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Trend & Moving Averages Indicators for Crypto Trading
24 trend & moving averages indicators, from the AlgoBrain wiki. Direction and strength of the trend: moving averages and crosses, ADX, Ichimoku and channels. Each lists what it measures, the strategies that use it, the Crypto Data API endpoints that serve it or its inputs, and a prompt for an AI agent to compute it. All of them are in the API: GET /api/v1/indicators/catalog?group=trend-moving-averages.
Compute the 200-Day Moving Average for BTC, ETH and SOL using the CryptoDataAPI (X-API-Key header).
1. Definition and parameters: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/concepts/indicators/200-day-ma.md
2. Inputs:
- GET https://cryptodataapi.com/api/v1/indicators/technical
- GET https://cryptodataapi.com/api/v1/indicators/signum-rgg
- GET https://cryptodataapi.com/api/v1/hyperliquid/candles
3. Pinned: 4h bars, 500-bar lookback, the playbook's default parameters. Return the latest value, its 30-day percentile, and a one-line read of what it says now. Research only.
Adaptive Moving AverageAdvanced Moving AveragesAMALow-Lag Moving AveragesMoving Average Taxonomy
Every moving average faces the same trade-off: smoothing requires averaging over history, and averaging over history introduces lag. An SMA of period n sits, on a linear trend, roughly (n−1)/2 bars behind price.
Via API/api/v1/indicators/catalog/adaptive-moving-averages
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Compute the Adaptive Moving Averages for BTC, ETH and SOL using the CryptoDataAPI (X-API-Key header).
1. Definition and parameters: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/concepts/indicators/adaptive-moving-averages.md
2. Inputs:
- GET https://cryptodataapi.com/api/v1/indicators/technical
- GET https://cryptodataapi.com/api/v1/indicators/signum-rgg
- GET https://cryptodataapi.com/api/v1/hyperliquid/candles
3. Pinned: 4h bars, 500-bar lookback, the playbook's default parameters. Return the latest value, its 30-day percentile, and a one-line read of what it says now. Research only.
ALMAArnaud Legoux Moving AverageGaussian Offset Moving Average
The Arnaud Legoux Moving Average (ALMA) applies Gaussian weights to a fixed lookback window, but shifts the peak of the Gaussian away from the centre of the window and toward the most recent bar.
Used byA building block; no catalogue strategy declares it directly.
Compute the ALMA (Arnaud Legoux Moving Average) for BTC, ETH and SOL using the CryptoDataAPI (X-API-Key header).
1. Definition and parameters: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/concepts/indicators/alma.md
2. Inputs:
- GET https://cryptodataapi.com/api/v1/indicators/technical
- GET https://cryptodataapi.com/api/v1/indicators/signum-rgg
- GET https://cryptodataapi.com/api/v1/hyperliquid/candles
3. Pinned: 4h bars, 500-bar lookback, the playbook's default parameters. Return the latest value, its 30-day percentile, and a one-line read of what it says now. Research only.
The Average Directional Index (ADX) is a technical indicator developed by J. Welles Wilder that measures the strength of a trend, regardless of its direction.
Compute the Average Directional Index (ADX) for BTC, ETH and SOL using the CryptoDataAPI (X-API-Key header).
1. Definition and parameters: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/concepts/indicators/adx.md
2. Inputs:
- GET https://cryptodataapi.com/api/v1/indicators/technical
- GET https://cryptodataapi.com/api/v1/indicators/signum-rgg
- GET https://cryptodataapi.com/api/v1/hyperliquid/candles
3. Pinned: 4h bars, 500-bar lookback, the playbook's default parameters. Return the latest value, its 30-day percentile, and a one-line read of what it says now. Research only.
A death cross occurs when a shorter-term moving average — most commonly the 50-day simple moving average — crosses below a longer-term moving average, typically the 200-day SMA, signalling a potential shift from a bullish to a bearish trend.
Used byA building block; no catalogue strategy declares it directly.
Compute the Death Cross for BTC, ETH and SOL using the CryptoDataAPI (X-API-Key header).
1. Definition and parameters: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/concepts/indicators/death-cross.md
2. Inputs:
- GET https://cryptodataapi.com/api/v1/indicators/technical
- GET https://cryptodataapi.com/api/v1/indicators/signum-rgg
- GET https://cryptodataapi.com/api/v1/hyperliquid/candles
3. Pinned: 4h bars, 500-bar lookback, the playbook's default parameters. Return the latest value, its 30-day percentile, and a one-line read of what it says now. Research only.
Donchian Channels plot the highest high and lowest low over the last N periods, creating a price envelope that identifies breakout levels. Created by Richard Donchian in the 1950s–1960s, often called the "father of trend following" (Source: 2026 04 20 comprehensive guide technical trading indicators).
Via API/api/v1/indicators/catalog/donchian-channels
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Compute the Donchian Channels for BTC, ETH and SOL using the CryptoDataAPI (X-API-Key header).
1. Definition and parameters: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/concepts/indicators/donchian-channels.md
2. Inputs:
- GET https://cryptodataapi.com/api/v1/indicators/technical
- GET https://cryptodataapi.com/api/v1/indicators/signum-rgg
- GET https://cryptodataapi.com/api/v1/hyperliquid/candles
3. Pinned: 4h bars, 500-bar lookback, the playbook's default parameters. Return the latest value, its 30-day percentile, and a one-line read of what it says now. Research only.
The Exponential Moving Average (EMA) is a type of moving average that applies exponentially decreasing weights to older prices, giving the most recent data the greatest influence. This makes the EMA more responsive to new price changes than the SMA, which weights all periods equally.
Via API/api/v1/indicators/catalog/exponential-moving-average
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Compute the Exponential Moving Average for BTC, ETH and SOL using the CryptoDataAPI (X-API-Key header).
1. Definition and parameters: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/concepts/indicators/exponential-moving-average.md
2. Inputs:
- GET https://cryptodataapi.com/api/v1/indicators/technical
- GET https://cryptodataapi.com/api/v1/indicators/signum-rgg
- GET https://cryptodataapi.com/api/v1/hyperliquid/candles
3. Pinned: 4h bars, 500-bar lookback, the playbook's default parameters. Return the latest value, its 30-day percentile, and a one-line read of what it says now. Research only.
Compute the Golden Cross for BTC, ETH and SOL using the CryptoDataAPI (X-API-Key header).
1. Definition and parameters: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/concepts/indicators/golden-cross.md
2. Inputs:
- GET https://cryptodataapi.com/api/v1/indicators/technical
- GET https://cryptodataapi.com/api/v1/indicators/signum-rgg
- GET https://cryptodataapi.com/api/v1/hyperliquid/candles
3. Pinned: 4h bars, 500-bar lookback, the playbook's default parameters. Return the latest value, its 30-day percentile, and a one-line read of what it says now. Research only.
Compute the HalfTrend for BTC, ETH and SOL using the CryptoDataAPI (X-API-Key header).
1. Definition and parameters: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/concepts/indicators/halftrend.md
2. Inputs:
- GET https://cryptodataapi.com/api/v1/indicators/technical
- GET https://cryptodataapi.com/api/v1/indicators/signum-rgg
- GET https://cryptodataapi.com/api/v1/hyperliquid/candles
3. Pinned: 4h bars, 500-bar lookback, the playbook's default parameters. Return the latest value, its 30-day percentile, and a one-line read of what it says now. Research only.
The Hull Moving Average, developed by Alan Hull in 2005, combines three weighted moving averages so that the lag of one cancels the lag of another, then re-smooths the noisy result with a short final pass.
Used byA building block; no catalogue strategy declares it directly.
Via API/api/v1/indicators/catalog/hull-moving-average
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Compute the Hull Moving Average (HMA) for BTC, ETH and SOL using the CryptoDataAPI (X-API-Key header).
1. Definition and parameters: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/concepts/indicators/hull-moving-average.md
2. Inputs:
- GET https://cryptodataapi.com/api/v1/indicators/technical
- GET https://cryptodataapi.com/api/v1/indicators/signum-rgg
- GET https://cryptodataapi.com/api/v1/hyperliquid/candles
3. Pinned: 4h bars, 500-bar lookback, the playbook's default parameters. Return the latest value, its 30-day percentile, and a one-line read of what it says now. Research only.
Ichimoku Kinko Hyo ("one-glance equilibrium chart") is an all-in-one technical indicator that combines trend identification, momentum measurement, support/resistance levels, and time projection in a single visual framework.
Compute the Ichimoku Kinko Hyo for BTC, ETH and SOL using the CryptoDataAPI (X-API-Key header).
1. Definition and parameters: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/concepts/indicators/ichimoku.md
2. Inputs:
- GET https://cryptodataapi.com/api/v1/indicators/technical
- GET https://cryptodataapi.com/api/v1/indicators/signum-rgg
- GET https://cryptodataapi.com/api/v1/hyperliquid/candles
3. Pinned: 4h bars, 500-bar lookback, the playbook's default parameters. Return the latest value, its 30-day percentile, and a one-line read of what it says now. Research only.
The Jurik Moving Average is a commercial adaptive smoothing filter sold by Jurik Research (Mark Jurik), marketed on the claim that it delivers very low lag, high smoothness, and minimal overshoot simultaneously — the three properties conventional filters are forced to trade against each other.
Used byA building block; no catalogue strategy declares it directly.
Via API/api/v1/indicators/catalog/jurik-moving-average
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Compute the Jurik Moving Average (JMA) for BTC, ETH and SOL using the CryptoDataAPI (X-API-Key header).
1. Definition and parameters: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/concepts/indicators/jurik-moving-average.md
2. Inputs:
- GET https://cryptodataapi.com/api/v1/indicators/technical
- GET https://cryptodataapi.com/api/v1/indicators/signum-rgg
- GET https://cryptodataapi.com/api/v1/hyperliquid/candles
3. Pinned: 4h bars, 500-bar lookback, the playbook's default parameters. Return the latest value, its 30-day percentile, and a one-line read of what it says now. Research only.
KAMAKaufman's Adaptive Moving AverageKaufman Adaptive Moving AverageEfficiency Ratio
KAMA is an EMA whose smoothing constant is driven by an Efficiency Ratio — the net distance price travelled over n bars divided by the total length of the path it took to get there.
Used byA building block; no catalogue strategy declares it directly.
Compute the KAMA (Kaufman's Adaptive Moving Average) for BTC, ETH and SOL using the CryptoDataAPI (X-API-Key header).
1. Definition and parameters: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/concepts/indicators/kama.md
2. Inputs:
- GET https://cryptodataapi.com/api/v1/indicators/technical
- GET https://cryptodataapi.com/api/v1/indicators/signum-rgg
- GET https://cryptodataapi.com/api/v1/hyperliquid/candles
3. Pinned: 4h bars, 500-bar lookback, the playbook's default parameters. Return the latest value, its 30-day percentile, and a one-line read of what it says now. Research only.
LSMALinear Regression CurveLeast Squares Moving AverageEnd-Point Moving AverageLinear Regression Line
The Least Squares Moving Average fits an ordinary least-squares straight line to the last n bars of price and plots the fitted value at the most recent bar — the endpoint of the line, not its midpoint.
Used byA building block; no catalogue strategy declares it directly.
Via API/api/v1/indicators/catalog/least-squares-moving-average
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Compute the Least Squares Moving Average (LSMA) for BTC, ETH and SOL using the CryptoDataAPI (X-API-Key header).
1. Definition and parameters: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/concepts/indicators/least-squares-moving-average.md
2. Inputs:
- GET https://cryptodataapi.com/api/v1/indicators/technical
- GET https://cryptodataapi.com/api/v1/indicators/signum-rgg
- GET https://cryptodataapi.com/api/v1/hyperliquid/candles
3. Pinned: 4h bars, 500-bar lookback, the playbook's default parameters. Return the latest value, its 30-day percentile, and a one-line read of what it says now. Research only.
The McGinley Dynamic is a self-adjusting moving average introduced by John R. McGinley (a Chartered Market Technician and former editor of the MTA's Journal of Technical Analysis) in 1997.
Used byA building block; no catalogue strategy declares it directly.
Via API/api/v1/indicators/catalog/mcginley-dynamic
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Compute the McGinley Dynamic for BTC, ETH and SOL using the CryptoDataAPI (X-API-Key header).
1. Definition and parameters: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/concepts/indicators/mcginley-dynamic.md
2. Inputs:
- GET https://cryptodataapi.com/api/v1/indicators/technical
- GET https://cryptodataapi.com/api/v1/indicators/signum-rgg
- GET https://cryptodataapi.com/api/v1/hyperliquid/candles
3. Pinned: 4h bars, 500-bar lookback, the playbook's default parameters. Return the latest value, its 30-day percentile, and a one-line read of what it says now. Research only.
A moving average is a smoothed representation of an asset's price over a specified number of periods, used to identify trend direction and dynamic support and resistance.
Compute the Moving Averages for BTC, ETH and SOL using the CryptoDataAPI (X-API-Key header).
1. Definition and parameters: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/concepts/indicators/moving-averages.md
2. Inputs:
- GET https://cryptodataapi.com/api/v1/indicators/technical
- GET https://cryptodataapi.com/api/v1/indicators/signum-rgg
- GET https://cryptodataapi.com/api/v1/hyperliquid/candles
3. Pinned: 4h bars, 500-bar lookback, the playbook's default parameters. Return the latest value, its 30-day percentile, and a one-line read of what it says now. Research only.
The Schaff Trend Cycle (STC), developed by Doug Schaff in the late 1990s, is a bounded 0–100 oscillator that runs a MACD line through a double stochastic calculation. The aim is MACD's trend sensitivity with less lag and a cleaner on/off output.
Used byA building block; no catalogue strategy declares it directly.
Via API/api/v1/indicators/catalog/schaff-trend-cycle
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Compute the Schaff Trend Cycle for BTC, ETH and SOL using the CryptoDataAPI (X-API-Key header).
1. Definition and parameters: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/concepts/indicators/schaff-trend-cycle.md
2. Inputs:
- GET https://cryptodataapi.com/api/v1/indicators/technical
- GET https://cryptodataapi.com/api/v1/indicators/signum-rgg
- GET https://cryptodataapi.com/api/v1/hyperliquid/candles
3. Pinned: 4h bars, 500-bar lookback, the playbook's default parameters. Return the latest value, its 30-day percentile, and a one-line read of what it says now. Research only.
The Simple Moving Average (SMA) is the arithmetic mean of closing prices over a specified number of periods. It assigns equal weight to every price in the lookback window and is the most fundamental indicator in technical analysis.
Via API/api/v1/indicators/catalog/simple-moving-average
AI-agent prompt
Compute it with an AI agent
Compute the Simple Moving Average for BTC, ETH and SOL using the CryptoDataAPI (X-API-Key header).
1. Definition and parameters: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/concepts/indicators/simple-moving-average.md
2. Inputs:
- GET https://cryptodataapi.com/api/v1/indicators/technical
- GET https://cryptodataapi.com/api/v1/indicators/signum-rgg
- GET https://cryptodataapi.com/api/v1/hyperliquid/candles
3. Pinned: 4h bars, 500-bar lookback, the playbook's default parameters. Return the latest value, its 30-day percentile, and a one-line read of what it says now. Research only.
SSL ChannelSSLSSL HybridSemaphore Signal Level channel
The SSL Channel is a trend-direction overlay built from two moving averages, one of the highs and one of the lows. Its two lines swap places whenever the close breaks outside the high-low envelope, which produces a crossover-style trend flip.
Used byA building block; no catalogue strategy declares it directly.
Compute the SSL Channel for BTC, ETH and SOL using the CryptoDataAPI (X-API-Key header).
1. Definition and parameters: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/concepts/indicators/ssl-channel.md
2. Inputs:
- GET https://cryptodataapi.com/api/v1/indicators/technical
- GET https://cryptodataapi.com/api/v1/indicators/signum-rgg
- GET https://cryptodataapi.com/api/v1/hyperliquid/candles
3. Pinned: 4h bars, 500-bar lookback, the playbook's default parameters. Return the latest value, its 30-day percentile, and a one-line read of what it says now. Research only.
A trend is the prevailing directional movement of a market's price over a given period. Trends are conventionally classified as uptrends (a sequence of higher highs and higher lows), downtrends (lower highs and lower lows), or sideways / ranging markets (price oscillating within a horizontal band with no net direction).
Compute the Trend for BTC, ETH and SOL using the CryptoDataAPI (X-API-Key header).
1. Definition and parameters: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/concepts/indicators/trend.md
2. Inputs:
- GET https://cryptodataapi.com/api/v1/indicators/technical
- GET https://cryptodataapi.com/api/v1/indicators/signum-rgg
- GET https://cryptodataapi.com/api/v1/hyperliquid/candles
3. Pinned: 4h bars, 500-bar lookback, the playbook's default parameters. Return the latest value, its 30-day percentile, and a one-line read of what it says now. Research only.
trendlinetrend linetrend linesuptrend linedowntrend line
A trendline is a straight line drawn on a price chart connecting a series of swing highs or swing lows to visualise the direction and slope of a trend.
Used byA building block; no catalogue strategy declares it directly.
Compute the Trendline for BTC, ETH and SOL using the CryptoDataAPI (X-API-Key header).
1. Definition and parameters: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/concepts/indicators/trendline.md
2. Inputs:
- GET https://cryptodataapi.com/api/v1/indicators/technical
- GET https://cryptodataapi.com/api/v1/indicators/signum-rgg
- GET https://cryptodataapi.com/api/v1/hyperliquid/candles
3. Pinned: 4h bars, 500-bar lookback, the playbook's default parameters. Return the latest value, its 30-day percentile, and a one-line read of what it says now. Research only.
TEMATriple Exponential Moving AverageMulloy TEMADEMADouble Exponential Moving Average
The Triple Exponential Moving Average, introduced by Patrick Mulloy in Technical Analysis of Stocks & Commodities in early 1994 (see Sources — the exact article of the two is contested), removes lag by estimating the smoothing error and subtracting it, using three nested EMAs.
Used byA building block; no catalogue strategy declares it directly.
Via API/api/v1/indicators/catalog/triple-exponential-moving-average
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Compute the Triple Exponential Moving Average (TEMA) for BTC, ETH and SOL using the CryptoDataAPI (X-API-Key header).
1. Definition and parameters: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/concepts/indicators/triple-exponential-moving-average.md
2. Inputs:
- GET https://cryptodataapi.com/api/v1/indicators/technical
- GET https://cryptodataapi.com/api/v1/indicators/signum-rgg
- GET https://cryptodataapi.com/api/v1/hyperliquid/candles
3. Pinned: 4h bars, 500-bar lookback, the playbook's default parameters. Return the latest value, its 30-day percentile, and a one-line read of what it says now. Research only.
WMAWeighted Moving AverageLinearly Weighted Moving AverageLWMALinear Weighted MA
The weighted moving average assigns linearly increasing weights to the prices in its window: the oldest bar gets weight 1, the next gets 2, and the most recent gets n. It sits between the SMA, which weights every bar equally, and the EMA, which decays weights geometrically over an unbounded history.
Used byA building block; no catalogue strategy declares it directly.
Via API/api/v1/indicators/catalog/weighted-moving-average
AI-agent prompt
Compute it with an AI agent
Compute the Weighted Moving Average (WMA) for BTC, ETH and SOL using the CryptoDataAPI (X-API-Key header).
1. Definition and parameters: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/concepts/indicators/weighted-moving-average.md
2. Inputs:
- GET https://cryptodataapi.com/api/v1/indicators/technical
- GET https://cryptodataapi.com/api/v1/indicators/signum-rgg
- GET https://cryptodataapi.com/api/v1/hyperliquid/candles
3. Pinned: 4h bars, 500-bar lookback, the playbook's default parameters. Return the latest value, its 30-day percentile, and a one-line read of what it says now. Research only.
ZLEMAZero-Lag EMAZero Lag Exponential Moving AverageZLEMA (Ehlers-Way)
The Zero-Lag Exponential Moving Average, developed by John Ehlers and Ric Way, removes lag by de-lagging the input before smoothing it rather than by modifying the smoother.
Used byA building block; no catalogue strategy declares it directly.
Via API/api/v1/indicators/catalog/zero-lag-exponential-moving-average
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Compute the Zero-Lag Exponential Moving Average (ZLEMA) for BTC, ETH and SOL using the CryptoDataAPI (X-API-Key header).
1. Definition and parameters: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/concepts/indicators/zero-lag-exponential-moving-average.md
2. Inputs:
- GET https://cryptodataapi.com/api/v1/indicators/technical
- GET https://cryptodataapi.com/api/v1/indicators/signum-rgg
- GET https://cryptodataapi.com/api/v1/hyperliquid/candles
3. Pinned: 4h bars, 500-bar lookback, the playbook's default parameters. Return the latest value, its 30-day percentile, and a one-line read of what it says now. Research only.
Any key works, Free included — mint one in a single call. The list endpoint returns summaries; the per-slug endpoint adds the prompts. Full playbooks come from /api/v1/algobrain/page?path=… using each entry's wiki_path. Or use the MCP server.
What are trend & moving averages indicators?
Direction and strength of the trend: moving averages and crosses, ADX, Ichimoku and channels.
Which trend & moving averages indicators are covered?
24: 200-Day Moving Average, Adaptive Moving Averages, ALMA (Arnaud Legoux Moving Average), Average Directional Index (ADX), Death Cross, Donchian Channels, Exponential Moving Average, Golden Cross, HalfTrend, Hull Moving Average (HMA), Ichimoku Kinko Hyo, Jurik Moving Average (JMA)…
Where do I get trend & moving averages data for crypto?
From these Crypto Data API endpoints: /api/v1/indicators/technical, /api/v1/indicators/signum-rgg, /api/v1/hyperliquid/candles.
Can an AI agent compute these indicators?
Yes. GET /api/v1/indicators/catalog/{slug} returns a prompt naming the endpoints to call and the parameters to pin. Any API key works, Free included.