Your complete resource for understanding and using technical indicators in your trading strategy.
This guide is for educational purposes only and does not constitute financial advice. Trading involves risk, and you should never invest more than you are willing to lose. Always conduct your own research, consider your risk tolerance, and if necessary, consult a licensed financial advisor before making any trading decisions.
Before diving into technical indicators, it’s essential to understand the core principles of trading:
Mastering these basics creates a solid foundation that helps you use the indicators more effectively and confidently.
A smoother moving average that adapts to market conditions and reduces lag.
The ALMA applies a Gaussian distribution to minimize lag and smooth price data. It responds quickly to price changes while filtering out noise, providing a clearer trend indication than traditional moving averages.
Reduces lag while maintaining responsiveness to price changes, helping traders spot trend shifts earlier.
Overlay ALMA on the price chart. Look for price crossing above ALMA to signal potential uptrends and crossing below to signal potential downtrends. Common period: 9 or 14 bars.
A day trader might use ALMA on a 5-minute chart to quickly identify intraday trend changes and plan short-term entries/exits.
Measures the strength of a trend, regardless of direction.
ADX derives from the Directional Movement Index (+DI and -DI) and indicates how strongly a market is trending. Values above 25 suggest a strong trend, while below 20 indicate a weak or sideways market.
Helps traders decide whether to employ trend-following strategies or range-bound tactics.
Use ADX > 25 to confirm trend strength. Combine with +DI/-DI to determine trend direction. Common period: 14 bars.
A swing trader might only take trades when ADX > 25 to avoid choppy markets that produce false signals.
Tracks trend, momentum, and support/resistance within one comprehensive system.
The Ichimoku Cloud uses five lines (Tenkan, Kijun, Senkou Span A & B, Chikou Span) to create a “cloud” showing trend direction, potential support/resistance, and momentum. Above the cloud is generally bullish, below is bearish.
Offers a holistic view of market conditions, enabling quicker decision-making without multiple separate indicators.
Look for price above the cloud for bullish conditions and below for bearish. Tenkan/Kijun crossovers provide entry signals. Common default periods: 9, 26, 52.
A position trader uses Ichimoku on daily charts to determine long-term trend direction and identify pullback levels within an uptrend.
A faster version of EMA that reduces lag.
Double EMA applies EMA calculations twice, providing a smoother yet more responsive trend line. It reacts quicker to price changes than a standard EMA, giving earlier trend signals.
Offers quicker trend detection without sacrificing too much stability.
Plot Double EMA on the chart and watch for price crossovers. For short-term traders, a 21-period DEMA may provide timely entries.
A day trader might prefer a DEMA over a simple EMA to catch early trend shifts during volatile intraday sessions.
Tracks short- and long-term moving averages to identify trend strength and potential reversals.
GMMA uses two sets of EMAs—short-term and long-term. The relationship between these groups shows how short-term traders and long-term investors interact, helping identify trend breaks and continuations.
Provides a multi-dimensional view of trend stability and crowd behavior.
Look for the short-term EMAs to separate from long-term EMAs to confirm a strong trend. Contraction suggests trend weakening.
A swing trader might use GMMA on a daily chart to confirm that both short-term traders and long-term investors are aligned before entering a position.
A moving average designed to reduce lag and improve responsiveness.
The HMA uses weighted averages and calculations to produce a smoother and faster-reacting line than traditional MAs. It’s designed to eliminate lag while maintaining smoothness.
Offers timely trend signals with less lag, making it easier to catch trends early.
Look for price crossings of HMA or HMA slope changes to signal new trends. A 21-period HMA is a popular setting.
A trend trader might use HMA on a 4-hour chart to identify trend reversals quicker than a simple moving average would.
Uses +DI and -DI lines to determine trend direction.
DMI splits directional movement into +DI (upward) and -DI (downward). When +DI > -DI, the trend is bullish; when -DI > +DI, it’s bearish. Often used alongside ADX to measure trend strength.
Helps clarify trend direction for better timing on entries/exits.
Look for crossovers of +DI and -DI. For example, +DI crossing above -DI can signal a new uptrend. Common period: 14 bars.
An investor might wait for +DI to remain above -DI for several days before entering a long position in a trending stock.
Measures the acceleration of momentum changes.
The Accelerator Oscillator (AC) highlights early changes in momentum. It measures how quickly the market’s driving force is accelerating or decelerating, often signaling trend shifts before they occur.
Helps identify changes in trend direction early, potentially catching turning points.
Monitor the AC around the zero line. Positive AC indicates bullish acceleration, negative AC suggests bearish acceleration.
A short-term trader might watch for AC turning positive from a negative reading as a clue to enter a long trade before price confirms.
Measures market momentum by comparing recent moves to a longer period.
The AO calculates the difference between a short-period and a long-period SMA. It’s displayed as a histogram around the zero line. Positive values indicate bullish momentum, negative values indicate bearish momentum.
Identifies potential trend shifts and momentum changes.
Watch for zero-line crossovers and AO patterns (like saucers) that hint at a developing trend.
A swing trader might wait for AO to cross above zero before entering a long position in anticipation of a bullish trend.
Measures momentum strength, identifying overbought/oversold levels.
The CMO calculates both upward and downward price changes over a period, producing an oscillator bounded between +100 and -100. Readings above +50 indicate overbought, below -50 oversold.
Helps traders time entries/exits by identifying extreme conditions.
Consider buying when CMO < -50 (oversold) and selling when CMO> +50 (overbought). Common period: 14 bars.
A swing trader might buy a dip when CMO signals an oversold condition, anticipating a price rebound.
Measures price deviation from a moving average, identifying cyclical trends.
CCI compares current price to its average price over a period. Values above +100 suggest overbought conditions, and below -100 suggest oversold. It’s not just for commodities; it works on various markets.
Identifies extremes to find potential turning points and swing opportunities.
Go long when CCI moves up from below -100, and consider selling when it moves down from above +100. Common period: 14 bars.
A swing trader might sell when CCI drops below +100 in a range-bound market, expecting a reversion to the mean.
A refined RSI variant combining short-term momentum to pinpoint overbought/oversold levels more accurately.
Connors RSI blends a short-term RSI with two other components (price change and a short-term RSI of that change). This creates more precise overbought/oversold signals, often used in mean-reversion strategies.
Offers more precise signals than standard RSI, improving timing on entries/exits.
Buy when Connors RSI is very low, indicating oversold conditions, and sell when it’s very high. Popular periods: RSI(3) combined with other short terms.
A short-term mean reversion trader might buy dips on a stock when Connors RSI < 10, anticipating a quick bounce.
Identifies long-term buying opportunities, originally designed for stock indices.
The Coppock Curve uses smoothed ROC calculations to find major market bottoms. When the curve turns up from negative territory, it historically signaled long-term buying opportunities in equities.
Designed for investors to identify significant market bottoms rather than short-term trades.
Investors look for the Coppock Curve turning positive from below zero as a long-term entry signal.
An investor may buy into a broad equity index ETF when Coppock Curve signals a new long-term upturn.
Measures momentum across multiple timeframes to identify trend reversals.
KST is a summation of multiple smoothed Rate-of-Change calculations, capturing different cycle lengths. It oscillates around zero, with crossovers signaling potential trend shifts.
Provides a comprehensive momentum reading that reduces false signals from single-timeframe indicators.
Watch for KST line crossing above its signal line for a bullish signal and below for bearish. Default periods vary, often medium-term.
A swing trader might use KST on daily charts to confirm momentum turnarounds before taking reversal trades.
Tracks the flow of money into or out of an asset.
The A/D line uses volume and price to measure whether a security is being accumulated (bought) or distributed (sold). It looks at where price closes within the daily range to assess buying/selling pressure.
Indicates underlying buying or selling pressure that might not be visible in price alone.
Compare A/D line direction with price action. If price falls but A/D rises, it suggests hidden accumulation and a potential bullish reversal.
A trader might hold a long position despite a slight price dip if the A/D line shows continued accumulation.
Measures money flow volume over a set period, indicating buying/selling pressure.
CMF considers where price closes in relation to its high-low range and multiplies by volume. Positive CMF suggests buying pressure, negative indicates selling pressure.
Helps confirm trends and identify divergences related to volume-based buying/selling.
CMF above zero indicates accumulation, below zero indicates distribution. Common period: 20 or 21 bars.
A trader might only take long signals when CMF is positive, ensuring the trend is backed by actual buying interest.
Combines the Accumulation/Distribution line with moving averages to detect volume-related shifts.
The Chaikin Oscillator takes a short and long EMA of the A/D line. When it diverges from price, it can signal looming reversals. Positive readings indicate buying pressure, negative selling pressure.
Offers early signs of trend shifts by incorporating volume and price movement.
Look for divergences between the Chaikin Oscillator and price. A bullish divergence occurs when price makes new lows but the oscillator doesn’t.
A swing trader may look for bullish divergences on the Chaikin Oscillator before entering a long position, anticipating a trend reversal.
Tracks long-term money flow and short-term price movements to signal reversals.
The Klinger Oscillator uses volume and price range to measure long-term money flow trends. It oscillates around zero, and crossovers or divergences can predict trend changes.
Provides early reversal signals by blending volume and price momentum aspects.
Look for Klinger Oscillator crossing above or below its signal line. Divergences with price action often precede reversals.
A trader might wait for a bullish Klinger divergence before buying a stock that’s been drifting lower, anticipating a reversal.
Measures average volatility over a given period.
ATR calculates the average range between high and low prices (including gaps) over a set period. It doesn’t show direction, only the magnitude of price moves.
Helps set stop-loss and take-profit levels and gauge market volatility.
If ATR is high, the market is volatile; use wider stops. If low, market is stable; consider tighter stops. Common period: 14 bars.
A trader might set a stop-loss at 1.5x ATR below their entry to allow for normal price fluctuations without being stopped out prematurely.
Uses standard deviation around a moving average to gauge volatility.
Bollinger Bands consist of an MA plus upper and lower bands set at standard deviations from the MA. Prices touching the bands suggest potential overbought/oversold conditions.
Identifies volatility and potential reversal points when prices reach extreme bands.
Buy near lower band and sell near upper band in range markets. In trending markets, band expansions signal volatility breakouts.
A range trader might short when price hits the upper band in a sideways market, expecting a mean reversion.
Measures the distance between Bollinger Bands to indicate volatility levels.
BB Width calculates the percentage difference between upper and lower bands. Narrow width indicates low volatility (possible breakout soon), wide width means high volatility.
Helps identify periods of consolidation and potential breakout scenarios.
Monitor BB Width for contractions. A very low width often signals a significant move ahead.
A breakout trader might watch for very low BB Width, anticipating a strong price thrust once volatility returns.
Measures volatility by comparing the spread between high and low prices.
Chaikin Volatility looks at the percentage change in the high-low range over a given period. Increases indicate expanding volatility, decreases indicate contraction.
Highlights changes in volatility that may precede major price moves.
A rising CV suggests market is becoming more volatile; traders might tighten stops or prepare for breakouts.
A trader sees Chaikin Volatility rising and anticipates a bigger price swing, adjusting position size accordingly.
Measures how much price has fluctuated in the past.
Historical Volatility calculates the standard deviation of price returns over a chosen period. It’s backward-looking, offering insight into how volatile the asset has been.
Gauges risk levels and helps traders set expectations for future price swings.
High historical volatility suggests larger expected moves. Traders may reduce position size or widen stops.
An options trader might use historical volatility to price options and predict premium changes.
Identifies the highest and lowest price levels over the last year.
Tracks the highest and lowest prices in the past 52 weeks, offering a long-term perspective of price extremes. These often act as key support and resistance levels.
Helps determine critical long-term support/resistance and gauge overall market sentiment.
A break above the 52-week high signals strong bullish sentiment; below 52-week low suggests strong bearish pressure.
An investor might buy a stock making a new 52-week high, expecting continued bullish momentum.
Highlights the highest high and lowest low over a set period, defining breakout levels.
Donchian Channels plot the recent highest high and lowest low. Price breaking above the upper line signals a potential uptrend; below the lower line signals a downtrend.
Helps identify breakouts from consolidations and set clear entry/exit points.
Buy on a break above the upper channel, sell on a break below the lower channel. Common period: 20 bars.
A trend follower might use Donchian Channels to enter trades when the price clears a 20-day high, riding the trend.
Calculates intraday support and resistance levels from the previous day’s prices.
Pivot Points use the previous day’s high, low, and close to generate a pivot plus support (S1, S2) and resistance (R1, R2) levels. Intraday traders often use these levels as reference points.
Helps with intraday trading decisions by providing predefined levels to target or defend.
Buy near S1 if price bounces, target R1 as a profit area. Use pivot as a midpoint reference.
A day trader might use Pivot Points as a guide for setting intraday profit targets or stop losses.
Calculates average price weighted by volume for the current trading session.
VWAP sums up price*volume over the day and divides by total volume. It’s often used as a benchmark by institutions. Price above VWAP suggests bullish sentiment; below suggests bearish.
Provides a fair intraday price, acting as dynamic support/resistance.
Traders may buy below VWAP and target moves toward it, or sell above VWAP, expecting a reversion to the mean.
Scalpers might use VWAP to gauge if they’re getting a “fair” price and align trades accordingly.
Quantifies the strength of price trends, accounting for gaps.
ASI creates a cumulative line representing the true direction of price by factoring in volatility and gaps. It helps confirm trend direction and potential breakout confirmations.
Smooths out erratic price moves to reveal underlying trend strength.
Check if ASI aligns with price trend. Divergences suggest possible reversals. Trendline breaks on ASI can confirm price breakouts.
A trader might wait for an ASI trendline break to confirm that a price breakout is genuine.
Measures the number of advancing vs. declining stocks to gauge market breadth.
The Advance/Decline line accumulates the net difference between advancing and declining stocks. It reveals market participation and sentiment beyond major indexes.
Checks if market rallies are broad-based or driven by a few large stocks.
If A/D line rises with the index, the rally is strong. If it diverges, caution is warranted.
An index trader might avoid longs if the index rises but A/D line falls, anticipating a weak underlying market.
Calculates a mean price over a given period, often (High+Low)/2.
The Average Price provides a central reference point. Traders can quickly see if price is trading above or below the average, indicating bullish or bearish sentiment.
Offers a simple benchmark to judge current price levels.
If current price consistently remains above the average price, sentiment is bullish; below suggests bearish tone.
A beginner might use average price to understand if today’s price is generally “cheap” or “expensive” compared to recent ranges.
Measures the strength of buying vs. selling pressure in the market.
Balance of Power compares the relationship between open and close prices. Positive values show buyers in control; negative values show sellers leading. It helps identify who dominates the market.
Useful for spotting shifts in control that may precede reversals.
Positive BOP readings suggest bullish conditions; negative indicates bearish. Look for changes around zero line.
A trader seeing BOP turn positive after a period of negativity might consider a long position, anticipating a bullish shift.
Normalizes price relative to Bollinger Bands into percentage terms.
%B indicates where the price lies within the Bollinger Bands. A reading of 1 means at the upper band, 0 at the lower band, 0.5 near the middle.
Makes it easy to see overbought/oversold levels in a normalized way.
If %B is near 1, price is near upper band (potentially overbought); near 0 suggests oversold.
A trader might sell a stock when %B nears 1 repeatedly and fails to break out, anticipating a pullback.
Sets trailing stop levels based on volatility, protecting profits in trending markets.
The Chande Kroll Stop calculates stop-loss points using volatility. These dynamic stops follow price as it moves, helping lock in gains without premature exits.
Helps manage risk and protect profits by adapting stop placement to volatility changes.
Plot stop lines above/below price. For longs, place stops below the line; for shorts, above the line.
A trend follower can ride a winning trade longer by trailing the stop level determined by the Chande Kroll Stop.
Indicates whether the market is choppy or trending.
Chop Zone evaluates price volatility and range to determine if conditions are “choppy” (sideways, no clear trend) or stable and trending. High readings mean choppy; low readings mean trending.
Helps traders avoid range-bound conditions when they prefer trending markets.
If the Chop Zone is high, consider using mean-reversion or range strategies; if low, apply trend-following methods.
A trader sees a high Chop Zone reading and decides to avoid breakout strategies until trending conditions return.
Quantifies how "choppy" or directionless the market is.
The Choppiness Index measures how erratic (non-trending) price action is. High readings mean prices move randomly (no trend), low readings indicate directional movement.
Helps traders choose between trend-following or range-bound strategies.
Set thresholds (e.g., above 61.8 = choppy, below 38.2 = trending) to decide strategy.
A day trader seeing a Choppiness Index above 60 might revert to range strategies until a trend emerges.
Measures correlation between two assets using logarithmic returns.
Correlation-Log looks at how two assets move in tandem based on their log returns. Values near +1 mean they move together; near -1 mean opposite moves; near 0 mean no relationship.
Helps with diversification and identifying hedges.
Check correlation before adding assets to a portfolio. Seek low or negative correlation to reduce risk.
A portfolio manager finds a low-correlation asset to hedge against the existing portfolio’s volatility.
Quantifies the linear relationship between two variables or assets.
The Correlation Coefficient measures the degree to which two assets move together in a linear fashion. Perfect correlation is +1, perfect inverse is -1, and no correlation is 0.
Helps understand interdependencies and reduce portfolio risk by choosing less correlated assets.
Use correlation to pair assets for diversification or to build pairs trading strategies (long one asset, short the correlated counterpart).
A trader might avoid highly correlated assets to prevent concentrated risk.
Removes longer-term trends to focus on shorter cycles.
DPO filters out long-term trends, highlighting shorter-term price cycles. It helps identify cyclical turning points without the overshadowing effect of a dominant trend.
Focuses on short-term price patterns and mean reversion opportunities.
Look for DPO peaks and troughs to identify cycle highs and lows. Combine with other signals for confirmation.
A swing trader might use DPO to spot short-term cycle tops and bottoms for quicker trades.
Combines volume and price changes to identify how easily price moves.
EOM relates price change to volume, indicating how much volume is needed to move price. High EOM means price moves easily on low volume, suggesting underlying strength or weakness.
Helps identify efficient price movements and possible emerging trends.
Positive EOM suggests price rises easily, negative EOM suggests downward ease. Use it to confirm breakouts.
A trader might enter long positions when EOM turns positive, expecting price to move upward with minimal resistance.
Combines price changes and volume to measure the force behind price moves.
Force Index = Volume * (Close(today) - Close(yesterday)). Positive values show bullish force, negative values show bearish force. Larger magnitudes mean stronger conviction.
Helps identify trend reversals and confirms the strength behind price moves.
Look for Force Index spikes to confirm breakouts or reversals. A rising Force Index supports bullish moves, a falling one supports bearish moves.
A trader might buy when Force Index turns positive and breaks past recent highs, indicating strong buying pressure.
Tracks when a short-term EMA crosses a long-term EMA to signal trend shifts.
An EMA Cross strategy uses two EMAs (e.g., 50 and 200-period). When the short EMA crosses above the long EMA, it signals a possible uptrend; below indicates downtrend.
Generates clear, easy-to-follow trend reversal signals.
Commonly, a “golden cross” (50 EMA over 200 EMA) signals bullishness, and a “death cross” signals bearishness.
A long-term investor might only buy stocks after a golden cross appears on the daily chart, holding until a death cross occurs.
Highlights overbought/oversold levels around a moving average.
Envelopes are bands set a fixed percentage above and below a moving average. When price hits the upper band, it may be overbought; at the lower band, oversold in range conditions.
Helps identify potential reversal areas in range-bound markets.
Sell at upper envelope and buy at lower envelope in a sideways market. Adjust percentages based on volatility.
A mean-reversion trader may short when price touches the upper envelope and buy at the lower envelope.
Applies a mathematical transform to price for clearer turning points.
The Fisher Transform converts price into a Gaussian normal distribution, making extreme price moves stand out. Crossovers of the Fisher line and signal line often mark turning points.
Clarifies potential reversals by normalizing price movements.
Look for Fisher Transform crossing its signal line at extreme levels to time entries/exits.
A trader might go long when Fisher Transform crosses above its signal line from a deeply negative value.
Uses ATR and an EMA to create dynamic volatility-based channels.
Keltner Channels set bands above and below an EMA based on ATR. Unlike Bollinger Bands, they use ATR rather than standard deviation, often producing smoother channels.
Provides dynamic support/resistance and helps spot trend breakouts.
Buy on breaks above the upper channel in an uptrend, sell on breaks below the lower channel in a downtrend.
A trend follower might use Keltner Channels to identify high-probability entries when price closes beyond channel boundaries.
Measures time since price hit a new high or low to identify trend changes.
Aroon consists of Aroon-Up and Aroon-Down lines. High Aroon-Up means recent highs are frequent (uptrend), high Aroon-Down means recent lows are frequent (downtrend).
Helps identify early trend changes and consolidations.
When Aroon-Up is above 70 and Aroon-Down is low, it indicates a strong uptrend, and vice versa.
A trader might buy a stock when Aroon-Up stays consistently high, signifying a robust uptrend.
Volatility: The degree of variation in a trading price series over time.
Overbought: A condition in which prices are considered too high and likely to fall.
Oversold: A condition in which prices are considered too low and likely to rise.
Divergence: When an indicator moves differently from price action, possibly signaling a reversal.
Stop-Loss: An order placed to sell/buy an asset once it reaches a certain price, limiting loss.
Breakout: When price moves beyond a defined support/resistance level with force.
Mean Reversion: The theory that price tends to return to its average after extreme moves.
Trend-Following: A strategy that aims to enter in the direction of the existing trend.
While each indicator has its own purpose, combining them can create a more holistic and reliable trading approach. Here’s an example of how you might combine multiple indicator types to analyze a coin or stock:
Example: Suppose you’re analyzing a cryptocurrency coin currently trading at $100:
In this scenario, you might consider entering a long position near $98 with a stop-loss below the pivot support and a profit target at a resistance level identified by the Donchian Channel or a recent 52-week high.
This multi-indicator approach gives you a comprehensive market view, reducing reliance on any single metric and improving your odds of making informed trading decisions.