#cross-asset

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.

api.oanor.com/varianceratio-api

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.

api.oanor.com/calendareffects-api

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.

api.oanor.com/closestrength-api

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.

api.oanor.com/streak-api

Measures the thing that destroys portfolios: correlations that look comfortably low in calm markets but spike toward 1 exactly when the market crashes, so the diversifiers you were counting on all fall together — computed live from Yahoo Finance daily closes, no key, nothing stored. A normal full-sample correlation hides this by averaging the calm days with the crisis days; this API instead conditions on the benchmark's extremes. For each asset it returns the ordinary correlation to the benchmark, the crash correlation (measured only on the benchmark's worst days — its lower tail), the rally correlation (on its best days), and the breakdown: how much the correlation rises in a crash versus normal. A bond, gold or commodity position with a low normal correlation but a high crash correlation is a false diversifier; one whose correlation stays low or falls in the tail is a genuine hedge. The asset endpoint returns one instrument's full tail-correlation profile; the screener endpoint ranks the cross-asset universe by crash correlation, surfacing which holdings actually fail when you need them. This is the conditional / tail-correlation cut — distinct from the unconditional cross-asset, sector and FX correlation matrices (which average all days together), the up/down capture API (magnitudes, not co-movement) and the price APIs. It is correlation when it matters: in the crash.

api.oanor.com/tailcorr-api

Measures the asymmetry every allocator actually cares about: how much of a benchmark's gains an asset captures when the market rises, versus how much of its losses it suffers when the market falls — computed live from Yahoo Finance daily closes, no key, nothing stored. A single beta assumes a market moves the same up and down, but the assets worth owning do not: they participate in rallies and cushion sell-offs, and the ones to avoid do the opposite. This API splits the benchmark's history into up-days and down-days and measures each side separately. The upside capture is the asset's average gain on the benchmark's up-days relative to the benchmark (above 100 = it gains more than the market in rallies); the downside capture is the same on down-days (below 100 = it loses less in sell-offs — defensive). Their ratio, the capture ratio, is the headline: above 1 means a favourable asymmetry. It also returns the downside beta and upside beta — the asset's beta measured only on the benchmark's down- and up-days — whose gap reveals whether the asset is more exposed in crashes than in rallies. The asset endpoint returns one instrument's full asymmetry profile; the screener endpoint ranks the cross-asset universe by capture ratio, downside capture or downside beta. This is the conditional / up-down asymmetry cut — distinct from the single unconditional beta screener, the correlation matrix, and the total-risk and tail-risk APIs. It separates the up market from the down market.

api.oanor.com/capture-api

Ranks the major markets by how brutal their bad days are, computed live from Yahoo Finance daily closes — no key, nothing stored. Volatility and the Sharpe ratio assume returns are symmetric and well-behaved, but the losses that actually blow up a book live in the left tail — the rare, deep down-days a standard-deviation number smooths away. This API measures that tail directly. For each market it returns Value-at-Risk (the daily loss not exceeded on 95% / 99% of days, both the historical percentile and the normal-distribution parametric estimate), the Conditional VaR / Expected Shortfall (the average loss on the worst days, beyond VaR — how bad the bad days really are), and the shape of the return distribution: skewness (negative = crash-prone, a long left tail) and excess kurtosis (high = fat-tailed, outlier-prone). The asset endpoint returns one instrument's full tail-risk profile; the screener endpoint ranks the cross-asset universe (equities, sectors, commodities, bonds, FX and crypto; filterable by class) from the most tail-risky to the safest. This is the cross-asset distribution-tail / VaR-CVaR cut — distinct from the bring-your-own-series risk-metrics engine, the crypto-only coin risk scorecard, the drawdown-pain (Ulcer) screener and the volatility APIs. It is the left tail, measured across the whole book.

api.oanor.com/tailrisk-api

Tells you whether each market is trending, behaving like a random walk, or mean-reverting — the single most important thing to know before choosing a strategy — computed live from Yahoo Finance daily closes, no key, nothing stored. A trend-following system bleeds money in a mean-reverting market, and a fade-the-move system gets run over in a trending one; the Hurst exponent (via rescaled-range R/S analysis) measures which world you are in. A Hurst above ~0.55 means the series is persistent — moves tend to continue, so it trends and trend-following fits; near 0.5 it is a random walk with no edge either way; below ~0.45 it is anti-persistent — moves tend to reverse, so it mean-reverts and fading extremes fits. Alongside it the API returns the Kaufman Efficiency Ratio (net move divided by the total path travelled, 0 = pure noise, 1 = a perfectly straight trend), a second intuitive read on how cleanly a market is trending. The asset endpoint returns one instrument's Hurst, efficiency ratio and a regime label; the screener endpoint ranks the cross-asset universe (equities, sectors, commodities, bonds, FX and crypto; filterable by class) from most trending to most mean-reverting. This is the persistence / trend-versus-mean-reversion regime cut — distinct from the z-score stretch gauges (how far a price is from its average right now, not the structure of its moves), the multi-timeframe momentum-alignment API and the price APIs. It tells you which kind of strategy the market is paying for.

api.oanor.com/hurst-api

Ranks a cross-asset universe by how painful each market's drawdowns have been, and how much return it paid for that pain, computed live from Yahoo Finance daily closes — no key, nothing stored. Volatility treats an up-move and a down-move as equally risky, but investors only lose sleep over the downside: the depth of the fall from the last high and how long it drags on before recovering. The Ulcer Index (Peter Martin) captures exactly that — the root-mean-square of every day's percentage drawdown from the running peak, so a deep, long drawdown is penalised far more than a brief dip and a market that keeps making new highs scores near zero. From it comes the Martin ratio (the Ulcer Performance Index) — annualised excess return divided by the Ulcer Index — the return earned per unit of drawdown pain, a downside-only cousin of the Sharpe ratio. The asset endpoint returns one instrument's full pain profile: Ulcer Index, maximum, average and current drawdown, longest time underwater, the Martin ratio and the pain ratio. The screener endpoint ranks the 21-instrument universe (equities, sectors, commodities, bonds, crypto; filterable by class) by Martin ratio (best pain-adjusted return) or by Ulcer Index (smoothest ride). This is the drawdown-pain / Ulcer-Index cut — distinct from a current-drawdown monitor (a point-in-time snapshot of how far below peak each market is), the Sharpe/Sortino/Calmar screener (Calmar uses only the single worst drawdown) and the price APIs. It scores the whole shape of the pain, not one point of it.

api.oanor.com/ulcerindex-api

Ranks a cross-asset universe by beta to a benchmark, so you can see at a glance which markets amplify the benchmark's moves and which dampen or hedge them, computed live from Yahoo Finance daily closes — no key, nothing stored. Beta is the single number that says how much an asset moves for each 1% the market moves: a beta of 1.3 rises ~1.3% when the benchmark rises 1% (and falls harder when it drops), a beta near 0 is decoupled, a negative beta moves against the market (a hedge). The screener endpoint ranks the 21-instrument universe (equities, sectors, commodities, bonds, crypto; filterable by class) by beta to a chosen benchmark (the S&P 500 by default), each with its correlation and R-squared so you know how reliable the beta is. The asset endpoint returns one instrument's full beta profile against the benchmark. The dispersion endpoint returns the spread of betas across the universe — the high-beta-minus-low-beta gap, the mean beta and the share of risk-on names — a read on how much the market is rewarding risk-taking right now. This is the systematic-risk / market-sensitivity ranking cut — distinct from a bring-your-own-series CAPM/beta calculator, the total-risk Sharpe/Sortino screener, the correlation matrix and the price APIs. It ranks live assets by how much market risk they carry.

api.oanor.com/betadispersion-api

Ranks a cross-asset universe by how much return each asset delivers per unit of risk, live from Yahoo Finance daily closes — no key, nothing stored. A raw return tells you nothing about how much risk you took to earn it: two assets up 12% are not equal if one rode a calm trend and the other whipsawed through deep drawdowns. This screener turns each asset's price history into the three risk-adjusted ratios allocators actually rank on — the Sharpe ratio (excess return per unit of total volatility), the Sortino ratio (excess return per unit of downside volatility only), and the Calmar ratio (annualised return per unit of worst peak-to-trough drawdown) — and sorts the whole universe (21 instruments across equities, sectors, commodities, bonds and crypto) so you can see in one call which markets pay the most for the risk you bear. The screener endpoint ranks the universe (filterable by asset class) by the metric you choose; the asset endpoint returns one instrument's full risk-adjusted profile with plain-language reads. This is the risk-adjusted-return / reward-per-risk ranking cut — distinct from a bring-your-own-series Markowitz optimiser, the CAPM/beta calculator, the momentum and the price APIs. It ranks live assets by efficiency, not raw performance.

api.oanor.com/riskadjusted-api

Which markets are breaking out of their volatility-adjusted trend channel, computed live from Yahoo Finance (no key, nothing stored). Keltner Channels wrap a 20-day exponential average in bands set at two Average-True-Ranges above and below it — and unlike Bollinger Bands, whose width is statistical standard deviation, Keltner's width is the market's actual trading range. A close above the upper Keltner band is a trend-following breakout (riding strength), below the lower a breakdown, and price hugging a band signals a powerful, persistent trend. For a cross-asset, cross-sector universe — equity indices and sectors, gold, oil, commodities, bonds and crypto — this computes each asset's Keltner upper, middle and lower bands, where price sits inside the channel, and flags fresh breakouts. The screener endpoint returns the upside and downside Keltner breakouts across the board. The asset endpoint returns one market's Keltner card. The universe endpoint lists what is covered. The cross-asset Keltner-channel / volatility-trend screener cut — distinct from the Bollinger-Bands screener (standard-deviation width, mean-reversion), the bring-your-own-candle ATR API and the other indicator screeners.

api.oanor.com/keltner-api

Which markets are stretched to an overbought or oversold extreme on the Commodity Channel Index, computed live from Yahoo Finance (no key, nothing stored). The CCI measures how far price has run from its statistical average relative to normal volatility: above +100 a market is in a strong up-move (and, when it unwinds, overbought), below -100 a strong down-move (or oversold), and the swing through zero frames trend and reversal trades. For a cross-asset, cross-sector universe — equity indices and sectors, gold, oil, commodities, bonds and crypto — this computes each asset's 20-period CCI from its typical price (high+low+close over three) and tags it overbought, bullish, bearish or oversold, then ranks the whole board. The screener endpoint returns the overbought (>+100) and oversold (<-100) markets right now. The asset endpoint returns one market's CCI card. The universe endpoint lists what is covered. The cross-asset CCI / extension screener cut — distinct from the bring-your-own-candle oscillator API, the RSI screener (a different oscillator), the OBV/volume and Bollinger screeners. It finds the over-extended markets across every asset class at once.

api.oanor.com/cci-api

Which markets are under accumulation or distribution and where volume is surging, computed live from Yahoo Finance (no key, nothing stored). Price tells you what is happening; volume tells you whether to believe it. On-Balance Volume adds the day's volume when a market closes up and subtracts it when it closes down, so a rising OBV means buyers are in control (accumulation) and a falling OBV means sellers are (distribution) — and a divergence between OBV and price is an early warning of a turn. A volume surge — today's volume well above its recent average — flags conviction behind a move. For a cross-asset, cross-sector universe — equity indices and sectors, gold, oil, commodities, bonds and crypto — this computes each asset's OBV trend over the last month, its latest volume versus the 20-day average, and tags it accumulation, distribution or neutral. The screener endpoint returns the markets under accumulation and distribution and the ones with a volume surge. The asset endpoint returns one market's OBV/volume card. The universe endpoint lists what is covered. The cross-asset volume / OBV screener cut — distinct from the bring-your-own-candle volume-indicator API and the crypto volume-profile API; it adds the volume dimension the price-only screeners miss.

api.oanor.com/obv-api

Whether each market is trending the same way across every timeframe, computed live from Yahoo Finance (no key, nothing stored). A single week's move is noise; what trend traders want is alignment — when the 1-week, 1-month, 3-month, 6-month and 1-year returns all point the same direction, that is a strong, coherent trend, and when they disagree the move is choppy or turning. For a cross-asset, cross-sector universe — equity indices and sectors, gold, oil, commodities, bonds and crypto — this measures each asset's return over those five horizons, the up/down direction of each, and an alignment score from -5 (every timeframe down) to +5 (every timeframe up), with a coherence label. The screener endpoint returns the fully aligned uptrends and downtrends across the board, ranked by alignment. The asset endpoint returns one market's multi-timeframe momentum card. The universe endpoint lists what is covered. The cross-asset multi-timeframe momentum / alignment cut — distinct from the crypto-only multi-timeframe API, the commodity-momentum ranking and the relative-strength APIs. It finds the coherent trends across every asset class at once.

api.oanor.com/multiassetmomentum-api

Which markets are strongly trending and which are stuck going nowhere, computed live from Yahoo Finance (no key, nothing stored). The Average Directional Index is the definitive measure of trend STRENGTH (not direction): above 25 a market has a real trend worth riding, below 20 it is choppy and range-bound where trend systems get whipsawed. The companion +DI and -DI lines give the direction — +DI over -DI is an uptrend, the reverse a downtrend. For a cross-asset, cross-sector universe — equity indices and sectors, gold, oil, commodities, bonds and crypto — this computes each asset's 14-day ADX, +DI and -DI (Wilder's method), and classifies it as a strong uptrend, strong downtrend, developing trend or ranging. The screener endpoint returns the strong uptrends and downtrends across the board, ranked by ADX, plus the ranging list. The asset endpoint returns one market's directional-movement card. The universe endpoint lists what is covered. The cross-asset ADX / trend-strength screener cut — distinct from the bring-your-own-candle trend-indicator API and the moving-average, RSI, MACD, Bollinger and Donchian screeners. It separates the trending markets from the chop across every asset class at once.

api.oanor.com/adxscreener-api

Which markets just printed a reversal or continuation candlestick pattern on their latest daily candle, computed live from Yahoo Finance (no key, nothing stored). Candlestick patterns are the oldest price-action signals there are: a hammer at a low hints a bounce, a shooting star at a high a turn, an engulfing candle a momentum shift. For a cross-asset, cross-sector universe — equity indices and sectors, gold, oil, commodities, bonds and crypto — this reads each asset's most recent candles and detects the classic single- and two-candle patterns (doji, hammer, inverted hammer, shooting star, hanging man, bullish/bearish engulfing, bullish/bearish harami, marubozu), tagging each bullish, bearish or neutral. The screener endpoint returns every market flashing a pattern right now, split into bullish and bearish signals. The asset endpoint returns one market's latest candle with any pattern detected on it. The patterns endpoint lists what is recognised. The cross-asset candlestick-pattern screener cut — distinct from the crypto-only pattern detector and the bring-your-own-candle pattern API. It scans the whole market for price-action signals at once.

api.oanor.com/candlestickscreener-api

Which markets are breaking out of their recent trading range, computed live from Yahoo Finance (no key, nothing stored). The Donchian channel — the highest high and lowest low of the last N days — is the breakout system the legendary Turtle traders rode: a close above the 20-day high is a classic long entry, below the 20-day low a short, and the 55-day channel is the slower, higher-conviction version. For a cross-asset, cross-sector universe — equity indices and sectors, gold, oil, commodities, bonds and crypto — this computes each asset's 20-day and 55-day Donchian channels (upper, lower and midline), where price sits inside the 20-day channel, and flags fresh breakouts above the high or below the low. The screener endpoint returns the upside and downside breakouts across the board plus the channel-position ranking. The asset endpoint returns one market's Donchian card. The universe endpoint lists what is covered. The cross-asset Donchian / channel-breakout (Turtle) screener cut — distinct from the crypto-only Donchian screener, the 52-week-range screener (a much longer window), the Bollinger-Bands screener and the bring-your-own-candle indicator APIs. It catches the range breakouts across every asset class at once.

api.oanor.com/donchian-api

Which markets just triggered a MACD buy or sell signal, computed live from Yahoo Finance (no key, nothing stored). The MACD — the gap between a fast and a slow moving average, smoothed by a signal line — is the workhorse momentum indicator: when the MACD line crosses up through its signal line it is a bullish trigger, down through it bearish, and the histogram between them shows momentum building or fading. For a cross-asset, cross-sector universe — equity indices and sectors, gold, oil, commodities, bonds and crypto — this computes each asset's MACD (12/26 EMA), signal line (9 EMA) and histogram, flags whether it is in a bullish or bearish posture, and detects how recently the lines crossed. The screener endpoint returns the fresh bullish and bearish crossovers across the board plus the histogram ranking. The asset endpoint returns one market's MACD card. The universe endpoint lists what is covered. The cross-asset MACD / momentum-crossover screener cut — distinct from the bring-your-own-candle technical-indicator APIs, the RSI, Bollinger and moving-average screeners and the FX-only signals API. It finds the fresh momentum triggers across every asset class at once.

api.oanor.com/macd-api

Which markets are overbought and which are oversold, ranked, computed live from Yahoo Finance (no key, nothing stored). The Relative Strength Index is the most-watched momentum oscillator: above 70 a market is overbought and stretched, below 30 oversold and ripe for a bounce, and the swing between them frames most mean-reversion trades. For a cross-asset, cross-sector universe — equity indices and sectors, gold, oil, commodities, bonds and crypto — this computes each asset's 14-day RSI (Wilder's method) and its 14-day Stochastic %K, tags it overbought / neutral / oversold, and ranks the whole board. The screener endpoint returns the markets that are overbought and oversold right now, sorted from hottest to coldest. The asset endpoint returns one market's oscillator card. The universe endpoint lists what is covered. The cross-asset RSI / oscillator screener cut — distinct from the crypto-only RSI screener, the bring-your-own-candle oscillator and technical-indicator APIs and the Bollinger and moving-average screeners. It finds the stretched markets across every asset class at once.

api.oanor.com/rsiscreener-api

Which markets are coiled for a breakout and which are stretched to their bands, computed live from Yahoo Finance (no key, nothing stored). Bollinger Bands wrap a 20-day average in plus/minus two standard deviations; price riding the upper band is strong, the lower band weak, and — the prized signal — when the bands pinch tight (a "squeeze"), volatility has compressed and a big move usually follows. For a cross-asset, cross-sector universe — equity indices and sectors, gold, oil, commodities, bonds and crypto — this computes each asset's bands, its %B (where price sits between the lower band at 0 and the upper at 100), the bandwidth and whether bandwidth is at a multi-month low (a squeeze, breakout pending). The screener endpoint returns the board with the markets in a squeeze, the ones breaking above the upper band and the ones breaking below the lower. The asset endpoint returns one market's Bollinger card. The universe endpoint lists what is covered. The Bollinger Bands / volatility-squeeze screener cut — distinct from the bring-your-own-candle technical-indicator APIs, the FX-only z-score API and the market-breadth API. It finds the coiled springs across the whole market.

api.oanor.com/bollinger-api

Which markets just flipped trend on the most-watched signal in technical analysis — the 50-day vs 200-day moving-average cross — computed live from Yahoo Finance (no key, nothing stored). A golden cross, the 50-day average crossing up through the 200-day, is the classic confirmation of a new uptrend, and a death cross the opposite; funds and headlines move on them. For a cross-asset, cross-sector universe — equity indices and sectors, gold, oil, commodities, bonds and crypto — this computes each asset's 50- and 200-day moving averages, whether it is in a golden-cross (bullish) or death-cross (bearish) regime, how many days since the last cross, and how far price sits above or below each average. The screener endpoint returns the whole board with the markets that have crossed most recently — the fresh golden and death crosses — and the bullish/bearish tally. The asset endpoint returns one market's moving-average card. The universe endpoint lists what is covered. The moving-average-crossover / golden-cross screener cut — distinct from the bring-your-own-candle technical-indicator APIs, the market-breadth API (which aggregates the share above a single moving average) and the FX-only signals API.

api.oanor.com/goldencross-api

Which markets are beating the benchmark and which are lagging, ranked, computed live from Yahoo Finance (no key, nothing stored). Relative strength is the engine of rotation: money flows toward what is outperforming, and the leaders of one quarter often lead the next. For a cross-asset, cross-sector universe — the eleven S&P 500 sectors plus small caps, international and emerging equities, gold, oil, commodities, bonds and crypto — this measures each asset's return MINUS the S&P 500's over one, three and six months, blends them into a relative-strength score, and ranks the whole board into leaders and laggards. A positive score means the asset is beating the market; a negative one means it is lagging. The ranking endpoint returns that ranked board with the benchmark's own return and the standout leaders and laggards. The asset endpoint returns one market's relative strength across each window, its beta to the S&P 500 and whether its relative strength is improving or fading. The universe endpoint lists what is covered. The relative-strength / market-leadership rotation cut — distinct from the absolute-momentum, the sector-correlation and the altcoin-season APIs. It answers what is leading the market, measured against it.

api.oanor.com/relativestrength-api

How far every major market is below its peak and how long it has been underwater, computed live from Yahoo Finance (no key, nothing stored). Drawdown is the risk investors actually feel: not volatility in the abstract, but the gap between today's price and the high-water mark, and the painful stretch spent climbing back. For every asset — equity indices, bonds, gold, oil, commodities, FX and crypto — this measures the current drawdown from its rolling peak, the worst (maximum) drawdown over the window, the date and level of the peak, how many days it has been underwater, and how much of the fall it has already recovered. The monitor endpoint returns the whole universe ranked by current drawdown — what is deepest underwater and what is back at new highs — with a summary of how many markets are in drawdown. The asset endpoint returns one market's drawdown card. The universe endpoint lists what is covered. The cross-asset drawdown / underwater-recovery cut — distinct from the FX-only drawdown API, the crypto all-time-high API and the cross-asset volatility API (which ranks risk-adjusted return, not the underwater curve). It answers how far from the highs, and how long.

api.oanor.com/assetdrawdown-api

The risk dashboard for the whole multi-asset book — how volatile each asset class is, how much it returned, and how much return it paid per unit of risk, computed live from Yahoo Finance (no key, nothing stored). Return without risk is meaningless; this puts them side by side. For every instrument — equities, bonds, gold, oil, commodities, FX and crypto — it measures the annualised realised volatility (the standard deviation of daily returns, the market's fear gauge), the trailing return, a Sharpe-style risk-adjusted return (return per unit of volatility) and the worst peak-to-trough drawdown over the window. The ranking endpoint returns the universe ranked by whichever you choose — volatility, Sharpe, return or drawdown — so you can see the calmest and wildest assets and who paid the best risk-adjusted return. The asset endpoint returns one instrument's full risk profile. The universe endpoint lists what is covered. The cross-asset volatility / risk-adjusted-return ranking cut — distinct from the crypto-only volatility and risk APIs, the FX-only volatility API and the bring-your-own-series risk-metrics, CAPM and portfolio-optimiser calculators. It ranks live risk across asset classes.

api.oanor.com/assetvolatility-api

Where every major asset sits in its one-year range — across stocks, indices, bonds, commodities, FX and crypto — computed live from Yahoo Finance (no key, nothing stored). The 52-week high/low is the single most-watched level in markets: assets breaking to new 52-week highs are in confirmed uptrends and chased by momentum, while new 52-week lows mark capitulation, and the "new highs / new lows" list is a classic breadth and momentum read. This places each instrument in its range as a 0-100 position (0 = sitting on its 52-week low, 100 = at its 52-week high), with how far it is below the high and above the low, and flags fresh new highs and new lows. The screener endpoint returns the whole multi-asset universe ranked by range position — what is breaking out at the top and breaking down at the bottom — plus the new-high and new-low lists. The asset endpoint drills into one instrument. The universe endpoint lists what is covered. The 52-week-range / new-highs-new-lows momentum cut across asset classes — distinct from the crypto Donchian-breakout screener (crypto only) and the single-quote, index, commodity and stock price feeds, which carry the 52-week high/low as a field but do not rank it across a multi-asset book.

api.oanor.com/fiftytwoweek-api

How the major asset classes move together — a live correlation matrix across stocks, bonds, gold, oil, crypto and the dollar (no key, nothing stored). Correlation is the single most important input to diversification and risk: two assets with a correlation near 1 are effectively the same bet, while a low or negative correlation is genuine diversification. Where a crypto-correlation API stays inside crypto and an FX-correlation API stays inside currencies, this spans the whole multi-asset book at once — US and international equities, Treasuries and credit, gold, silver, oil and broad commodities, Bitcoin and Ether, the dollar and real estate — so an allocator can see in one call whether bonds are still hedging stocks, whether gold is decoupled and whether crypto is trading as a risk asset. The matrix endpoint returns the full pairwise return-correlation matrix over a chosen window, with the most- and least-correlated pairs. The asset endpoint returns one asset's correlation to every other, ranked, so you see its best diversifiers at a glance. The assets endpoint lists what is covered. The cross-asset / multi-asset correlation surface — distinct from the crypto-only correlation API, the FX-only currency-correlation API and the bring-your-own-series CAPM, risk-metrics and portfolio-optimiser calculators.

api.oanor.com/crossassetcorrelation-api

One number for the market's mood across asset classes — a live 0-100 risk-on / risk-off (RORO) score, computed from Yahoo Finance (no key, nothing stored). On any day capital is either reaching for risk or fleeing to safety, and the signal lives in the relationships between markets, not any single price. This blends four classic cross-asset gauges — stocks vs long bonds (SPY/TLT), high-yield vs investment-grade credit (HYG/LQD), copper vs gold (the growth metal vs the haven) and the VIX (inverted) — into one score: high = risk-on (greed), low = risk-off (fear). The score endpoint returns the composite, each gauge's contribution and a regime label; the components endpoint returns the four underlying ratios with where each sits in its recent range (its percentile), so you can see what is driving the mood. The cross-asset risk-sentiment / RORO composite cut — distinct from the intermarket-ratios feed (raw ratios), the volatility-index API and the price APIs. It synthesises the regime, not the parts.

api.oanor.com/riskappetite-api

Whether crypto is trading as a risk asset or a hedge, measured by how closely a coin moves with the stock market, gold and the dollar — computed live from Binance and Yahoo Finance, no key, nothing stored. The single most-asked macro question about crypto is whether it is "digital gold" or just high-beta tech; this answers it with numbers. The correlation endpoint returns, for a coin (BTC or ETH), its return correlation to the S&P 500, the Nasdaq 100, gold and the US dollar index over a chosen window, each with a plain-language read (risk-on if it tracks stocks, a hedge if it tracks gold or moves against the dollar) and an overall verdict. The beta endpoint returns the coin's beta to the S&P 500 — how much it amplifies equity moves — with the correlation and R-squared. This is the cross-asset / crypto-versus-traditional-markets correlation cut — distinct from the crypto-to-crypto correlation API (coins against each other), the realised-volatility and the price APIs in the catalogue. Correlations use daily log returns aligned on common trading days; coin is BTC or ETH, window 20-365 days.

api.oanor.com/cryptomacro-api

Live cross-asset prices from Pyth, the largest decentralised first-party oracle, which aggregates prices contributed by exchanges, market makers and trading firms and serves them across 90+ blockchains. Pyth covers far more than crypto: around 3,000 feeds spanning crypto, US and global equities, FX pairs, commodities and precious metals. The feeds endpoint searches the feed registry by symbol or asset type; the price endpoint returns one feed's latest aggregate price with its confidence interval, exponent, EMA price and publish time; the prices endpoint returns many feeds at once. Each price carries a confidence band — Pyth's signature measure of how tightly publishers agree. Read live from Pyth, nothing stored. This is Pyth's own multi-asset first-party oracle layer — distinct from single-DEX oracles and single-asset-class price feeds.

api.oanor.com/pyth-api