Skip to content
Research
KnowledgeVisuals
Pricing↗Open the workspace↗Get a free API key↗
.orgResearchResearch — current site.netWorkspace↗Workspace — opens riskmodels.net.appAPI↗API — opens riskmodels.app
Next filing · Form 10-Q · Q3 2026 · 56 days
Next filing · Form 10-Q · Q3 2026 · 56 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 · 56 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
Ledger
    • Cascade Hedging and the Cost of Interpretability
    • Decile One, Not Ticker by Ticker
    • Every Position Has a Level Too
    • NVIDIA: The Economic-Profit Burden of an AI Bottleneck
    • RiskModels Quarterly Funds Report — Q1 2026
    • The Industry Beneath the Index
    • When does a spin-off start having returns?
    • Who got NVDA right before it became benchmark exposure?
  • Visuals
    • Concept graph (all)
    • Public glossary
  • Methodology
    • Filing calendar
    • API use-cases
    • Pricing↗
    • About

Concept · Stock-level risk (bottom-up)

Residual

The part of a stock's return left after the factor model is removed. RiskModels emphasizes the residual as where selection skill lives.

In depth

After the orthogonal cascade strips market, sector, and subsector, what's left is the residual — the pure idiosyncratic bet, where selection skill lives. RiskModels treats the residual as the thing worth measuring, not a leftover.

Formula

ε_i = r_i − Σ_k β_ik · f_k

Compute it with the API

GET /api/metrics/{ticker}

# pip install riskmodels-py
client.get_metrics("NVDA", as_dataframe=True)["l3_residual_er"]

Full API docs ↗

In the methodology

Explained risk: variance decomposition →

Referenced by (6)

  • Every Position Has a Level Too

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

  • NVIDIA: The Economic-Profit Burden of an AI Bottleneck

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

  • Decile One, Not Ticker by Ticker

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

  • Cascade Hedging and the Cost of Interpretability

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

  • RiskModels Quarterly Funds Report — Q1 2026

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

  • Who got NVDA right before it became benchmark exposure?

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

Related concepts

Factor modelBeta (β)IdiosyncraticAlpha (α)Hedge ratioVariance decompositionReturn attribution
← Beta (β)Stock-level risk (bottom-up) · 3 / 8Idiosyncratic →
Get a free API keyRun on your portfolio

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.

By registering, you agree to receive technical factor research and API deployment logs. RM-Registry-2026. Privacy Policy.

Sign inHomePrimerWorkspaceResearchKnowledgeConceptsReviewsLedgerReferencesAboutSubscribeMethodology noteOne-pagerAPI docsWeb appContactPrivacyStatusRSS
RiskModelsResearch/Workspace/API