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CoCI • Research Terminal Option Pricing for Speed & Risk

🔬 The Cost of Certainty Index (CoCI)

A seller’s discount-to-retail is the market price for time saved and risk removed—an option premium for a guaranteed closing. CoCI turns that trade-off into a defensible, repeatable model instead of a gut-feel discount.

CoCI • DISCOUNT TAPE
National CoCI 8–13% Price of Certainty Los Angeles 11–14% ▲ 31d saved High DOM • High Spread Miami 12–15% ▲ 32d saved Insurance / Storm Risk Philadelphia 13–16% ▲ 32d saved Slower Retail Exit Houston 14–17% ▲ 26d saved Capex / Weather Chicago 11–14% ▲ 37d saved Tax & Seasonality Atlanta 12–15% ▲ 28d saved Growth + Risk National CoCI 8–13% Price of Certainty Los Angeles 11–14% ▲ 31d saved High DOM • High Spread Miami 12–15% ▲ 32d saved Insurance / Storm Risk Philadelphia 13–16% ▲ 32d saved Slower Retail Exit Houston 14–17% ▲ 26d saved Capex / Weather Chicago 11–14% ▲ 37d saved Tax & Seasonality Atlanta 12–15% ▲ 28d saved Growth + Risk
Cost of Certainty Index — featured graphic for Local Home Buyers USA research
Featured: The market price of speed & certainty, modeled by PropTechUSA.ai.
30Days Saved (vs. DOM)
8–13%Typical Discount Band
10 daysModeled Close
↓ Fail RiskFinancing & Repair Risk
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Executive Summary

In every market cycle, sellers face a classic trade: wait for retail and maximize price, or sell quickly and minimize execution risk. The Cost of Certainty Index (CoCI) translates that decision into measurable economics. The index estimates the market price of certainty—the typical discount-to-retail (spread) buyers require to compress time-to-close and absorb failure risk.

Key takeaway: Across many metros, every 30 days you shave off the clock prices at roughly 3–6 percentage points of spread, tightening with strong neighborhood sentiment (HSS↑) and widening when anxiety signals rise (API↑).

For homeowners, this reframes a stressful choice into a practical one: How much is my time worth, given my property’s condition and the odds of a clean close?

Scenario Lab • v2025.11 Seller vs. Time & Risk

Interactive: Model Your Cost of Certainty

Tweak your timeline, condition, and market mood to see how much discount buyers may require to guarantee a fast, clean closing. Then share your scenario with a click.

Slide toward 1.0 for turnkey; toward 0 for heavy repairs, tenants, or access friction.
7–21 days = “certainty-first”; 45–90 days approximates a slower, retail-style exit.
Baseline stress: typical macro jitters and news flow.
Neutral-to-positive neighborhood story and resale confidence.
72
Certainty Premium
Balanced speed vs price
Discount Band8–13%
Offer (Low)$—
Offer (High)$—

You’re trading about 0% of headline price for ~0 days of time-savings and risk transfer to the buyer.

Copies a ready-to-share snapshot for LinkedIn, X, or email (or opens your phone’s share sheet).

Illustrative only. For a firm, inspection-light offer and a line-item net sheet, call 1-800-858-0588 or email sales@localhomebuyersusa.com.

What Drives the Discount?

The spread is not arbitrary. It’s an aggregation of tangible costs and probabilistic risks that cash buyers internalize when they commit to a compressed closing timeline. The CoCI formalizes those drivers so sellers can understand the economics behind a “quick close.”

  • Time Value & Holding Costs: Taxes, insurance, utilities, interest, opportunity cost of capital during listing and escrow.
  • Financing Failure Risk: Retail deals can fail late if financing/appraisals wobble, causing relist delay and price erosion.
  • Condition Penalty: Volatile repair scopes and access friction (tenants, debris) increase execution risk and holding time.
  • API: Stress-search growth widens near-term spreads as uncertainty lifts risk premiums.
  • HSS: Strong neighborhood sentiment tightens spreads by improving resale confidence and exit liquidity.

Spread Components & Sensitivity

Supporting visualization: spread components and sensitivity
Components that widen or tighten spreads under different conditions.

Deep Dive, Calibration & Practical Use

CoCI expresses a price for two goods: days saved and risk removed. The calculator above demonstrates how condition and local friction move the band. Calibration blends internal outcomes (observed discount and time-to-close) with metro DOM and fall-through benchmarks. API/HSS add early-move behavioral context so spreads can widen or tighten ahead of lagging indicators. Sellers use CoCI to align closing dates, weigh light prep vs. immediate cash, evaluate novation paths in strong HSS ZIPs, and maintain a rational fallback when retail risk is high.

Interpretation: In a steady metro with friendly access and average condition, shaving 30 days may price ~3–4 points. Stack a tight timeline with heavy repairs and rising anxiety, and the same 30 days may price ~5–6+ points.

Datasets & Downloads (Sample Excerpts + Integrity Hashes)

These excerpts match our schema. Full series available for non-commercial use with attribution (see License). Each download is generated client-side with a SHA-256 hash for verification.

Dataset A — Metro Benchmarks (DOM & Fall-Through)

Creators: Justin Erickson; LHBUSA Analytics & Editorial.  |  Fields: metro, dom_days, fall_through_rate.

MetroDOM (days)Fall-Through Rate
⬇️ Download CSV hash: … v2025.11.08 • rows: 7

Dataset B — CoCI Output Examples (Offer Band Samples)

Creators: Justin Erickson; LHBUSA Analytics & Editorial.  |  Fields: metro, retail_avm, condition, target_days, discount_low, discount_high, offer_low, offer_high.

MetroRetail AVMCond.Target (days)Discount BandOffer LowOffer High
⬇️ Download CSV hash: … v2025.11.08 • rows: 6

Dataset C — Signals Illustrators (API & HSS, ZIP-level synthetic)

Creators: Justin Erickson; LHBUSA Analytics & Editorial.  |  Fields: zip, api_0_100, hss_0_1 (demonstrative only, not external data).

ZIPAPIHSS
⬇️ Download CSV hash: … v2025.11.08 • rows: 10

Governance & Versioning

  • Model cadence: Quarterly review; emergency hotfix for anomalies.
  • Monitoring: Drift checks on DOM vs. observed time-to-close, fall-through variance, API/HSS stability.
  • Changes logged: Coefficients, city lists, and estimator UX updates recorded below and in dataset metadata.

Change Log

  • v2025.11.08 — Added inline TOC; Datasets A–C with CSV/JSON & hashes; schema.org for TechArticle + Dataset; hardened calculator; added featured + supporting images.
  • v2025.10.25 — Introduced interactive CoCI; added API/HSS signals explainer; initial narrative.

Beyond the Zestimate: How We Price the Human Signal

We extend retail AVMs with two early-move layers: the Anxiety Premium Index (API) from stress-search growth and the Hyperlocal Sentiment Score (HSS) from review/social text—so your offer strategy sees shifts before the MLS does.

  • API: correlates growth in stress queries with cash-buyer Discount-to-Retail (DTR).
  • HSS: summarizes neighborhood amenity sentiment to anticipate distressed-close ratios.

Signals Lab: Nationwide ZIP Estimator (API + HSS)

Estimate signals for any 5-digit US ZIP. No external calls.

Research Stream
RCI · Certainty Discount now visible as a line-item in every offer. BDI · Buyer Demand Index translates absorption into timeline guidance. FOS · Friction-to-Offer Score surfaces readiness tasks in your portal. LESI · Local Economic Stability Index monitors macro-local shocks. Anxiety Premium Index tracks hyperlocal sentiment beyond AVMs. RCI · Certainty Discount now visible as a line-item in every offer. BDI · Buyer Demand Index translates absorption into timeline guidance. FOS · Friction-to-Offer Score surfaces readiness tasks in your portal. LESI · Local Economic Stability Index monitors macro-local shocks. Anxiety Premium Index tracks hyperlocal sentiment beyond AVMs.

Research Hub — Indices, Methods & Transparency

Explore the indices and pricing rails powering Local Home Buyers USA. We don’t guess. We model — then expose the math for sellers, partners, and regulators.

PricingMethod

Unified PropTechUSA.ai Net Offer Sheet

How our indices come together into a single, seller-facing offer with transparent line-items and guardrails.

Open
IndexMarket

Buyer Demand Index (BDI)

Measures local absorption and buyer intensity to inform timelines and pricing power.

Open
IndexNovation

Partnership Value Index (PVI): Novation vs Cash

Quantifies the value unlocked by a Novation partnership relative to an as-is cash sale.

Open
IndexFriction

Closing Risk Score (FOS)

Estimates real-world hurdles to closing (ID, title, occupancy) and shows how tasks lower risk.

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IndexPricing

How We Price Risk (RCI)

Composite execution-risk score that drives the transparent Certainty Adjustment in every offer.

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IndexMarket

Local Market Transparency Score (LMTS)

Signals clarity of comps, HOA disclosures, and public data—improving expectations and timelines.

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IndexMacro-local

Local Economic Stability Index (LESI)

Macro-local health: employment, permits, inflation, delinquencies—expressed as a stability score.

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MethodsFOS

Friction-to-Offer Score (Methods)

Implementation notes and lead-gen calculator patterns for deploying FOS in production.

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IndexValue-Add

Renovation Value Index (RVI)

Models expected value from targeted repairs vs timeline risk under Novation or cash.

Open
PricingPolicy

Cost of Certainty — Pricing Time & Risk

How time-to-close and execution risk translate into a fair, transparent adjustment.

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MarketSentiment

Beyond Zestimate — Anxiety Premium (Hyperlocal Sentiment)

Captures block-level sentiment and uncertainty that drive list-to-close variance.

Open
CatalogLicense

Research Data Catalog & License

Datasets, sources, and licensing (CC BY 4.0) for transparency and reproducibility.

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