FAQ & Glossary — CB Intelligence™

CB Intelligence™ uses long-horizon data and analytical terminology to explain housing market behavior. This page provides definitions and context to help readers interpret charts, metrics, and commentary accurately.

Core Concepts

What is ZIP Intelligence™?

ZIP Intelligence™ is a long-horizon, ZIP-level market analysis framework within CB Intelligence™. It examines how housing markets have behaved across multiple cycles, with emphasis on downside risk, recovery behavior, and structural durability.

It is designed for context and expectation-setting, not price prediction.

Who is CB Intelligence™ designed for?

CB Intelligence™ is designed for:

• buyers with long holding horizons
• advisors guiding analytical clients
• decision-makers who value context over headlines

It is not designed for short-term speculation or market timing.

Methodology & Data Sources

What data does CB Intelligence™ use?

ZIP Intelligence™ and ZIP Performance Analysis™ rely on long-horizon, publicly available housing market data and structural indicators compiled from authoritative sources.

The platform prioritizes datasets that provide consistent coverage across multiple market cycles, often spanning approximately 30 to 50 years where available. This allows analysis of expansions, downturns, recoveries, and long-term behavior that shorter datasets do not capture.

CB Intelligence™ does not rely on proprietary MLS feeds, does not scrape listings, and does not use advertising-driven consumer portals. The analysis is designed to complement MLS data and local disclosures, not replace them.

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Why focus on long-horizon data instead of recent years?

Many real estate tools focus on the last 10 to 15 years of data. While useful for recent pricing context, short timeframes often capture only part of a market cycle.

By extending the analytical horizon, CB Intelligence™ makes visible:

• How markets behaved during prior downturns
• How long recoveries historically took
• How volatility differed across neighborhoods
• How holding period length affected outcomes

This context is especially important for long-term buyers, investors, and advisors setting expectations beyond the current market phase.

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How is the data analyzed?

Data is indexed and normalized to emphasize historical behavior rather than nominal price levels. This allows meaningful comparison across time and across ZIP codes without distortion from absolute price differences.

In ZIP Performance Analysis™, indexed behavior may be translated into estimated price equivalents anchored to a current price. These estimates are illustrative only and are not forecasts, appraisals, or transaction-level valuations.

Returns and volatility are calculated using standard historical methods, including year-over-year return analysis and rolling annualized return calculations.

Are forecasts or predictions used?

No. CB Intelligence™ does not forecast prices, model future scenarios, or predict returns. All analysis reflects observed historical behavior only.

The purpose is to provide context around how markets have behaved over time, not to project how they will behave in the future.

What are the limitations of the data?

Historical housing data varies by region, time period, and availability. Where direct measurement would imply false precision, proxies are used intentionally to preserve consistency and avoid over-interpretation.

All analysis is subject to historical coverage limits and aggregation constraints. Past behavior does not guarantee future results.

Does this replace MLS data or professional advice?

No. CB Intelligence™ provides historical analysis and educational context only. It does not replace MLS data, local disclosures, appraisals, or professional due diligence, and it does not constitute financial, legal, tax, or investment advice.

What types of properties does the FHFA House Price Index reflect?

The FHFA House Price Index reflects price changes for single-family homes financed with conforming mortgages purchased or guaranteed by Fannie Mae and Freddie Mac. The index uses a repeat-sales methodology to measure how prices for the same properties change over time, which helps isolate market behavior from changes in the mix of homes sold.

At the ZIP-code level, publicly available FHFA data primarily reflects single-family housing and does not fully capture condominiums, co-operatives, cash-only transactions, jumbo-loan activity, or ultra-luxury properties. As a result, the index should be understood as a long-term behavioral proxy rather than a complete census of all housing activity.

FHFA data is well suited for analyzing historical cycles, drawdowns, and recovery patterns, but it is not intended to represent current listing prices, appraisals, or the full range of property types within a market.

What is an indexed price?

An indexed price shows how values change relative to a starting point rather than displaying actual home prices.

In CB Intelligence™, prices are indexed to a base year (e.g., 1975 = 100). This allows analysis to focus on:

• growth and decline patterns
• volatility and drawdowns
• recovery behavior

Indexed prices are used to understand market behavior, not to estimate current property values.

Why doesn’t CB Intelligence™ show median home prices?

Median prices are useful for short-term market snapshots, but they can distort long-term analysis due to:

• changes in home size and quality
• shifts in the mix of homes sold
• inflation and nominal price effects

Indexed data provides a clearer view of cycle behavior over decades.

What is a drawdown?

A drawdown measures how much prices declined from a prior peak to the lowest point during a market downturn.

Drawdowns help answer:

“Historically, how much did prices fall during the worst part of a cycle?”

This is a key measure of downside risk.

How is a drawdown different from year-to-year price changes?

Year-to-year changes show short-term movement between individual periods.

Drawdowns focus on the maximum peak-to-trough decline during a full downturn cycle, which is more relevant for long-horizon buyers concerned with capital preservation and risk exposure.

What is recovery time?

Recovery time refers to how long it took prices to return to their prior peak after a downturn.

Shorter recoveries generally reduce long-term risk for patient buyers, while longer recoveries increase the importance of holding power and time horizon.

Does a drawdown mean prices won’t recover?

No.

A drawdown describes the depth of a decline, not the long-term outcome. Historical data in many ZIPs shows that prices have eventually recovered after downturns, though timing varies by cycle and economic conditions.

What are structural drivers?

Structural drivers are the underlying forces that shape how a housing market behaves over time. They help explain why a ZIP code tends to be more stable, more volatile, slower to recover, or more resilient across market cycles. Unlike short-term factors such as interest rates or market sentiment, structural drivers change slowly and tend to influence housing behavior over decades rather than months. They form the foundation beneath observed price movement.

CB Intelligence™ evaluates several long-term factors that have historically influenced downside risk and recovery behavior. These include the degree to which demand is anchored by primary residents rather than short-term investors (owner-occupant orientation), how constrained housing supply is due to land use and zoning (housing supply constraints), access to stable and diversified employment centers (employment access and demand base), the difficulty of replacing existing housing stock given land and construction costs (replacement difficulty), and the consistency of buyer characteristics across market cycles (buyer profile stability). Together, these factors help explain why some ZIP codes experience less severe downturns, steadier recoveries, and more durable long-horizon behavior than others, independent of short-term market conditions.

Structural drivers are best used to understand why a market behaves the way it does over long periods. They help buyers and advisors assess whether a ZIP code aligns with their time horizon, risk tolerance, and long-term objectives, rather than focusing on short-term price changes.

What does “owner-occupant orientation” mean?

Owner-occupant orientation refers to the proportion of homes occupied by primary residents rather than investors.

ZIPs with higher owner-occupant orientation have historically:

• experienced less forced selling during downturns
• shown steadier recovery patterns
• exhibited lower speculative volatility

This is one of the key structural stabilizers discussed in ZIP Intelligence™.

Does CB Intelligence™ predict future prices?

No.

CB Intelligence™ provides historical analysis and educational context only. It does not forecast prices or guarantee outcomes.

Future performance depends on economic conditions, policy decisions, interest rates, and buyer behavior.

How is Advisor Access different?

Public ZIP Intelligence™ provides a 30-year historical view and high-level interpretation.

Advisor Access unlocks:

• extended 31–50 year historical context
• deeper comparative risk analysis
• structural caveats and stress points
• buyer-fit nuance by holding period

Disclaimer: CB Intelligence™ provides historical analysis and educational context only. It does not constitute financial, tax, legal, or investment advice.