days
Next filing · Form 10-Q · Q3 2026 · 53 daysAPI Update · Point-in-Time (PIT) historical commit tracking — securities and funds unifiedAPI Update · ERM3 L3 variance partition — institutional transparency releaseFactor Research · L-Star adaptive hedge depth — out-of-sample validation across ten allocator universesPart 1 · One Position, Four BetsPart 2 · Risk Structure in 13F FilingsNext filing · Form 10-Q · Q3 2026 · 53 daysAPI Update · Point-in-Time (PIT) historical commit tracking — securities and funds unifiedAPI Update · ERM3 L3 variance partition — institutional transparency releaseFactor Research · L-Star adaptive hedge depth — out-of-sample validation across ten allocator universesPart 1 · One Position, Four BetsPart 2 · Risk Structure in 13F Filings
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Latest updates

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Filings

DueNov 9
10-Q

Form 10-Q · Q3 2026

53 days · period ended Sep 30, 2026.

DueNov 16
13F-HR

Form 13F · Q3 2026

60 days · period ended Sep 30, 2026.

DueNov 30
NPORT-P

Form N-PORT · Q3 2026

74 days · period ended Sep 30, 2026.

DueFeb 16, 2027
13F-HR

Form 13F · Q4 2026

152 days · period ended Dec 31, 2026.

Filing calendar

API & product

PostedJun 24
API Update

Point-in-Time (PIT) historical commit tracking — securities and funds unified

Integrated PIT snapshot tracking across security_master (stocks) and fund master (funds). Every significant commit now surfaces as a timestamped entry with full lineage. Enables research reproducibility and audit trails for institutional allocators who need to re-run analyses at historical market snapshots. Synced across ERM3, Funds_DAG, and RiskModels platforms.

PostedJun 15
API Update

ERM3 L3 variance partition — institutional transparency release

Finalized subsector-level (L3) factor decomposition with the formal variance partition identity σ_p² = β_market² σ_market² + β_sector² σ_sector² + β_subsector² σ_subsector² + σ_residual². Aligns ERM3 reporting with GIPS / FactSet institutional standards. The Methodology page renders the identity with KaTeX alongside live variance calculators.

PostedJun 10
Factor Research

L-Star adaptive hedge depth — out-of-sample validation across ten allocator universes

Completed out-of-sample backtests on L-Star adaptive hedge selection, which chooses market / sector / subsector hedge depth automatically per position. Validated across ten distinct allocator universes (concentrated, factor-tilted, systematic, discretionary): average 18% variance reduction versus a fixed subsector hedge, with adaptive selection adding roughly 2% net execution-cost reduction. Documented in methodology note RM-2026-02.

PostedMay 20
Factor Research

Part 2 published: risk structure in 13F filings across five allocator styles

Mirrored the Medium series Part 2 on riskmodels.org — market, thematic, and stock-specific risk across Berkshire, Ackman, Lone Pine, Tiger Global, and Baupost, with explicit treatment of the 45-day 13F filing lag. Multi-row L3 attribution tables and cumulative return strips render from the shared Plotly artifact pipeline.

All updates

Filing deadlines synced May 22, 2026

Research

Managing Equity Risk via Hierarchical Orthogonal Decomposition

Methodology, empirical studies, and the One Position, Four Bets series — hierarchical orthogonal decomposition applied to positions, 13F books, and mutual-fund panels.

Research library

The One Position, Four Bets series and empirical working papers first; shorter product and methodology notes below.

Papers

Series parts and working papers — figures, samples, and replication detail.

Part 1Jan 2026

One Position, Four Bets

Turning conviction into tradeable risk: same label, different bets across AAPL/NVDA, XOM/KMI, and MAG7.

Also on Medium

Part 2Jan 2026

Risk Structure in 13F Filings

Market, thematic, and stock-specific risk across Buffett, Ackman, Lone Pine, Tiger Global, and Baupost — and what survives the 45-day filing lag.

Also on Medium

PaperNVDA visual case study · economic-profit burden + implied scenario weights

NVIDIA: The Economic-Profit Burden of an AI Bottleneck

A RiskModels.app visual case study in market-implied expectations

PaperCase window: Oct–Nov 2021 (IBM / Kyndryl)

When does a spin-off start having returns?

When-issued market mechanics, the CRSP convention, and how RiskModels incorporates spin-off pricing — the IBM/Kyndryl case

PaperApr 2020 – Apr 2026 · 9,074 funds

Cascade Hedging and the Cost of Interpretability

Subsector ETF value, joint optimization, and executable hedge layers across 9,074 US mutual funds

PaperQ1 2026 · top-AUM cohort (~313 CIKs)

RiskModels Quarterly Funds Report — Q1 2026

Top cohort holdings refresh, factor decomposition, and residual winners for the March 2026 reporting window

Paper2019-Q3 – 2025-Q4 · 114 complexes

Who got NVDA right before it became benchmark exposure?

Early ownership, active conviction, and residual attribution in U.S. mutual-fund managers, 2019–2026

Notes

Shorter explainers on API surfaces, screening, and how to read the cascade.

NoteMarketing explainer · learned L\* selector in production since June 2026

Every Position Has a Level Too

How RiskModels picks the right hedge depth automatically, per stock, per day

NoteMarketing explainer · companion to the industry-panel endpoint

The Industry Beneath the Index

Vasicek peer-β cross-sections expose what sector ETFs paper over

NoteMarketing explainer · companion to the rankings/screen endpoint

Decile One, Not Ticker by Ticker

Server-side rank screening turns the universe into one queryable cross-section

One Position, Four Bets — arc

Part 1 — The problem. Custodial reporting obscures concentration. Four names that looked diversified drew down 50%+ together in 2022. Style factors (Growth, Value) are symptoms, not drivers — subsectors are the real unit of risk.

Part 2 — The manager. The same decomposition applied to five concentrated 13F filers: how portfolio risk partitions across market, thematic, and stock-specific layers; how active structure compounds in dollars; and what survives a realistic filing lag.

RiskModels ecosystem

Research here. Reproduce through the API. Operate in the web app.

RiskModels.org stays the credibility layer: methodology, proof, and exhibits. Product links are kept contextual so the research remains the primary object.

Research

RiskModels.org

Methodology, article series, and public exhibits for institutional review.

Read the research

API

riskmodels.app

REST API, SDKs, CLI, and MCP-ready endpoints for reproducible decomposition calls.

Open API docs

Workspace

riskmodels.net

Web application surface for portfolio workflows, dashboards, and authenticated product use.

Open web app
Technical one-pagerDownload PDF

RiskModels.org

A research surface for hierarchical orthogonal decomposition, variance attribution, and allocator-grade risk measurement. Operational APIs and developer workflows live at riskmodels.app.

Subscribe to the Quarterly Attribution Review.

Research notes on risk decomposition, fund attribution, 13F filings, and benchmark structure — a few times a quarter.

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