Technical Indicators Glossary

Averages the closing price over N periods, giving equal weight to each bar. Traders use it to smooth out noise and identify the prevailing trend direction.

A moving average that places more weight on recent prices using exponential decay. It reacts faster to price changes than the SMA, making it popular for short-term trend signals.

Applies EMA twice and combines the results (2×EMA − EMA(EMA)) to nearly eliminate the lag of a standard EMA. Traders use it for faster trend confirmation without sacrificing too much smoothness.

Applies EMA three times and combines them (3×EMA − 3×EMA² + EMA³) to produce the smoothest, lowest-lag moving average in the EMA family. Used for catching trend reversals early.

Assigns linearly increasing weights to bars, so the most recent close has the highest influence on the average. It sits between the SMA (equal weights) and EMA (exponential weights) in terms of responsiveness.

Uses nested weighted moving averages to produce an average that is both smoother than an EMA and nearly as fast as the raw price. The result visually tracks price closely while filtering high-frequency noise.

Automatically adjusts its smoothing speed based on an efficiency ratio: fast in trending markets and slow in choppy ones. This keeps it close to price during trends and flat during consolidation.

Fits a linear regression line to the last N closes and plots its endpoint, showing where the trend line 'is' right now. It reduces noise by treating price as a statistical trend rather than a simple average.

Uses Wilder's smoothing formula (the same method behind RSI and ATR) to produce a very slow, noise-resistant trend line. It gives older data less weight than SMA but smooths more aggressively than EMA.

A self-adjusting moving average that tracks price faster during rallies and slower during declines by dividing the lag correction by the ratio (price/MA)⁴. It avoids whipsaws from market speed changes.

A multi-line system that calculates midpoints of highs and lows over three lookback windows, forming a "cloud" of support and resistance. Traders read the cloud thickness, line crossovers, and price position relative to the cloud to gauge trend direction and momentum.

Measures how strong the current trend is on a 0–100 scale, regardless of direction, by comparing smoothed directional movements to the true range. Readings above 25 suggest a strong trend; the +DI and -DI lines show whether bulls or bears are in control.

Plots a trailing stop that accelerates toward the price as a trend extends. When price crosses the stop, the indicator flips direction, signaling a potential reversal. Traders use it to set dynamic exit points.

Draws a single line above or below price using ATR-based bands around the median price. When price crosses the line, the trend direction flips. Traders use it as a simple trend-following overlay and trailing stop.

Marks significant swing highs and lows by requiring a set number of confirmation bars on each side. A pivot high occurs when a bar's high exceeds every high within the lookback window on both sides; a pivot low when its low undercuts every surrounding low. NaN is returned for non-pivot bars.

Calculates daily support and resistance levels from the previous bar's high, low, and close. The central pivot point (PP) is the average of those three prices. R1 and S1 are the first resistance and support derived by reflecting the PP across the prior high or low.

Three Wilder-smoothed moving averages of the median price (high+low)/2, each using a different period: the slow Jaw (13), medium Teeth (8), and fast Lips (5). When the lines are intertwined the market is sideways ('sleeping'); when they diverge and fan out a trend is in motion ('eating').

Marks swing highs and lows by requiring a bar's high (or low) to be strictly greater (or lower) than the surrounding bars within the chosen period. Fractal Up dots appear at bearish reversal points above price; Fractal Down dots appear at bullish reversal points below price.

Filters out small price fluctuations and draws straight lines connecting only significant swing highs and lows where price reverses by at least the chosen percentage. The current unconfirmed leg is extended forward from the last pivot, making the indicator repaint until confirmed.

Compares the average size of recent gains to recent losses using Wilder's smoothing, producing a 0–100 oscillator. Readings above 70 suggest overbought conditions; below 30 suggests oversold.

Subtracts a slow EMA from a fast EMA to measure momentum, then smooths the result into a signal line. Traders watch for crossovers between the MACD and signal lines, and the histogram shows the gap between them.

Shows where the current close sits within the recent high-low range on a 0–100 scale, smoothed into %K and %D lines. Readings above 80 indicate overbought; below 20 indicates oversold. %K/%D crossovers signal potential turns.

Measures how far the typical price deviates from its moving average, scaled by mean absolute deviation. Readings beyond +100 or –100 signal overbought or oversold conditions.

Measures where the close falls relative to the highest high over N periods on a –100 to 0 scale. Above –20 signals overbought; below –80 signals oversold. It is the inverse of the Stochastic %K.

Applies the Stochastic formula to RSI values instead of price, producing a 0–100 oscillator that is more sensitive to shifts in momentum. Traders use it to catch RSI extremes earlier than RSI alone.

Calculates the percentage change in closing price over N periods. Positive values mean price is rising; negative means falling. It oscillates around zero and helps traders gauge momentum strength.

Takes the percentage change of a triple-smoothed EMA, filtering out short-term noise to reveal the underlying momentum. Zero-line crossings signal trend changes.

Measures how recently the highest high (Aroon Up) and lowest low (Aroon Down) occurred within an N-period lookback, producing two 0–100 lines. The Aroon Oscillator is Up minus Down. High Aroon Up with low Aroon Down signals a new uptrend; the reverse signals a downtrend.

Subtracts the 34-period SMA of the bar’s midpoint (high+low)/2 from the 5-period SMA of the same midpoint. The result oscillates around zero and reflects short-term momentum relative to a longer-term baseline.

Divides the open-to-close move by the high-to-low range, producing a −1 to +1 reading. A value near +1 means buyers pushed price from open to high-end of range; near −1 means sellers dominated. Doji candles (equal high and low) return 0.

Combines Bull Power (high minus EMA) and Bear Power (low minus EMA) into a single line equal to (high + low) − 2×EMA. Positive readings mean bulls are pushing both the high and low above the EMA; negative means bears are dominant.

Calculates the ratio of the sum of up-day moves to the sum of all moves over N periods, scaled to −100–+100. Unlike RSI, it uses both gains and losses in the denominator, making it more sensitive to momentum shifts.

Averages three components: a short RSI of closing prices, an RSI of the consecutive up/down streak count, and a percentile rank of the recent price change. The composite is more mean-reverting than standard RSI.

Applies a weighted moving average to the sum of two rate-of-change readings (default 14 and 11 months). Edwin Coppock designed it specifically to identify long-term bear market bottoms in stock indices.

Subtracts a past SMA from the current close to remove the dominant trend, leaving behind shorter price cycles. Traders use DPO peaks and troughs to measure cycle length and time entries within recurring patterns.

Multiplies the price change by volume and smooths the result with an EMA. Large positive spikes confirm bullish breakouts backed by volume; large negative spikes confirm bearish breakdowns.

Normalizes the close within the N-period high-low range to a −1 to +1 value, then applies the Fisher Transform to convert it into a near-Gaussian distribution. Extreme readings sharply identify potential turning points.

Sums four smoothed rates of change with increasing weights (1, 2, 3, 4) to produce a broad momentum oscillator. A signal line (SMA of KST) is plotted alongside. KST signal crossovers and zero-line crosses are used as trade triggers.

Calculates the raw difference between the current close and the close N bars ago. Positive values mean price is higher than it was N periods ago; negative values mean lower. It is the simplest form of momentum measurement.

Applies two successive EMAs to a rate-of-change calculation, producing a very smooth momentum oscillator. Developed by DecisionPoint, it is used to identify overbought/oversold conditions and momentum divergences on longer timeframes.

Measures the tendency of prices to close higher than they open, normalized by the high-low range and symmetrically smoothed across four bars. High values indicate bullish vigor (closes near highs); low values indicate bearish vigor (closes near lows).

Applies the RSI formula to the rolling standard deviation of closing prices instead of to price changes. Above 50 indicates that recent high-volatility moves were upward; below 50 indicates that high-volatility moves were downward.

Measures the distance of the close from the midpoint of the N-period high-low range, then double-smooths both the numerator and denominator with EMAs. The result is less prone to whipsaw than the standard Stochastic and ranges roughly −100 to +100.

Applies two successive EMAs to both price momentum and absolute momentum, then divides them. The double smoothing removes noise while the ratio normalizes the output to −100–+100. Zero-line crossings and signal-line crossovers are the primary signals.

Combines buying pressure (close minus true low) relative to true range across three timeframes (default 7, 14, 28) using weights of 4, 2, and 1. The multi-timeframe approach reduces false divergence signals common in single-period oscillators.

Shows where the current close sits within the Bollinger Bands on a 0–1 scale: 0 means price is at the lower band, 1 means it is at the upper band. Values below 0 or above 1 indicate the price has broken outside the bands.

Measures the width of the Bollinger Bands as a percentage of the middle band: (upper − lower) / middle × 100. Rising BBW means increasing volatility; falling BBW (a squeeze) means the market is coiling and a breakout is likely.

Places a long stop below the highest high of the lookback period (minus a multiple of ATR) and a short stop above the lowest low (plus the same multiple). When price closes beyond a stop, it signals an exit from the current position.

A two-stage ATR stop that first computes an initial stop from the recent high/low minus/plus ATR, then takes the rolling extreme of that stop over a second lookback. The double smoothing removes whipsaws that plague simpler ATR stops.

Draws upper and lower bands at a fixed percentage above and below an SMA. Unlike Bollinger Bands, the width does not change with volatility. Traders use the bands as dynamic support/resistance and mean-reversion targets.

Computes the annualized standard deviation of daily log returns over N periods, expressed as a percentage. It measures how much the asset actually moved—as opposed to implied volatility, which reflects market expectations.

Measures how much of the total true range over N bars falls within the single highest-to-lowest price range. Readings above 61.8 indicate a choppy, sideways market; below 38.2 indicates a strong trend. It is based on fractal geometry.

Calculates the root mean square of percentage drawdowns from the rolling peak over N periods. Unlike standard deviation, it only penalizes downside moves. Higher values mean more severe or prolonged drawdowns—more ‘stomach pain’ for the holder.

Computes an ATR-based trailing stop that ratchets in the direction of the trend: the long stop only moves up (rolling maximum of close minus ATR multiple) and the short stop only moves down (rolling minimum of close plus ATR multiple).

Places an upper and lower band at N standard deviations above and below an SMA of the close price. The bands widen when volatility increases and contract when it decreases. Traders watch for price touching or breaking the bands as potential reversal or breakout signals.

Smooths the true range (the greatest of high–low, |high–prev close|, or |low–prev close|) using Wilder's method to produce a single volatility reading in price units. Traders use it to size stops and gauge how much a market typically moves per bar.

Draws the highest high and lowest low over N periods as upper and lower bands, with the midpoint between them. A break above the upper channel signals a potential uptrend; below the lower channel signals a downtrend.

Centers an EMA with upper and lower bands set at a multiple of ATR away. Smoother than Bollinger Bands because ATR changes more gradually than standard deviation. Traders use band breaks to confirm trend strength.

Computes a moving average of closing prices where each bar is weighted by its volume. Bars with heavy trading have more influence on the average, making VWMA faster to react during high-activity sessions than an equal-weight SMA.

Applies a fast and slow EMA to the Accumulation/Distribution line and subtracts them, revealing momentum shifts in money flow before they appear in price. Positive values indicate accumulation; negative indicate distribution.

Divides the midpoint price change by the box ratio (volume divided by the high-low range) to measure how easily price moves. Readings far from zero mean price is moving freely; readings near zero mean heavy volume is needed for any movement.

Combines price trend direction, high-low range, and volume into a ‘volume force’ measurement, then applies fast and slow EMAs to produce an oscillator and signal line. Designed to identify long-term money flow while remaining sensitive to short-term swings.

Two companion indicators: NVI updates only on low-volume days (when informed, ‘smart money’ is thought to trade), while PVI updates on high-volume days (when the crowd trades). A rising NVI above its 255-day EMA signals a bull market 96% of the time historically.

Applies the same MACD-style fast/slow EMA crossover logic to volume rather than price, then normalises the result as a percentage. Positive PVO means short-term volume exceeds the longer-term average, signalling rising interest.

Similar to OBV but weights each bar’s volume by the percentage price change rather than just its direction. A bar with a 3% move contributes three times as much as a bar with a 1% move, making PVT more sensitive to the size of price changes.

Assigns each bar’s volume a sign based on whether price closed up (+) or down (−). The result is a signed volume bar chart that makes it easy to see whether buyers or sellers dominated on a given session.

Splits each bar’s volume into two streams: Up Volume (full volume on up-closes) and Down Volume (full volume on down-closes). Unlike Net Volume which assigns a sign, this gives separate bars for each direction, making buying and selling pressure visually distinct.

Calculates the cumulative average price weighted by volume, reflecting the true average price at which trading occurred. Price above VWAP suggests bullish sentiment; below suggests bearish.

Smooths volume over N periods to show the average trading activity. Traders compare current volume to this baseline to spot unusual activity that may confirm or question a price move.

Divides current volume by its moving average. A ratio above 1 means volume is higher than usual; below 1 means quieter. Spikes often confirm breakouts or signal capitulation.

Keeps a running total that adds volume on up-close bars and subtracts it on down-close bars. A rising OBV line suggests accumulation; a falling line suggests distribution, even before price confirms the move.

Applies an RSI-style formula to money flow (typical price multiplied by volume) instead of price alone, producing a 0–100 oscillator. Above 80 signals overbought with heavy buying; below 20 signals oversold with heavy selling.

Sums the close location value (where the close falls within the high-low range) weighted by volume over N periods, then divides by total volume. Positive values indicate buying pressure; negative values indicate selling pressure.

Keeps a cumulative total of each bar's volume weighted by where the close falls within the high-low range. A rising line signals accumulation (buying); a falling line signals distribution (selling).

The raw closing price of each bar. Used as a baseline for comparison with other indicators or as a direct input to trading rules.

Calculates the percentage change in closing price over N bars. Traders use it to measure short-term momentum or to set threshold-based entry and exit rules.

Tracks the highest high price over the last N bars. Commonly used to identify resistance levels and breakout points.

Tracks the lowest low price over the last N bars. Commonly used to identify support levels and breakdown points.