Relative Strength Index
Momentum oscillator measuring speed and change of price movements between 0 and 100.
Request RSI, MACD, moving averages, Bollinger Bands, ADX, Ichimoku, ATR and other technical measures from one REST endpoint. Get structured values with price context, timestamps and OHLCV data — ready for dashboards, alerts, screeners and analytics workflows.
{ "symbol": "EURUSD", "indicator": "RSI_14", "timeframe": "H1", "value": 58.43, "bid": 1.08432, "ask": 1.08443, "updated_at": 1774267200, "server_time": "2026-03-23T12:00:00+00:00" }
Each indicator is returned through the same endpoint pattern, so switching from momentum to trend or volatility analysis means changing parameters — not integrating a new product.
Momentum oscillator measuring speed and change of price movements between 0 and 100.
Difference between fast and slow EMAs with a signal line and histogram.
Upper, middle, and lower bands plus bandwidth derived from price standard deviation.
Measures trend strength regardless of direction with +DI and -DI lines.
Conversion, base and leading-span A lines for trend, support and resistance.
Average of true range over the lookback period, expressing realised volatility.
The indicator reference groups the documented library into trend, momentum, volatility and volume analysis. That keeps discovery simple while the API contract stays identical across every family.
Moving averages and directional tools for identifying trend direction, structure and strength.
Oscillators for measuring momentum, overbought/oversold states and price-change intensity.
Measures of range and dispersion for understanding how widely and quickly prices are moving.
Volume-based measures for evaluating flow, participation and accumulation/distribution behavior.
The same request pattern reaches all of them. Each entry links to the endpoint documentation and to a written explanation of what the measure does.
Moving averages and directional tools for identifying trend direction, structure and strength.
Arithmetic average of closing prices over the lookback period.
Periods: 10, 20, 50, 100, 200
Weighted moving average that gives more weight to recent prices.
Periods: 10, 20, 50
Difference between fast and slow EMAs with a signal line and histogram.
Components: main, signal, histogram
Measures trend strength regardless of direction with +DI and -DI lines.
Components: adx, +di, -di
Conversion, base and leading-span A lines for trend, support and resistance.
Components: tenkan, kijun, senkou_a
Three smoothed moving averages that visualise trending vs ranging regimes.
Components: jaw, teeth, lips
Trailing stop-and-reverse indicator that flips on trend reversals.
Reduced-lag moving average that triples EMA smoothing.
Periods: 20
Twice-smoothed EMA that reacts faster to price changes.
Periods: 20
Oscillators for measuring momentum, overbought/oversold states and price-change intensity.
Momentum oscillator measuring speed and change of price movements between 0 and 100.
Periods: 14
Compares closing price to a price range over a given period.
Components: %k, %d
Measures deviation of price from its statistical mean.
Periods: 14, 20
Momentum indicator measuring overbought and oversold levels.
Periods: 14
Rate of price change over the lookback period.
Periods: 14
Identifies price exhaustion zones based on intra-bar price comparisons.
Periods: 14
Measures of range and dispersion for understanding how widely and quickly prices are moving.
Upper, middle, and lower bands plus bandwidth derived from price standard deviation.
Components: upper, middle, lower, width
Average of true range over the lookback period, expressing realised volatility.
Periods: 14, 7
Statistical measure of price dispersion around its mean.
Periods: 20
Volume-based measures for evaluating flow, participation and accumulation/distribution behavior.
Cumulative volume flow that confirms or diverges from price action.
Volume-weighted RSI measuring buying and selling pressure.
Periods: 14
Volume-based line that gauges accumulation or distribution by smart money.
Number of price changes per bar — a proxy for true volume in OTC markets.
The core request is intentionally boring: symbol, indicator, timeframe and your API key. That makes the endpoint easy to wrap in your own SDK, job runner, alert pipeline or data service.
symbol and indicator. timeframe, with H1 as the documented default. X-API-Key header. # RSI for EUR/USD on H1 curl -H "X-API-Key: YOUR_API_KEY" \ "https://tickatlas.com/v1/indicator?symbol=EURUSD&indicator=RSI_14&timeframe=H1" # same contract, different indicator curl -H "X-API-Key: YOUR_API_KEY" \ "https://tickatlas.com/v1/indicator?symbol=XAUUSD&indicator=ATR_14&timeframe=M15" # a historical series — different route, adds from/to/limit curl -H "X-API-Key: YOUR_API_KEY" \ "https://tickatlas.com/v1/indicator/history?symbol=GBPUSD&indicator=RSI_14&timeframe=H4&limit=100"
# the latest value: symbol + indicator + timeframe URL = "https://tickatlas.com/v1/indicator" H = { "X-API-Key": KEY } d = requests.get(URL, headers=H, params={ "symbol": "EURUSD", "indicator": "RSI_14", "timeframe": "H1", }).json()["data"] # the value arrives with the price context of the same read print(d["symbol"], d["indicator"], d["timeframe"], d["value"]) print(d["bid"], d["ask"], d["updated_at"], d["server_time"]) # a series is a different route — one call, weighted 5× s = requests.get(URL + "/history", headers=H, params={ "symbol": "GBPUSD", "indicator": "RSI_14", "timeframe": "H4", "limit": 100, }).json()["data"] print(s["count"], s["from"], s["to"], s["max_window_hours"]) for p in s["series"]: # [{ "time": ..., "value": ... }] print(p["time"], p["value"])
// one value per call; there is no list form on this route const res = await fetch( "https://tickatlas.com/v1/indicator?symbol=EURUSD&indicator=RSI_14&timeframe=H1", { headers: { "X-API-Key": KEY } }, ); const body = await res.json(); // a non-2xx uses the same envelope, with error in place of data if (!res.ok) throw new Error(body.error.code); // 404 also lists error.available_indicators const { data } = body; console.log(data.symbol, data.timeframe, data.indicator, data.value); console.log(data.bid, data.ask, data.updated_at, data.server_time);
The documented RSI response returns the computed value alongside the bid and ask at the moment of calculation, and the time of the data twice — updated_at as epoch seconds, server_time as ISO-8601 UTC. That is enough to judge how fresh the number is and what the spread around it was, without a second call just to establish context.
Use the same indicator endpoint on M1, M5, M15, M30, H1, H4, D1. For a series
rather than the latest value, /v1/indicator/history takes the same symbol,
indicator and timeframe plus from, to and limit,
which defaults to 500 and is then bounded per timeframe by how far back that timeframe is
retained.
The API should feel like infrastructure: predictable authentication, familiar REST semantics, structured errors and enough contextual data to reduce integration glue.
Indicator values are served from Redis, so repeated reads do not re-run the calculation. Each timeframe is held just past the interval at which our data updates it.
M1 180s · H1 900s · D1 2700s Pass your key in one request header. No custom session flow for server-to-server integrations.
X-API-Key: tk_... Indicator value, price context, timestamps and consistent error payloads are machine-readable JSON.
application/json Related endpoints add batching, screening and broader analysis without changing the integration.
/v1/multi · /v1/screener Use a single indicator when that is all you need, then expand into batching, screening, candle history or higher-level summaries as the product grows.
The indicator endpoint sits inside the broader developer API plans, so you can add related endpoints without opening a separate account or billing model.
Keep the maths and the refresh layer behind one API while your application focuses on user experience, automation and domain logic.
Compare symbols against indicator thresholds, rank conditions and surface only the instruments that match your application rules.
Populate visual components with normalized indicator values while keeping the computation layer off the frontend.
Feed structured indicator responses into rules, workflows, scheduled jobs or AI systems that need market-state features.
Practical details about the documented library, the response format, timeframes and how the endpoint fits into the rest of the platform.
The indicator reference documents four families: 9 trend indicators, 6 momentum oscillators, 3 volatility measures and 4 volume measures. Examples include SMA, EMA, MACD, ADX, Ichimoku, RSI, Stochastic, Bollinger Bands, ATR, OBV and MFI. Together those families expose 42 individually addressable series — one family can return several, as SMA does across its five periods and MACD across its main, signal and histogram components.
M1, M5, M15, M30, H1, H4, D1. H1 is the documented default when a timeframe is not supplied.
Yes, on a different route. GET /v1/indicator returns the latest value only — symbol, indicator and timeframe. Historical series come from GET /v1/indicator/history, which adds from, to and limit, returns series as [{time, value}], and carries a 5× weight while counting once against a daily quota. It is available on Starter, Pro, Enterprise and pay-as-you-go keys.
Eight fields, and that is the whole object: symbol, timeframe and indicator identify the request, value carries the result, bid and ask give the price context at calculation time, and updated_at and server_time date the data: the same instant, as epoch seconds and as ISO-8601 UTC. There is no signal classification, no OHLC block and no metadata section.
Yes. /v1/multi batches indicators across symbols — up to 50 for real-time values and 10 for historical ones — and /v1/screener filters symbols by indicator criteria.
No. TickAtlas provides market data and computed analytics for software use. It does not provide personalized investment advice, brokerage accounts, trade execution, custody of customer assets or transaction-counterparty services.
Start with one RSI request on your $2.50 of starting credit, then reuse the same integration pattern across trend, momentum, volatility and volume analytics as your product grows.