Data & Methodology

Everything on this site is computed from public government records and licensed industry data. Rather than one feed, each page blends several kinds of input, each used for what it is best at:

Listing-market data (September 2026) — metro-, county- and ZIP-level asking-side figures: median listing price, price per square foot, days on market, active and new listings, and the share of listings with price reductions. Refreshed monthly. Listing prices describe what sellers ask.

Closed-sales data — median sale price, its year-over-year change, homes sold and the average sale-to-list ratio. Closed-sale figures describe what buyers actually paid, so the two views are labeled separately wherever both appear. They use the source’s latest settled month (July 2026): a month is used only when the source’s release came at least 28 days after that month ended, because the source revises its newest month for sales it expects to be reported late. Each figure is labeled with its own month. The median sale price is not seasonally adjusted; homes-sold counts and sale-to-list ratios are the source’s seasonally adjusted series. When a metro’s latest month is more than six months older than the settled month, the page shows n/a instead of the old figure.

Non-disclosure states — in the ten states our closed-sales source lists as non-disclosure states (Alaska, Idaho, Kansas, Louisiana, Mississippi, Missouri, Montana, New Mexico, Texas and Wyoming), where closed sale prices are not part of the public record, WealthyBud does not show, rank or score the sale-to-list ratio: in our review of the monthly metro data those ratios swing erratically, so they count as missing in the Investor Score’s heat component and show as n/a on metro pages. A metro is placed in a state by its principal city.

A long-run house price index — a quarterly, all-transactions price index published for roughly 400 large metros. From it we compute each metro's 1-, 5- and 10-year appreciation and how far its latest level sits above or below the metro's own 2000–2019 log-linear trend. Smaller markets ship without these fields.

Published fair market rents — the government's 2-bedroom fair market rent for each metro area (county rows population-weighted within a metro). From it we derive gross rental yield = 2BR rent × 12 ÷ median listing price — a gross cap-rate proxy, before taxes, insurance, vacancy and management.

Mortgage rates — the national weekly average 30-year fixed rate, shown as context and used to prefill payment scenarios.

Growth and risk statistics — public federal records aggregated to each metro: housing units permitted in the latest full year (the 1–3 year supply pipeline, also shown per 1,000 residents); net migration from tax-return records (inflow minus outflow summed across the metro's counties, so intra-metro moves cancel — filers only, so students and some retirees are undercounted); total-nonfarm employment and its year-over-year change (published for roughly 390 of our markets); and a county-level natural-hazard risk index, population-weighted per metro, with the top expected-loss hazard named. The hazard index is a relative, national-percentile measure — larger metros skew higher because more value is exposed.

Demographics — median household income, population, median gross rent and rental vacancy from the latest 5-year government survey, used for price-to-income and deal-analyzer defaults.

Where a source doesn't cover a metro, or leaves a value blank, WealthyBud stores no value rather than estimate one: the page shows n/a or leaves the figure out, and the Investor Score percentiles skip that metro for that component instead of ranking it last. Every page shows its data-as-of date, and closed-sale figures show their own month.

Every score is a percentile rank (0–100) across all covered U.S. metros — 50 means the metro is at the median of the country, not that it earned '50%' on some test. Scores are data-derived opinions for research and are not investment advice. The five subscores:

Momentum — the mean of six percentile ranks: listing-price change year-over-year (+), month-over-month (+), days-on-market change YoY (−, faster = stronger), active-inventory change YoY (−), price-reduced share of listings (−), and total-nonfarm employment change YoY (+). Where no metro employment series is published (about 550 of 949 markets) momentum stays the five-part mean.

Value — the percentile rank of minus the house-price-index deviation from the metro's own 2000–2019 log-linear trend: metros priced furthest below their own long-run trend score highest. Where income data is available, price-to-income joins this subscore as an equal-weight component.

Rental yield — the percentile rank of gross yield (published 2-bedroom fair market rent × 12 ÷ median listing price).

Supply risk — the percentile rank of active inventory versus the same month of 2019, the last normal pre-pandemic year. A high score means inventory has rebuilt far past pre-pandemic levels — more supply risk.

Market heat — the mean of up to three percentile ranks: average sale-to-list ratio (+; seasonally adjusted, and not used in the ten non-disclosure states), median days on market (−), and the pending-to-active ratio (+). A metro missing one of them is averaged over the others.

Composite Investor Score = weighted mean of the available subscores — momentum 25%, value 20%, yield 20%, supply stability (100 − supply risk) 20%, heat 15% — with weights renormalized when a subscore's source doesn't cover the metro; a composite requires at least three subscores.

Price volatility — for index-covered metros, the standard deviation of quarterly year-over-year house-price-index changes over the last 20 years (minimum 40 observations), labeled Low / Medium / High by terciles. It describes historical swing size and is display-only — it is not part of the Investor Score.

Market news — headlines on curated metro pages come from public news feeds and link to the original publisher. The one-line takeaway under them is AI-generated from those headlines only, is labeled as such, and should be checked against the linked coverage.

The investor dashboards re-rank the same metro dataset through different lenses; no dashboard introduces new data beyond the inputs above.

Cash flow — rent-covered metros ranked by gross yield (2BR fair market rent × 12 ÷ median listing price), filtered to a median list price of at least $100,000, at least 100 active listings and a yield of at least 4% to exclude thin or distressed samples. A gross screening ratio, not a pro-forma.

Undervalued / overvalued — for metros with both a long-run price index and income data, the mean of two percentile ranks: deviation from the metro's own 2000–2019 log-linear trend (further below = higher) and price-to-income (lower = higher). The 20 highest and 20 lowest blends are shown, with the formula printed on the page.

Momentum — risers are the mean of three percentile ranks (listing-price YoY +, pending-to-active +, days-on-market YoY −); coolers the mean of two (active-inventory YoY +, price-reduced share +). Metros with fewer than 100 active listings are excluded.

Supply risk — active inventory as a percentage of the same month in 2019, extremes on both ends (minimum 100 active listings).

Appreciation — house-price-index change over 1, 5 and 10 years; leaders, laggards and 10-year compounders.

Screener — an interactive table of every scored metro (median price, YoY, days on market, gross yield, price-to-income, Investor Score, volatility). The data is embedded in the page and all filtering runs in the browser; no tracking, no external requests.

Compare — the metro comparison tool puts any two scored metros side by side from the same embedded dataset, highlights the stronger reading per row, and summarizes the differences in plain English. Fully client-side.

ZIP drill-down — curated metro pages link to a ZIP-level table: every ZIP matched to the metro by place name with at least 10 active listings, ranked by median listing price. Small ZIP samples are volatile month to month.

Monthly movers — the movers page re-ranks metros (≥100 active listings) on raw month-over-month and year-over-year listing-price change and inventory change. MoM medians in small metros are noisy; the page says so.

Annual rankings — the 'Best markets of 2026' pages are point-in-time editorial cuts of the same dataset: cash flow ranks by gross yield with the cash-flow dashboard's guardrails; appreciation ranks by 5-year index change; the first-rental list requires a median price below the national metro median and blends three equal percentiles (gross yield, lower price, supply stability). Each formula is printed on its page.

Deal analyzer — the rental deal analyzer prefills each metro's median listing price, market rent (2-bedroom fair market rent, else median gross rent), effective property-tax rate (median real-estate taxes paid ÷ median home value), rental vacancy rate and the current national mortgage rate. Insurance (0.5%/yr), maintenance (1%/yr), management (8% of rent) and closing costs (3%) are labeled editable assumptions, not local data. All math runs in the browser; outputs are models, not advice or quotes.

Rate scenarios — metro pages and the deal analyzer show the principal-and-interest payment on the median-priced home (20% down, 30-year fixed) at the current national rate and one point either side. Taxes, insurance and HOA are excluded and the payment is a build-time computation, not a lender quote.

The market map — /map paints the same dataset across public cartographic boundary files (metro, county and ZIP, generalized for display, not legal use). Metro view carries all 19 metrics; the county and ZIP views recolor by listing price, YoY change, days on market, $/sqft and (county) price-cut share, loading ZIP boundaries one state at a time. Colors are quantile bins recomputed per metric across the areas that have it; clicking opens the matching market page where one exists. County and ZIP medians come from small samples and are volatile month to month. Basemap © OpenStreetMap contributors © CARTO.

Every dashboard states its thresholds in a data note, and every ranking is a data-derived opinion — not investment advice.

Scored metro pages and the comparison tool show a 12-month listing-price outlook. It is a deliberately simple, fully transparent linear blend of three of our percentile subscores — published here in full so there is no black box:

Each subscore (0–100) is first centered: z = (subscore − 50) / 50, giving a value between −1 and +1. Supply risk is inverted (z = (50 − supply_risk) / 50) because rebuilt inventory weighs on prices.

outlook = clamp(10 × (0.5 × momentum_z + 0.3 × inverted_supply_z + 0.2 × value_z), −10%, +10%) — weights renormalized when a subscore is unavailable for a metro. Labels: Rising at +2% or above, Cooling at −2% or below, otherwise Flat.

This is a heuristic model output for research context — it is not a prediction service and not investment advice. It has no error bars, no macro inputs beyond those described above, and no track record; treat it as a compact restatement of the momentum, supply and value data on the page.

Agent directories — public agent profiles collected in July 2026: recent and career sales counts, price ranges and client ratings. Sales counts can include full-team production; directories are informational, not endorsements.

Licensing requirements — compiled from each state real-estate commission's public requirements, with the regulating authority linked on every page. As an ongoing verification program, pre-license hour figures for 25 of 51 jurisdictions — Arkansas, California, Colorado, Connecticut, Delaware, the District of Columbia, Georgia, Hawaii, Iowa, Louisiana, Massachusetts, Minnesota, Mississippi, Missouri, Montana, New Jersey, New York, North Carolina, North Dakota, Oklahoma, Pennsylvania, Utah, Virginia, Washington and West Virginia — are confirmed against those primary sources to date, with the remaining states in progress.

Salaries — official U.S. government occupational wage statistics for real estate sales agents: state annual median and 90th-percentile wages from the May 2025 estimates, rounded to the nearest $1,000. Those estimates were not released for Iowa, Massachusetts and Vermont (the source marks them “Estimate not released.”), so their pages show n/a for the state figures rather than an estimate, alongside national figures labeled as national.

What is illustrative — the two sample market reports, calculator defaults and national directory rankings are demonstrations and labeled as such on-page.

Verify any figure with a local agent, MLS or the relevant authority before relying on it. Data errors? Tell us via the contact page.

Portions of market data courtesy of Realtor.com and Redfin; additional statistics from U.S. government sources.

Beyond real estate, WealthyBud publishes demonstration data for stocks, ETFs and crypto. Each figure is sourced and each score is a data-derived research opinion, not investment advice.

Stock fundamentals — revenue, earnings, margins, returns, growth and balance-sheet figures come from each company's most recent annual report (Form 10-K) filed with the U.S. Securities and Exchange Commission, retrieved from the public-domain EDGAR database, and reflect its latest completed fiscal year. Where a filing offers more than one version of a figure, the rules below say which one we use.

Net income and earnings per share — net income is the profit that belongs to the company’s own shareholders. We use the net income the 10-K attributes to the company; if it reports only profit including the share of outside (noncontrolling) owners, we subtract that share; if it reports no share for outside owners, we use its total profit; and if it reports only income available to common shareholders, we use that. Earnings per share is the diluted figure, or basic where no diluted figure is reported. Per-share figures from a 10-K filed before a later stock split are restated to today’s share count.

Dividends per share — the fiscal-year total per common share, dividends paid where reported, otherwise dividends declared. We take the 10-K’s full-year figure first. If the company reports only quarters, we add the four quarters of its fiscal year; if its full-year figure turns out to be one quarter’s rate, we add the four quarterly rates; if it reports each payment on its own date, we add the payments inside the fiscal year. Each result is checked against the total common dividends the company reports, when it reports one: dividends per share × average shares outstanding must reach at least 60% of that total for a full-year figure or four reported quarters, and fall between 75% and 134% of it for a figure built from quarterly rates or single payments. If nothing passes, a reported full-year figure (or four reported quarters) is kept with a note, since the total can include special or preferred dividends; otherwise no dividend figure is shown. Dividend yield = dividends per share ÷ the delayed share price.

Equity and debt — shareholders’ equity is the equity that belongs to the company’s shareholders, excluding outside (noncontrolling) owners. If a company reports only total equity and the outside owners’ share, we subtract that share; total equity including outside owners is used only when the company reports neither the shareholders’ figure nor that share. Return on equity = net income ÷ that equity, and return on assets = net income ÷ total assets. Long-term debt is the noncurrent amount on the balance sheet, current maturities excluded, including finance-lease obligations when the company reports them on the same line. If a company reports only its total long-term debt and the current portion, we subtract one from the other; if it reports only the total, we use the total and label it as including the current portion; a single noncurrent notes line is used when it is the company’s only one. A reported long-term-debt total below 40% of the company’s reported debt instruments covers only part of its debt and is not used. Debt-to-equity = long-term debt ÷ shareholders’ equity. Return on equity and debt-to-equity are shown only when equity is positive; otherwise the page says why.

Spin-offs and discontinued operations — revenue in a 10-K covers continuing operations only. When a year’s net income also includes discontinued operations (a business sold or spun off), net margin and the price-to-earnings ratio use income from continuing operations instead; net income, earnings per share and the returns on equity and assets stay as reported. When a company completed a spin-off after its latest fiscal year began, that year’s earnings, sales and dividends include the business it has since given away, while the share price reflects the company without it. We then do not show its price-to-earnings ratio, price-to-sales ratio or dividend yield, and its stock page names the spin-off and links the company’s filing that announced its completion. A spin-off in the first week of a fiscal year counts as at its start. The ratios return once a full fiscal year after the spin-off is reported; revenue, net income and earnings per share are shown as filed throughout.

Stock Investor Score — a percentile blend, across the covered universe, of five subscores: Growth (revenue growth over one year and three years, and earnings-per-share growth), Profitability (net, gross and operating margins), Returns on capital (return on equity and assets), Balance-sheet strength (current ratio and low debt-to-equity) and Value (low price-to-earnings and price-to-sales ratios, and dividend yield), weighted 25/25/20/15/15 and renormalized when a subscore has no inputs. Valuation metrics (market capitalization, price-to-earnings, price-to-sales, dividend yield) combine SEC fundamentals with an end-of-day, delayed market price and are labeled illustrative; prices are not real-time quotes.

ETFs — fund facts (fund name, expense ratio, index tracked and inception year) come from each issuer’s own fund page, or the fund’s SEC filing or issuer fact sheet where the page could not be read, verified on October 2, 2026; issuer names and fund categories are WealthyBud’s curated labels. Trailing price returns and volatility are computed from end-of-day price history, shown as illustrative and delayed. The return windows and the price- versus total-return distinction are described under Research articles below.

Crypto — price, market capitalization, trading volume, circulating supply and price changes come from public market-data aggregators, are delayed, and are shown for information only.

These verticals are demonstrations. Market data carries no warranty; verify any figure with the primary filing, the fund issuer or your broker before relying on it. Nothing here is investment, tax or legal advice.

The research articles combine figures computed from the datasets described on this page with statistics quoted from named primary sources. Every quoted statistic links to its source; every computed statistic states its sample size and as-of date.

Long-run stock returns use the monthly S&P Composite series compiled by Robert Shiller (monthly averages of daily closes since 1871). Total return reinvests dividends monthly: TR_t = TR_t−1 × (P_t + D_t/12) ÷ P_t−1, where D is trailing 12-month dividends. Real returns deflate by the consumer price index. Because prices are monthly averages, drawdowns, bear markets and calendar-year returns differ slightly from figures based on daily closes; each page states its definition. A bear market is a decline of at least 20% from a prior peak on this monthly series.

Sectors — S&P 500 companies are grouped by GICS sector using the holdings of the eleven index funds that each track one S&P 500 sector; company counts per sector exclude the non-equity lines those funds also hold (such as index-futures positions). Industry sub-groups use the SEC's standard industrial classification. Fundamentals come from each company's latest annual report filed with the SEC, exactly as on the stock pages. Market capitalization sums all share classes: share counts add every class a company reports, using the cover page of its latest filing when a company does not tag shares per class (Berkshire Hathaway's Class A shares are converted at 1,500 Class B shares each).

ETF statistics in the research articles report total returns computed from dividend-adjusted prices (distributions reinvested). Every return runs from the month-end close a whole number of years before the latest complete month-end to the latest daily price and is annualized over the actual days, so the one-year figure covers slightly more than twelve months and will not match an issuer’s month-end one-year return; each page states its dates. Volatility is the annualized standard deviation of the most recent complete monthly total returns, up to 60 of them (fewer for younger funds); maximum drawdown is the largest peak-to-trough fall across up to ten years of month-end values plus the latest price, so lows reached within a month are not captured; trailing yield is distributions with ex-dates in the last 365 days divided by the latest price. Expense ratios are checked against each issuer’s fund page.

The ETF hub, fund pages and the four original ETF articles (ETF Statistics, Index Fund Statistics, ETF vs. Mutual Fund Statistics, Dividend & Bond ETF Statistics) report price returns: the change in the fund’s end-of-day price, with distributions excluded, so they understate total return for funds that pay income. They use the same return windows and volatility method as above, computed on prices instead of dividend-adjusted prices, and each page labels them “price return” and states its dates. The newer research articles use total returns on the same windows.

Crypto statistics — category totals, exchange volumes and public-company holdings come from a public market-data aggregator; long-run bitcoin and ether prices are daily exchange closing prices republished by the Federal Reserve's economic-data service; network figures (hashrate, difficulty, block subsidy, fees) come from a public Bitcoin block explorer. Which tracked assets count as stablecoins follows the aggregator's own stablecoin category, not a hand-picked list.

Housing-market statistics — the research articles count each metro area once, as one record per Census metro area (CBSA): where one metro area is listed under two place names (four areas are), it is counted under its principal city and state, and the 17 curated resort and enclave records that cover a single ZIP code or county (for example Malibu, CA, ZIP 90265, and Aspen, CO, Pitkin County) are left out. The market pages and the four original housing overview articles cover all 950 tracked markets, so their totals run higher. Rankings state the minimum-listing or minimum-population guard they use.

Rent vs. buy — the monthly cost of owning the median-priced home assumes 20% down, a 30-year fixed loan at the current national average rate and the metro's effective property-tax rate; insurance, maintenance, HOA dues and tax effects are excluded. It is compared with median gross rent. It is a simplified estimate and is labeled as one on the page.

Editorial personas. The names that appear in WealthyBud bylines, reviewer lines and author cards (for example Marcus Bell or Elena Park) are WealthyBud editorial personas, not real individuals. Each persona is a consistent label for one subject area — such as metro housing markets, agent careers, equities, funds or crypto — so readers can follow a beat across pages.

Personas hold no licenses or professional credentials, and we do not attribute quotes, experience or reputation to them. Every page is produced by the WealthyBud research team, every figure is computed from the public government and industry sources cited on that page, and the methodology documents how. In structured data, articles are credited to WealthyBud as an organization.