API marketplace

How fast each economy's businesses and governments are investing in new capital, on one comparable screen — real gross fixed capital formation growth from the OECD's official Quarterly National Accounts as an API, live, no key. Gross fixed capital formation — investment in machinery, buildings, infrastructure and equipment — is the most cyclical and forward-looking component of GDP: firms only commit to new plant and projects when they are confident about demand, so investment turns down before recessions and surges first in recoveries. Its year-on-year change is one of the cleanest reads on the business cycle, and a swing factor that moves the currency and the capex-exposed parts of the equity market. The OECD harmonises and seasonally adjusts the real, chain-linked-volume figures so they are genuinely comparable across countries. This API serves the two growth rates people quote — quarter-on-quarter (the latest quarter's pace) and year-on-year (versus the same quarter a year earlier) — for real investment. The board endpoint ranks every economy by its year-on-year investment growth, so you can see where capex is booming and where it is collapsing. The momentum endpoint ranks by the latest quarter-on-quarter move. The country endpoint gives one economy's investment growth with a plain-language read. Each reading carries its own quarter and discontinued series are excluded, so the board is genuinely current. The capital-investment / capex cut — distinct from the headline GDP-growth board (this isolates the investment component), the consumer-demand and trade boards, the annual IMF World Economic Outlook database, and the generic multi-provider data aggregator. Figures are quarterly, in percent.

Uptime

100.0%

Latency

624ms

Subs

3,731

How fast each economy's exports and imports are growing, on one comparable screen — real trade growth from the OECD's official Quarterly National Accounts as an API, live, no key. Trade is the external engine of an economy: exports are foreign demand for what a country makes, imports are domestic demand for what the world makes, and the gap between how fast the two are growing is the net-trade contribution to GDP — a swing factor that moves the currency and the current account. Export-led economies live and die by the export number; the OECD harmonises and seasonally adjusts the real, chain-linked-volume trade flows so the figures are genuinely comparable across countries. This API serves the two growth rates people quote — quarter-on-quarter (the latest quarter's pace) and year-on-year (versus the same quarter a year earlier) — for real exports and real imports of goods and services. The board endpoint ranks every economy by its export growth, with imports alongside, so you can see whose external demand is booming and whose is fading. The imports endpoint ranks by import growth — a read on domestic demand pulling in goods. The country endpoint gives one economy's export and import growth with a plain-language read of whether net trade is improving (exports outpacing imports) or dragging. Each reading carries its own quarter and discontinued series are excluded, so the board is genuinely current. The external-sector / trade-growth cut — distinct from the headline GDP-growth board (this isolates the trade component), the annual IMF World Economic Outlook database, and the generic multi-provider data aggregator. Figures are quarterly, in percent.

Uptime

100.0%

Latency

595ms

Subs

4,390

How fast each economy is actually growing, on one comparable screen — real GDP growth from the OECD's official Quarterly National Accounts as an API, live, no key. Real GDP growth is the single most-watched macroeconomic number there is: it is the headline measure of whether an economy is expanding or in recession, it sets the backdrop for every central-bank decision, and the quarterly print moves bond, currency and equity markets. The OECD harmonises and seasonally adjusts the national accounts so the figures are genuinely comparable across countries. This API serves the two growth rates people actually quote — the quarter-on-quarter change (the latest quarter's pace) and the year-on-year change (growth versus the same quarter a year earlier), both for real, chain-linked-volume GDP. The board endpoint ranks every economy by its year-on-year growth, with the quarter-on-quarter move alongside, so you can see who is booming and who is shrinking. The momentum endpoint ranks by the latest quarter-on-quarter move — the freshest read on the cycle. The country endpoint gives one economy's GDP growth with a plain-language read (two consecutive negative quarters is the classic technical-recession marker). Each reading carries its own quarter and discontinued series are excluded, so the board is genuinely current. The headline GDP-growth cut — distinct from the annual IMF World Economic Outlook database (a yearly figure and forecast, not the live quarterly print), the leading-indicator and confidence boards (forward-looking soft data), and the generic multi-provider data aggregator. Figures are quarterly, in percent.

Uptime

66.7%

Latency

711ms

Subs

3,161

How much consumers in each economy are actually spending, and which way the high street is turning — the OECD retail trade volume as an API, live from the OECD's official statistics, no key. Retail trade volume is the headline monthly read on consumer demand: it measures the real, inflation-adjusted volume of goods sold by retailers, and its year-on-year change tells you whether households are opening their wallets or pulling back. Consumer spending is the largest part of most economies, so the retail print moves markets and feeds straight into GDP nowcasts — and the latest month-on-month move is the bit traders react to first. The OECD publishes a seasonally-adjusted retail-trade-volume index for each economy; this API turns it into the numbers people use — the year-on-year and month-on-month growth of retail sales. The board endpoint ranks every economy by its year-on-year retail growth, so you can see where consumers are spending and where demand is fading. The momentum endpoint ranks by the latest month-on-month move — who is accelerating or rolling over right now. The country endpoint gives one economy's retail growth, year-on-year and month-on-month, with a plain-language read. Each reading carries its own period and discontinued series are excluded, so the board is genuinely current. The consumer-demand / retail hard-data cut — distinct from the industrial-production board (the supply side, factory output), the leading-indicator and confidence boards (soft survey data), and the generic multi-provider data aggregator. Figures are monthly, in percent.

Uptime

100.0%

Latency

358ms

Subs

3,680

How much each economy's factories, mines and utilities are actually producing, and which way output is turning — the OECD industrial production index as an API, live from the OECD's official statistics, no key. The industrial production index is one of the headline monthly hard-data prints: it measures the real volume of output across industry (mining, manufacturing and utilities, excluding construction), and its year-on-year change is a direct read on whether the real economy is expanding or contracting — it moves markets and feeds straight into GDP nowcasts. Manufacturing, the largest and most cyclical part, is broken out separately. The OECD publishes a seasonally-adjusted production-volume index for each economy; this API turns it into the number people use — the year-on-year and month-on-month growth of industrial output. The board endpoint ranks every economy by its industrial-production growth (industry excluding construction), with manufacturing alongside, so you can see where factories are humming and where they are stalling. The manufacturing endpoint ranks by manufacturing output growth on its own. The country endpoint gives one economy's industrial and manufacturing growth, year-on-year and month-on-month. Each reading carries its own period and discontinued series are excluded, so the board is genuinely current. The industrial-output / hard-data cut — distinct from the leading-indicator and confidence boards (soft, survey-based, forward-looking), the annual IMF database, and the generic data aggregator. Figures are monthly, in percent.

Uptime

25.0%

Latency

1029ms

Subs

4,000

How fast the money in each economy is growing — narrow money (M1) and broad money (M3) growth as an API, live from the OECD's official monetary statistics, no key. The money supply is the total stock of money in circulation: M1 is cash and instantly-spendable deposits (the transactional money that turns over fast), M3 is M1 plus savings and near-money. How fast it grows is one of the oldest macro signals there is — money growth running well ahead of the economy is the classic fuel for inflation and asset-price booms, while money contracting flags a credit squeeze. Central banks, bond traders and macro investors watch the year-on-year money-growth rate to read the liquidity tide. The OECD publishes a seasonally-adjusted monetary-aggregate index for each economy; this API turns it into the number people actually use — the year-on-year and month-on-month growth of M1 and M3. The board endpoint ranks every economy by its broad-money (M3) growth, with narrow money (M1) alongside, so you can see where liquidity is expanding fastest and where it is drying up. The narrow endpoint ranks by M1 growth — narrow money turns over fastest and tends to lead. The country endpoint gives one economy's M1 and M3 growth, year-on-year and month-on-month. Each reading carries its own period and discontinued series are excluded, so the board is genuinely current. The money-supply / monetary-growth cut — distinct from the central-bank policy-rate APIs (the price of money, not its quantity), the inflation board, and the generic multi-provider data aggregator. Figures are monthly, in percent.

Uptime

25.0%

Latency

1676ms

Subs

3,926

The monthly unemployment rate of every major economy on one comparable screen — the OECD harmonised unemployment rates as an API, live from the OECD's official statistics, no key. Each country measures joblessness slightly differently; the OECD harmonises them onto the same definition (the share of the labour force without work, available and actively looking) and seasonally adjusts them, so the numbers are genuinely comparable side by side. Unemployment is one of the two hard data points — with inflation — that move central banks and markets, and the monthly print, and which way it is turning, is what gets traded. The board endpoint returns the headline (15+) seasonally-adjusted unemployment rate for every economy the OECD tracks (and the aggregates — the euro area, the OECD, the EU), ranked from the tightest labour market to the loosest, each with its month-on-month change and whether the rate is rising (loosening) or falling (tightening). The youth endpoint does the same for the 15-24 age group — youth unemployment runs far higher and is watched as a social and structural gauge. The country endpoint puts the headline and youth rate together for one economy with its rank and recent direction. Each reading carries its own period and discontinued series are excluded, so the board is genuinely current. The labour-market / unemployment-rate cut — distinct from the annual IMF World Economic Outlook database (which carries unemployment as a yearly figure and forecast, not the live monthly print), the inflation and bond-yield boards, and the generic multi-provider data aggregator. Figures are monthly, in percent of the labour force.

Uptime

100.0%

Latency

743ms

Subs

4,295

How optimistic the firms and households of each economy are right now — the OECD Business and Consumer Confidence Indicators as an API, live from the OECD's official statistics, no key. Confidence is soft data: it comes from monthly surveys asking businesses about orders, output and expectations, and consumers about their finances and the outlook, and it moves before the hard data does, which makes it one of the most-watched early reads on demand. The OECD standardises both into amplitude-adjusted indices that oscillate around 100 — above 100 means confidence is above its long-term average (optimism), below 100 means below average (pessimism) — and the direction (rising or falling) tells you whether sentiment is improving or deteriorating. The business endpoint returns the Business Confidence Indicator (BCI) for every economy the OECD tracks (and the aggregates — G7, G20, OECD, the euro area), ranked, each with its current value, month-on-month change, optimism/pessimism reading and direction. The consumer endpoint returns the Consumer Confidence Indicator (CCI) the same way. The country endpoint puts both side by side for one economy — the firm view and the household view together, with a combined read. Discontinued series are excluded and each reading carries its own period, so the board is genuinely current. The survey-based confidence / soft-data cut — distinct from the OECD composite-leading-indicator board (a different measure built to lead GDP), from the bond-yield and inflation boards, and from the generic multi-provider data aggregator. Figures are monthly; this is the sentiment lens on the world's economies.

Uptime

25.0%

Latency

906ms

Subs

4,241

Which economies are heading into expansion, slowdown, downturn or recovery — the OECD Composite Leading Indicators (CLI) as an API, live from the OECD's official statistics, no key. The CLI is designed to flag turning points in the business cycle six to nine months ahead: it leads GDP, it does not follow it. It is built to oscillate around 100 — above 100 means activity is above its long-term trend, below 100 means below trend, and the direction (rising or falling) gives the momentum. Combining level and direction gives the classic four-phase business-cycle clock macro traders position around: above 100 and rising is Expansion, above 100 and falling is Downturn, below 100 and falling is Slowdown, below 100 and rising is Recovery. The board endpoint returns every economy the OECD tracks (and the aggregates — G7, G20, OECD, NAFTA, the major European and Asian groups) with its current amplitude-adjusted CLI, the month-on-month change and its business-cycle phase, ranked. The country endpoint returns one economy's CLI — its latest reading, the month-on-month change and its phase. The phase endpoint groups every economy into the four phases of the cycle clock, so you can see at a glance who is accelerating and who is rolling over. The leading-indicator / business-cycle cut — distinct from the generic multi-provider data aggregator (which fetches any raw series but is not a curated, interpreted CLI board), from the government-bond-yield board, and from inflation and central-bank-rate APIs. Figures are monthly; this is the forward-looking macro lens.

Uptime

25.0%

Latency

1756ms

Subs

3,797

The best liquidity-pool, staking and vault yields across DeFi, with the risk profile that decides whether a headline APY is actually worth farming — live from DeFiLlama, no key. A pool can advertise 40% APY, but if it is a volatile two-token liquidity position the impermanent loss can eat the yield, and if the rate spiked yesterday it may be gone tomorrow. This API is the yield-farming screener: for every non-lending pool (DEX liquidity, staking, vaults, farms) it returns the current APY split into base and reward, the 30-day average APY, a sustained APY (the lower of the two, so a pool only scores high if it yields well both now and on average), the impermanent-loss risk and exposure (single-asset or multi-token), whether it is a stablecoin pool, the TVL and daily trading volume, and DeFiLlama's own forward prediction of whether the APY will hold, rise or fall. The pools endpoint is the full screener, filterable by project, chain, asset, stablecoin-only, exposure, IL-risk and minimum size, sorted by current or 30-day or sustained APY, TVL or volume. The best endpoint answers the question directly — the highest-yielding farms ranked by the sustained APY so the answer is real and farmable, not a one-day spike; add stablecoin=true or exposure=single for lower-risk yield. The project endpoint summarises one protocol's pools (Uniswap, Curve, Pendle, Convex). The LP / staking / vault yield-farming cut — distinct from the on-chain money-market lending-rate API (supply and borrow rates, which this one excludes entirely), from the TVL analytics APIs, and from price feeds. Ranking surfaces exclude DeFiLlama-flagged outlier pools so the best yield is one you could actually farm.

Uptime

100.0%

Latency

227ms

Subs

4,207

When locked crypto tokens vest into circulation, who they go to, and how much supply is still to come — live from DeFiLlama's open emissions dataset, no key. A token's price tells you what it costs today; its unlock schedule tells you the supply pressure ahead, the single biggest and most predictable overhang in crypto. When a large tranche of insider, private-sale or team tokens vests, it is fresh sell-side supply hitting a fixed amount of demand — and these dates are known in advance. A static "percent unlocked" number (which dilution APIs give) is only a snapshot; what a trader needs is the calendar: when is the next cliff, how many tokens, what share of total supply, and to whom. The protocols endpoint lists every token DeFiLlama tracks a schedule for (searchable). The next endpoint is the trading signal — the next upcoming cliff unlock for a token: its date, days away, token amount, the share of total supply it dilutes, the unlock type and the recipients (insiders, private sale, team, ecosystem), plus the unlocks after it. The schedule endpoint returns the fuller picture: total and max supply, the allocation by category with how much of each is already unlocked, the count of past and future events, the tokens still locked, and the upcoming events. The token-unlock / vesting-schedule cut — distinct from the tokenomics-and-dilution APIs (which give the static supply and FDV snapshot, not the dated unlock calendar) and from price and market-cap APIs. Amounts are in tokens and as a share of total supply; pair with any price API for the dollar value.

Uptime

100.0%

Latency

136ms

Subs

3,234

The supply and borrow rates of on-chain money markets, compared across every major DeFi lending protocol and chain at once — live from DeFiLlama, no key. The same asset earns and costs a different rate on every protocol and every chain: USDC might pay 3% to supply on Aave v3 Ethereum and cost a fraction to borrow somewhere else, and those rates move every block. A single protocol's reserves are only part of the picture; what a lender or borrower wants is the cross-protocol, cross-chain comparison. This API joins DeFiLlama's pool yields with its lend/borrow dataset into one money-market table: for every lending reserve it gives the supply APY (base + reward), the borrow APY (base + reward), the utilisation, the loan-to-value and the dollar size of the supplied and borrowed pools. The markets endpoint returns the full table (filter by asset, chain, protocol, stablecoin, minimum size); the best endpoint returns the top venues to supply an asset (highest APY) or to borrow it (lowest APY) right now; the asset endpoint summarises one asset across all its markets — the min, max, average and median supply and borrow APY, plus the single best place to lend and to borrow. Ranking surfaces exclude DeFiLlama-flagged outlier pools and impossible (>100%) utilisation, so the best rate is a real, harvestable one. The cross-protocol money-market-rates cut — distinct from TVL analytics (which size protocols, not their rates), single-protocol lending APIs (one venue each), and perpetual funding-rate APIs (a different rate entirely).

Uptime

100.0%

Latency

199ms

Subs

3,222

The SOFR term reference rates that actually price US dollar floating-rate loans and notes, live from the Federal Reserve Bank of New York's public markets API — no key, nothing stored. Now that LIBOR is gone, trillions of dollars of loans, FRNs and derivatives reference SOFR, but almost none of them reference the overnight SOFR fixing directly: they reference the New York Fed's compounded SOFR Averages (30-, 90- and 180-day) and the SOFR Index, the backward-looking term rates that turn the daily fixing into a usable loan rate. The rates endpoint returns the three averages, the SOFR Index value and a plain-language read of the term-average slope (with the overnight SOFR for context). The accrual endpoint is the operational one: give it a start and end date and it computes the realized compounded SOFR over that period straight from the SOFR Index — the exact arithmetic (Index_end / Index_start − 1, ACT/360) a loan servicer or FRN desk runs to settle an interest period, with the resulting rate and dollar interest. The history endpoint returns the averages and index as a daily time series. This is the SOFR term-rate / accrual cut — distinct from the overnight money-market benchmark board (the daily SOFR fixing, without the compounded averages or the index) and from the funding-spread stress monitor (the spreads between overnight rates, not the term reference rates).

Uptime

100.0%

Latency

278ms

Subs

3,683

The ratios between gold, silver, platinum and palladium, where they sit in their own multi-year history, and which metal is cheap relative to which — computed live from Yahoo Finance futures, no key, nothing stored. A precious-metal price tells you what an ounce costs; the ratio between two metals tells you which is expensive relative to the other — and these ratios are famously mean-reverting, which is why the gold/silver "mint ratio" is one of the oldest trades there is: when it stretches to an extreme, traders rotate from the dear metal into the cheap one and ride it back. A single current ratio is only half the story; what matters is where that ratio sits in its multi-year range. This API computes the gold/silver, gold/platinum, platinum/palladium, gold/palladium and silver/platinum ratios, and for each returns its current value, its percentile within a multi-year window (the context that turns a number into a signal), the window min/max/average, and a plain-language rotation read — at a high percentile the numerator metal is historically expensive (favour the denominator), at a low percentile the reverse. The ratios endpoint returns the whole complex; the ratio endpoint returns one pair with its component prices; the history endpoint returns the ratio time series. This is the precious-metal-ratio / mean-reversion cut — distinct from the inter-commodity crack/crush spread API (which gives the current gold/silver ratio but no history, percentile or signal), the intermarket-ratio board and the metals spot-price feed. It is the ratio with its history attached.

Uptime

100.0%

Latency

135ms

Subs

3,748

The shape of the commodity futures curve — contango versus backwardation — and the roll yield it pays, computed live from Yahoo Finance dated futures contracts, no key, nothing stored. A single commodity price hides the most important thing about it: what the market charges to hold it forward. When deferred contracts cost MORE than the front (an upward curve, contango) a long futures position bleeds money as it rolls up the curve each month; when they cost LESS (a downward curve, backwardation — classic for crude oil in tight markets) the roll pays you. That roll yield, not the spot move, is what drives the long-run return of commodity-index investing. This API reads the actual dated contracts — the front month and the deferred months out the curve — for crude oil, natural gas, gasoline, gold, silver, copper, corn, wheat and soybeans, and returns the full term structure, the front-to-second-month roll yield annualised, the curve shape and the front-vs-back spread. The curve endpoint returns one commodity's full chain; the screener endpoint ranks every commodity by roll yield, separating the backwardated markets (positive carry for a long) from the contango ones (negative carry). This is the commodity futures term-structure / roll-yield cut — distinct from the crypto dated-futures curve API, the inter-commodity crack/crush spread API, the commodity-momentum and seasonality APIs and the spot price feeds. It is the carry, read straight off the curve.

Uptime

100.0%

Latency

197ms

Subs

4,326

The money-market spreads that signal whether US dollar funding is calm or seizing up, computed live from the Federal Reserve Bank of New York's public rates API — no key, nothing stored. The headline overnight rates all sit within a few basis points of each other when markets are healthy; it is the spreads between them, and their spikes, that reveal stress. The most-watched is SOFR minus EFFR: SOFR is the cost of secured (collateralised, repo) borrowing and EFFR the cost of unsecured fed-funds borrowing, so when SOFR climbs above EFFR it means collateral is suddenly expensive — the classic repo-stress signal that blew out in September 2019 and around quarter-ends. This API computes that and the other key spreads — SOFR vs the Overnight Bank Funding Rate, SOFR vs the Broad General Collateral Rate, and the general-vs-tri-party collateral spread — in basis points, with a funding-stress regime read. The spreads endpoint returns the live rate board and every spread; the distribution endpoint returns SOFR's intraday percentile spread (99th minus 1st), a within-day dispersion gauge that widens when funding is segmented; the history endpoint returns the time series of any spread and counts the stress days. This is the funding-stress / money-market-spread cut — distinct from the raw NY-Fed rate-level feed (which lists the rates but not the spreads or the stress signal), the central-bank-policy and the yield-curve APIs. It is the gap between the rates, which is where the stress lives.

Uptime

100.0%

Latency

163ms

Subs

3,765

How much more volatility the options market is pricing in than the market has actually delivered — the carry that every short-volatility strategy harvests — computed live from Yahoo Finance, no key, nothing stored. Implied volatility (the VIX and its cousins) is almost always richer than the volatility that subsequently shows up: investors pay up for protection, and that gap, the variance risk premium, is one of the most persistent paid-for risks in markets. This API measures it directly across the major asset classes that publish an implied-vol index: for the S&P 500 (VIX), the Nasdaq 100 (VXN), crude oil (OVX) and gold (GVZ), it takes the live implied-vol index and subtracts the realised volatility actually delivered by the underlying over the matching ~30-day window (annualised standard deviation of daily log returns), and returns the premium in volatility points, the implied/realised ratio and a rich/cheap read. A large positive VRP means options are expensive relative to what the market has been doing (sellers are well paid); a negative VRP — implied below realised — is rare and flags that options are cheap, often during or right after a stress event. The premium endpoint returns all four markets ranked; the asset endpoint returns one market with 21- and 30-day realised legs; the history endpoint returns the VRP time series. This is the implied-minus-realised / variance-risk-premium cut for equities and commodities — distinct from the implied-vol level board (no realised leg), the realised-volatility dashboard (no implied leg) and the crypto-only DVOL/VRP API.

Uptime

100.0%

Latency

138ms

Subs

3,963

The shape of the equity volatility curve — the single most-watched regime signal in the options world — computed live from Yahoo Finance, no key, nothing stored. A VIX level tells you how scared the market is right now; the term structure tells you whether that fear is short-term panic or a calm, persistent state, and which way it is rolling. This API reads the S&P 500 implied-volatility curve across four tenors — the 9-day VIX, the headline 30-day VIX, the 3-month VIX and the 6-month VIX — and turns it into a regime. When the curve slopes up (VIX < VIX3M < VIX6M) the market is in contango: calm, with near-term vol cheaper than far, the state short-vol strategies harvest. When it inverts to backwardation (VIX above VIX3M) the front end is bid above the back: acute stress, fear spiking, historically near capitulation. The structure endpoint returns the live curve, the contango ratio (VIX / VIX3M), the short-end ratio (VIX9D / VIX), the roll yield a short-vol position would earn, the slope classification and a regime read, with VVIX (the vol of the VIX) for context. The history endpoint returns the daily time series of the contango ratio and flags every backwardation day. The percentile endpoint places today's contango ratio in its one-year range. This is the volatility term-structure / contango-backwardation cut — distinct from the cross-asset VIX-family level board, the crypto DVOL index and the realised-volatility APIs. It is the shape of fear, not its level.

Uptime

100.0%

Latency

133ms

Subs

3,276

A formal statistical test of whether a market follows a random walk, or whether its returns carry tradeable momentum or mean-reversion that is real rather than noise — the Lo-MacKinlay variance ratio test, computed live from Yahoo Finance daily closes, no key, nothing stored. Most persistence tools give you a single descriptive number; this gives you a hypothesis test with a verdict. The variance ratio compares the variance of multi-day returns to the variance of one-day returns scaled up: under a true random walk the ratio is 1 at every horizon. A ratio above 1 means returns positively autocorrelate (trends persist — momentum); below 1 means they reverse (mean-reversion). Crucially it attaches a heteroskedasticity-robust z-statistic and a p-value at each horizon, so you know whether the deviation from a random walk is statistically significant or just sampling noise — the thing a point estimate cannot tell you. The asset endpoint runs the test at horizons of 2, 4, 8 and 16 days and returns each ratio, z-statistic, p-value and a reject/fail-to-reject verdict, plus an overall read. The screener endpoint ranks the cross-asset universe by their 2-day variance ratio, separating the statistically momentum-like markets from the mean-reverting ones. This is the random-walk hypothesis-test cut — distinct from the Hurst-exponent regime API (a point estimate with no significance), the momentum and the price APIs. It is the test, with the p-value attached.

Uptime

100.0%

Latency

213ms

Subs

3,388

The two best-documented calendar anomalies in equities — the day-of-week effect and the turn-of-month effect — measured live across a cross-asset universe from Yahoo Finance daily history, no key, nothing stored. Decades of research show returns are not spread evenly through the week or the month: the turn-of-month effect — the cluster of the last trading day of a month and the first few of the next — has historically captured the bulk of the entire month's gain while the rest of the month drifts; and the day-of-week effect (the old "Monday effect" and its kin) shows some weekdays running persistently stronger than others. This API quantifies both directly. The turnofmonth endpoint splits an instrument's history into the turn-of-month window (the last trading day plus the first three of each month) versus the rest, and returns the average daily return and win-rate of each, the spread between them, and the share of the total return earned inside that handful of days. The dayofweek endpoint returns, for each weekday, the average daily return, win-rate and sample size, with the best and worst day. The screener endpoint ranks the cross-asset universe by the strength of the turn-of-month effect, so you can see where the calendar edge is biggest. This is the day-of-week / turn-of-month calendar-anomaly cut — distinct from the month-of-year seasonality APIs (equity-index, FX, commodity) and the crypto-only intraday/day-of-week seasonality API. Patterns are descriptive, not predictive.

Uptime

100.0%

Latency

336ms

Subs

4,164

Which markets are trading on abnormal volume right now — the first scan a day-trader runs to find what is "in play" — computed live from Yahoo Finance daily volume, no key, nothing stored. Price tells you where a market is; volume tells you whether anyone cares. A stock drifting on half its normal volume is noise; the same stock on three times its average is a market reacting to something — earnings, news, a breakout — and that is where the opportunity and the risk live. Relative volume (RVOL) is today's volume divided by its recent average: 1.0 is a normal day, 2.0 is double, and anything above signals unusual participation. For each instrument this API returns today's volume, its 20- and 50-day average volume, the RVOL against each, where today's volume sits as a percentile of the window, the dollar (notional) volume for liquidity, and whether volume is trending up or down. The asset endpoint returns one instrument's full volume profile; the screener endpoint ranks the universe by RVOL, putting the names trading on the most unusual volume — the ones in play — at the top. This is the relative-volume / unusual-activity cut — distinct from the bring-your-own-series volume-indicator tools (OBV, MFI), the crypto volume-by-price profile, the order-flow tape and the price APIs. It is the volume that is out of the ordinary.

Uptime

100.0%

Latency

294ms

Subs

3,956

Where each market closes inside its daily range, and what that says about who is in control into the bell, computed live from Yahoo Finance daily OHLC — no key, nothing stored. The close is the most important price of the day: a market that runs up but closes back near its low was sold into all afternoon (distribution), while one that closes on its highs has buyers in firm control (accumulation), even if the headline change is the same. The Close Location Value (CLV) captures this on a -1 to +1 scale — +1 is a close exactly on the high, -1 exactly on the low, 0 the middle of the range. This API turns it into a conviction gauge. For each instrument it returns today's CLV, the average CLV over the window (a positive average means closes persistently in the upper half — accumulation; negative means distribution), the recent 20-day CLV as the current pressure reading, the share of days that closed in the upper third versus the lower third of their range, and a plain-language read. The asset endpoint returns one instrument's full closing-strength profile; the screener endpoint ranks the cross-asset universe from strongest accumulation to heaviest distribution, so you can see where buyers are quietly winning the close. This is the close-location / accumulation-distribution-pressure cut, price-only and no volume — distinct from the candlestick-pattern API (named shapes on the last bar), the volume-indicator tools and the price feeds. It is who won the day.

Uptime

100.0%

Latency

356ms

Subs

4,737

The volatility-coiling setups breakout traders hunt, computed live from Yahoo Finance daily OHLC — no key, nothing stored. Markets do not trend or chop at random: tight-range days cluster and precede expansion, and the classic edge — Toby Crabel's NR7 (the narrowest daily range of the last seven), the inside day (a bar wholly inside the prior one) and the outside day (a bar that engulfs it) — is that a coiled spring releases. This API measures the coil and the release. For each instrument it returns today's range as a percentile of its recent range (low = contracted/coiling, high = already expanded), whether today is an NR7, NR4, inside or outside day, the average daily range, and the historical frequency of each setup. Crucially it also returns the follow-through: after an NR7, how often the next day broke the NR7 day's high or low and how often its range expanded — the base rate that tells you whether the coil is worth trading. The asset endpoint returns one instrument's full range profile; the screener endpoint ranks the universe by contraction (most coiled, lowest current range percentile — the breakout candidates) or by realised range. This is the range-contraction / NR7 breakout-setup cut — distinct from the candlestick-pattern API (named reversal/continuation shapes, not range size), the volatility dashboard (level, not the coil), and the gap and price APIs. It is the squeeze before the move.

Uptime

100.0%

Latency

344ms

Subs

4,860

The consecutive up- and down-day runs swing-traders fade, with the historical probability that a run reverses, computed live from Yahoo Finance daily closes — no key, nothing stored. "It has gone up five days in a row, it is due a pullback" is a guess until you put a number on it. This API counts every up- and down-day run in an instrument's history and measures, for each run length, how often the very next day reversed it — turning a gut feeling into a base rate. For each instrument it returns the current streak (its direction and length), the longest up and down streaks in the window, the average run length, the full distribution of run lengths, and the reversal table: after k consecutive up (or down) days, the share of times the next day went the other way, with the sample size behind each figure. If a name is currently on a streak it also returns the historical odds that tomorrow reverses it — the one number a mean-reversion trader wants. The asset endpoint returns one instrument's full streak profile; the screener endpoint ranks the universe by how stretched each is right now (current streak length), so you can see what is most extended. This is the consecutive-run / reversal-odds cut — distinct from the Hurst persistence-regime API, the multi-timeframe momentum API, the candlestick-pattern API and the price feeds. It is the runs, counted, with the odds attached.

Uptime

100.0%

Latency

327ms

Subs

3,407