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HWEMA + Ceiling/Channel Combo testThis is a test script. Was developed as a decaying ATR smoothed with HMA
Bullish_1Hour_entry_Indicator with Alertsthis indicator consioders entry basis of EMAs convergence , VWAP & Multitime frame analysis
Candle Range % MarkerHigh/Low Percentage marker. For a Green Candle its low to High. For a Red its from High to Low of the Candle
Bullish_1Hour_entry_Indicator with AlertsIt uses EMAs convergence & VWAP confirmation along with multi Time frame analysis
RSI: alternative derivationMost traders accept the Relative Strength Index (RSI) as a standard tool for measuring momentum. But what if RSI is actually a position indicator?
This script introduces an alternative derivation of RSI, offering a fresh perspective on its true nature. Instead of relying on the traditional calculation of average gains and losses, this approach directly considers the price's position relative to its equilibrium (moving average), adjusted for volatility.
While the final value remains identical to the standard RSI, this alternative derivation offers a completely new understanding of the indicator.
Key components:
Price (Close)
Utilizes the closing price, consistent with the original RSI formula.
normalization factor
Transforms raw calculations into a fixed range between -1 and +1.
normalization_factor = 1 / (Length - 1)
EMA of Price
Applies Wilder’s Exponential Moving Average (EMA) to the price, serving as the anchor point for measuring price position, similar to the traditional RSI formula.
myEMA = ta.rma(close,Length)
EMA of close-to-close absolute changes (unit of volatility)
Adjusts for market differences by applying a Wilder’s EMA to absolute price changes (volatility), ensuring consistency across various assets.
CC_vol = ta.rma(math.abs(close - close ),Length)
Calculation Breakdown
DISTANCE:
Calculate the difference between the closing price and its Wilder's EMA. A positive value indicates the price is above the EMA; a negative value indicates it is below.
distance = close - myEMA
STANDARDIZED DISTANCE
Divide the distance by the unit of volatility to standardize the measurement across different markets.
S_distance = distance / CC_vol
NORMALIZED DISTANCE
Normalize the standardized distance using the normalization factor (n-1) to adjust for the lookback period.
N_distance = S_distance * normalization_factor
RSI
Finally, scale the normalized distance to fit within the standard RSI range of 0 to 100.
myRSI = 50 * (1 + N_distance)
The final equation:
RSI = 50 ×
What This Means for RSI
Same RSI Values, Different Interpretation
The standard RSI formula may obscure its true measurement, whereas this approach offers clarity.
RSI primarily indicates the price's position relative to its equilibrium, rather than directly measuring momentum.
RSI can still be used to analyze momentum, but in a more intuitive and well-informed way.
KD The ScalperWe have to take the trade when all three EMAs are pointing in the same direction (no criss-cross, no up/down, sideways). All 3 EMAs should be cleanly separated from each other with strong spacing between them; they are not tangled, sideways, or messy. This is our first filter before entering the trade. Are the EMAs stacked neatly, and is the price outside of the 25 EMA? If price pulls back and closes near or below the 25 or 50 EMA and breaks the 100 EMA, we don't trade. Use the 100 EMA as a safety net and refrain from trading if the price touches or falls below the 100 EMA.
1. Confirm the trend- All 3 EMAs must align, and they must spread
2. Watch price pull back to the 25th or the 50 EMA
3. Wait for the price to bounce - And re-approach the 25 EMA
Why is this powerful?
Removes 80% of the low-probability Trades
It keeps you out of choppy markets
Avoids Reversal Traps
Anchors us to momentum
We take the entry when the price moves up again and touches the 25 EMA from below, and then when it breaks above the 25 EMA, or even better, when a lovely green bullish candle forms. A bullish candle indicates good momentum. When a bullish candle closes in green, it means the momentum has increased significantly. This is when we enter a long trade, with the stop-loss just below the 50 EMA and the profit target being 1.5 times the stop-loss.
The same rule applies to the bearish trade.
KDJ Divergence Indicator(Regular & Hidden)📌 中文介绍
KDJ 背离指标(副图版,支持 Regular & Hidden)
这是一个基于 KDJ 指标 的背离检测工具,可以在副图中直观显示 Regular 背离(顶背离/底背离) 和 Hidden 背离(隐藏顶/隐藏底)。
功能特点:
可选计算基线:支持以 J 值 或 K 值 作为背离判定依据。
多种背离类型:
Regular Bullish(底背离):价格创新低,但指标不创新低 → 可能反弹。
Regular Bearish(顶背离):价格创新高,但指标不创新高 → 可能回落。
Hidden Bullish(隐藏底背离):价格不创新低,但指标创新低 → 可能延续上涨。
Hidden Bearish(隐藏顶背离):价格不创新高,但指标创新高 → 可能延续下跌。
连线显示:在副图用线条连接前后两个背离点,帮助更直观地发现趋势变化。
自定义选项:
可选择是否显示 Regular / Hidden 背离。
可调整回溯范围(左侧/右侧/最大最小)。
可自定义颜色和信号样式。
报警提醒:背离出现时会触发报警。
适合:
波段交易者寻找趋势反转。
短线交易者捕捉关键拐点。
技术分析结合 KDJ 的交易策略。
📌 English Introduction
KDJ Divergence Indicator (Sub-Chart, Regular & Hidden Supported)
This is a KDJ-based divergence detection tool, plotted in a sub-window, that highlights Regular Divergences (Bullish/Bearish) and Hidden Divergences (Hidden Bullish/Hidden Bearish).
Key Features:
Selectable Oscillator Line: Choose between J or K line as the basis for divergence detection.
Divergence Types:
Regular Bullish: Price makes a lower low, but oscillator makes a higher low → potential rebound.
Regular Bearish: Price makes a higher high, but oscillator makes a lower high → potential drop.
Hidden Bullish: Price holds higher low, but oscillator makes a lower low → potential trend continuation upward.
Hidden Bearish: Price holds lower high, but oscillator makes a higher high → potential trend continuation downward.
Line Connections: Draws connecting lines between divergence points for better visual clarity.
Customizable Settings:
Enable/disable Regular & Hidden divergences.
Adjustable left/right lookback and range filters.
Custom colors and shapes for signals.
Alert Ready: Alerts trigger when divergences are detected.
Best for:
Swing traders spotting trend reversals.
Short-term traders catching turning points.
Technical analysts using KDJ-based strategies.
InsideBarPlus - Alpha GroupInside bar is a great strategy for prop firm evaluations. Since it's a short scalp.
In this version, the target and stops are ATR based.
The reason is that the volatility measurement on that specific moment, makes more sense to measure SL or TP sizing.
I hope you all enjoy. (Backtest it considering slippage, spreads and commissions), on higher timeframes the performance is better, since the spread size "becomes tiny".
Average True Range TrackerThis indicator calculates the daily ATR of the past 14 days. The ATR% indicates the range completed for the day. The ATR indicates the average daily range. The 20% ATR indicates the value of 20% of the daily ATR for retracement purposes.
Daily ATR TrackerThis indicator calculates the daily ATR of the past 14 days. The ATR% indicates the range completed for the day. The ATR indicates the average daily range. The 20% ATR indicates the value of 20% of the daily ATR for retracement purposes.
30m stratDefine a time range, and the indicator will highlight it with a shaded area
This indicator lets you visualize higher timeframe levels while viewing a lower timeframe chart.
Stop ATR [TheAlphaGroup]The Stop ATR is a volatility-based trailing stop that adapts dynamically to market conditions.
It uses the Average True Range (ATR) to plot a continuous “stair-step” line:
• In uptrend, the stop appears below price as a green line, rising with volatility.
• In downtrend, the stop appears above price as a red line, falling with volatility.
Unlike fixed stops, the Stop ATR never moves backward. It only trails in the direction of the trend, locking in profits while leaving room for price to move.
Key features:
• ATR-based trailing stop that adapts to volatility.
• Clean “one line only” design — no overlap of signals.
• Adjustable ATR period and multiplier for flexibility.
• Color-coded visualization for quick trend recognition.
How traders use it:
• Manage trades with volatility-adjusted stop placement (trailing stop).
• Identify trend reversals when price closes across the stop.
• Combine with other entry signals for a complete strategy.
FAILED 9Define a time range, and the indicator will highlight it with a shaded area.
The indicator helps you see higher timeframe structure while trading on a lower timeframes
Adaptive Heikin Ashi [CHE]Adaptive Heikin Ashi — volatility-aware HA with fewer fake flips
Summary
Adaptive Heikin Ashi is a volatility-aware reinterpretation of classic Heikin Ashi that continuously adjusts its internal smoothing based on the current ATR regime, which means that in quiet markets the indicator reacts more quickly to genuine directional changes, while in turbulent phases it deliberately increases its smoothing to suppress jitter and color whipsaws, thereby reducing “noise” and cutting down on fake flips without resorting to heavy fixed smoothing that would lag everywhere.
Motivation: why adapt at all?
Classic Heikin Ashi replaces raw OHLC candles with a smoothed construction that averages price and blends each new candle with the previous HA state, which typically cleans up trends and improves visual coherence, yet its fixed smoothing amount treats calm and violent markets the same, leading to the usual dilemma where a setting that looks crisp in a narrow range becomes too nervous in a spike, and a setting that tames high volatility feels unnecessarily sluggish as soon as conditions normalize; by allowing the smoothing weight to expand and contract with volatility, Adaptive HA aims to keep candles readable across shifting regimes without constant manual retuning.
What is different from normal Heikin Ashi?
Fixed vs. adaptive blend:
Classic HA implicitly uses a fixed 50/50 blend for the open update (`HA_open_t = 0.5 HA_open_{t-1} + 0.5 HA_close_{t-1}`), while this script replaces the constant 0.5 with a dynamic weight `w_t` that oscillates around 0.5 as a function of observed volatility, which turns the open update into an EMA-like filter whose “alpha” automatically changes with market conditions.
Volatility as the steering signal:
The script measures volatility via ATR and compares it to a rolling baseline (SMA of ATR over the same length), producing a normalized deviation that is scaled by sensitivity, clamped to ±1 for stability, and then mapped to a bounded weight interval ` `, so the adaptation is strong enough to matter but never runs away.
Outcome that matters to traders:
In high volatility, the weight shifts upward toward the prior HA open, which strengthens smoothing exactly where classic HA tends to “chatter,” while in low volatility the weight shifts downward toward the most recent HA close, which speeds up reaction so quiet trends do not feel artificially delayed; this is the practical mechanism by which noise and fake signals are reduced without accepting blanket lag.
How it works
1. HA close matches classic HA:
`HA_close_t = (Open_t + High_t + Low_t + Close_t) / 4`
2. Volatility normalization:
`ATR_t` is computed over `atr_length`, its baseline is `ATR_SMA_t = SMA(ATR, atr_length)`, and the raw deviation is `(ATR_t / ATR_SMA_t − 1)`, which is then scaled by `adapt_sensitivity` and clamped to ` ` to obtain `v_t`, ensuring that pathological spikes cannot destabilize the weighting.
3. Adaptive weight around 0.5:
`w_t = 0.5 + oscillation_range v_t`, giving `w_t ∈ `, so with a default `range = 0.20` the weight stays between 0.30 and 0.70, which is wide enough to matter but narrow enough to preserve HA identity.
4. EMA-like open update:
On the very first bar the open is seeded from a stable combination of the raw open and close, and thereafter the update is
`HA_open_t = w_t HA_open_{t−1} + (1 − w_t) HA_close_{t−1}`,
which is equivalent to an EMA where higher `w_t` means heavier inertia (more smoothing) and lower `w_t` means stronger pull to the latest price information (more responsiveness).
5. High and low follow classic HA composition:
`HA_high_t = max(High_t, max(HA_open_t, HA_close_t))`,
`HA_low_t = min(Low_t, min(HA_open_t, HA_close_t))`,
thereby keeping visual semantics consistent with standard HA so that your existing reading of bodies, wicks, and transitions still applies.
Why this reduces noise and fake signals in practice
Fake flips in HA typically occur when a fixed blending rule is forced to process candles during a volatility surge, producing rapid alternations around pivots or within wide intrabar ranges; by increasing smoothing exactly when ATR jumps relative to its baseline, the adaptive open stabilizes the candle body progression and suppresses transient color changes, while in the opposite scenario of compressed ranges, the reduced smoothing allows small but persistent directional pressure to reflect in candle color earlier, which reduces the tendency to enter late after multiple slow transitions.
Parameter guide (what each input really does)
ATR Length (default 14): controls both the ATR and its baseline window, where longer values dampen the adaptation by making the baseline slower and the deviation smaller, which is helpful for noisy lower timeframes, while shorter values make the regime detector more reactive.
Oscillation Range (default 0.20): sets the maximum distance from 0.5 that the weight may travel, so increasing it towards 0.25–0.30 yields stronger smoothing in turbulence and faster response in calm periods, whereas decreasing it to 0.10–0.15 keeps the behavior closer to classical HA and is useful if your strategy already includes heavy downstream smoothing.
Adapt Sensitivity (default 6.0): multiplies the normalized ATR deviation before clamping, such that higher sensitivity accelerates adaptation to regime shifts, while lower sensitivity produces gradual transitions; negative values intentionally invert the mapping (higher vol → less smoothing) and are generally not recommended unless you are testing a counter-intuitive hypothesis.
Reading the candles and the optional diagnostic
You interpret colors and bodies just like with normal HA, but you can additionally enable the Adaptive Weight diagnostic plot to see the regime in real time, where values drifting up toward the upper bound indicate a turbulent context that is being deliberately smoothed, and values gliding down toward the lower bound indicate a calm environment in which the indicator chooses to move faster, which can be valuable for discretionary confirmation when deciding whether a fresh color shift is likely to stick.
Practical workflows and combinations
Trend-following entries: use color continuity and body expansion as usual, but expect fewer spurious alternations around news spikes or into liquidity gaps; pairing with structure (swing highs/lows, breaks of internal ranges) keeps entries disciplined.
Exit management: when the diagnostic weight remains elevated for an extended period, you can be stricter with exit triggers because flips are less likely to be accidental noise; conversely, when the weight is depressed, consider earlier partials since the indicator is intentionally more nimble.
Multi-asset, multi-TF: the adaptation is especially helpful if you rotate instruments with very different vol profiles or hop across timeframes, since you will not need to retune a fixed smoothing parameter every time conditions change.
Behavior, constraints, and performance
The script does not repaint historical bars and uses only past information on closed candles, yet just like any candle-based visualization the current live bar will update until it closes, so you should avoid acting on mid-bar flips without a rule that accounts for bar close; there are no `security()` calls or higher-timeframe lookups, which keeps performance light and execution deterministic, and the clamping of the volatility signal ensures numerical stability even during extreme ATR spikes.
Sensible defaults and quick tuning
Start with the defaults (`ATR 14`, `Range 0.20`, `Sensitivity 6.0`) and observe the weight plot across a few volatile events; if you still see too many flips in turbulence, either raise `Range` to 0.25 or trim `Sensitivity` to 4–5 so that the weight can move high but does not overreact, and if the indicator feels too slow in quiet markets, lower `Range` toward 0.15 or raise `Sensitivity` to 7–8 to bias the weight a bit more aggressively downward when conditions compress.
What this indicator is—and is not
Adaptive Heikin Ashi is a context-aware visualization layer that improves the signal-to-noise ratio and reduces fake flips by modulating smoothing with volatility, but it is not a complete trading system, it does not predict the future, and it should be combined with structure, risk controls, and position management that fit your market and timeframe; always forward-test on your instruments, and remember that even adaptive smoothing can delay recognition at sharp turning points when volatility remains elevated.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Best regards and happy trading
Chervolino
SMC Volatility Liquidity Prothis one’s a confluence signaler. it fires “BUY CALL” / “BUY PUT” labels only when four things line up at once: trend, volatility squeeze, a liquidity sweep, and MACD momentum. quick breakdown:
what each block does
Trend filter (context)
ema50 > ema200 ⇒ trendUp
ema50 < ema200 ⇒ trendDn
Plots both EMAs for visual context.
Volatility compression (setup)
20-period Bollinger Bands (stdev 2).
bb_squeeze is true when current band width < its 20-SMA ⇒ price is compressed (potential energy building).
Liquidity sweep (trigger)
Tracks 20-bar swing high/low.
Long sweep: high > swingHigh ⇒ price just poked above the prior 20-bar high (took buy-side liquidity).
Short sweep: low < swingLow ⇒ price just poked below the prior 20-bar low (took sell-side liquidity).
MACD momentum (confirmation)
Standard MACD(12,26,9) histogram.
Bullish: hist > 0 and rising versus previous bar.
Bearish: hist < 0 and falling.
the actual entry signals
LongEntry = trendUp AND bb_squeeze AND liquiditySweepLong AND macdBullish
→ prints a green “BUY CALL” label below the bar.
ShortEntry = trendDn AND bb_squeeze AND liquiditySweepShort AND macdBearish
→ prints a red “BUY PUT” label above the bar.
alerts & dashboard
Alerts: fires when those long/short conditions hit so you can set TradingView alerts on them.
On-chart dashboard (bottom-right):
Trend (Bullish/Bearish/Neutral)
Squeeze (Yes/No)
Liquidity (Long/Short/None)
Momentum (Bullish/Bearish/Neutral)
Current Signal (BUY CALL / BUY PUT / WAIT)
(btw the comment says “2 columns × 5 rows” but the table is actually 5 columns × 2 rows—values under each label across the row.)
what it’s trying to capture (in plain english)
Trade with the higher-timeframe bias (EMA 50 over 200).
Enter as volatility compresses (bands tight) and a sweep grabs stops beyond a 20-bar extreme.
Only pull the trigger when momentum agrees (MACD hist direction & side of zero).
caveats / tips
It’s an indicator, not a strategy—no entries/exits/backtests baked in.
Signals are strict (4 filters), so you’ll get fewer but “cleaner” prints; still not magical.
The liquidity-sweep check uses the prior bar’s 20-bar high/low ( ), so on bar close it won’t repaint; intrabar alerts may feel jumpy if you alert “on every tick.”
Consider adding:
Exit logic (e.g., ATR stop + take-profit, or opposite signal).
Minimum squeeze duration (e.g., bb_squeeze true for N bars) to avoid one-bar dips in width.
Cool-down after a signal to prevent clustering.
Session/time or volume filter if you only want liquid hours.
if you want, I can convert this into a backtestable strategy() version with ATR-based stops/targets and a few toggles, so you can see stats right away.
LT's RSI Invalidation Targets//@version=5
indicator("Triple RSI Divergence", overlay=true)
// === INPUTS ===
rsiLength = input.int(14, title="RSI Length")
src = input.source(close, "Source")
lookback = input.int(50, title="Lookback Period")
// === RSI ===
rsi = ta.rsi(src, rsiLength)
// === Find local peaks and troughs ===
isTop = ta.pivothigh(rsi, 5, 5)
isBottom = ta.pivotlow(rsi, 5, 5)
var float rsiTroughs = array.new_float()
var float priceTroughs = array.new_float()
var int rsiTroughBars = array.new_int()
if isBottom
array.unshift(rsiTroughs, rsi )
array.unshift(priceTroughs, low )
array.unshift(rsiTroughBars, bar_index )
if array.size(rsiTroughs) > 3
array.pop(rsiTroughs)
array.pop(priceTroughs)
array.pop(rsiTroughBars)
// === Check for triple bullish divergence ===
bullDiv = false
if array.size(rsiTroughs) == 3
r1 = array.get(rsiTroughs, 2)
r2 = array.get(rsiTroughs, 1)
r3 = array.get(rsiTroughs, 0)
p1 = array.get(priceTroughs, 2)
p2 = array.get(priceTroughs, 1)
p3 = array.get(priceTroughs, 0)
// Price: Lower lows, RSI: Higher lows
if p1 > p2 and p2 > p3 and r1 < r2 and r2 < r3
bullDiv := true
label.new(array.get(rsiTroughBars, 0), low, "Triple Bullish Divergence", style=label.style_label_up, color=color.green, textcolor=color.white)
// === Same for triple bearish divergence ===
var float rsiPeaks = array.new_float()
var float pricePeaks = array.new_float()
var int rsiPeakBars = array.new_int()
if isTop
array.unshift(rsiPeaks, rsi )
array.unshift(pricePeaks, high )
array.unshift(rsiPeakBars, bar_index )
if array.size(rsiPeaks) > 3
array.pop(rsiPeaks)
array.pop(pricePeaks)
array.pop(rsiPeakBars)
bearDiv = false
if array.size(rsiPeaks) == 3
r1 = array.get(rsiPeaks, 2)
r2 = array.get(rsiPeaks, 1)
r3 = array.get(rsiPeaks, 0)
p1 = array.get(pricePeaks, 2)
p2 = array.get(pricePeaks, 1)
p3 = array.get(pricePeaks, 0)
// Price: Higher highs, RSI: Lower highs
if p1 < p2 and p2 < p3 and r1 > r2 and r2 > r3
bearDiv := true
label.new(array.get(rsiPeakBars, 0), high, "Triple Bearish Divergence", style=label.style_label_down, color=color.red, textcolor=color.white)
MACD (The Moving Average Convergence Divergence)The Moving Average Convergence Divergence (MACD) is a momentum indicator used in technical analysis to identify trends, measure their strength, and signal potential reversals. It is calculated by subtracting the 26-period Exponential Moving Average (EMA) from the 12-period EMA, creating the MACD line. A 9-period EMA of the MACD line, known as the signal line, is then plotted to generate buy or sell signals. Positive MACD values suggest upward momentum, while negative values indicate downward momentum. Traders often watch for crossovers, divergences, and movements relative to the zero line to make informed decisions.
Ch Enhanced Buy Sell Volume// ========================================
// 📊 HOW TO READ THIS INDICATOR 📊
// ========================================
//
// 🟢 GREEN BARS (Above Zero) = BUY VOLUME
// 🔴 RED BARS (Below Zero) = SELL VOLUME
//
// 💡 BAR COLORS MEANING:
// • DARK GREEN = Strong buyer dominance (high conviction buying)
// • LIGHT GREEN = Weak buyer dominance (low conviction)
// • DARK RED = Strong seller dominance (high conviction selling)
// • LIGHT RED = Weak seller dominance (low conviction)
//
// 🎯 TRADING SIGNALS:
// • Tall dark green bars = Strong bullish momentum
// • Tall dark red bars = Strong bearish momentum
// • Light colored bars = Weak conviction, potential reversal
// • Green bars > Red bars = Buyers winning
// • Red bars > Green bars = Sellers winning
//
// 📈 BULLISH SIGNALS:
// • Buy% > 70% = Strong buying interest
// • Dark green bars with high delta = Professional buying
// • Buy volume above yellow MA line = Above average buying
//
// 📉 BEARISH SIGNALS:
// • Sell% > 70% = Strong selling pressure
// • Dark red bars with high delta = Professional selling
// • Sell volume below yellow MA line = Above average selling
//
// ⚠️ WARNING SIGNALS:
// • Price up + Red dominance = Bearish divergence
// • Price down + Green dominance = Bullish divergence
// • Low delta (<10%) = Market indecision
//
// 📊 INFO TABLE (Top-Right):
// • Buy%: Percentage of volume that was buying
// • Sell%: Percentage of volume that was selling
// • Delta%: Strength of dominance (difference between buy/sell)
// • Dom: Which side is currently dominant (BUYERS/SELLERS)
//
// 🟡 YELLOW LINES = Volume Moving Average
// • Upper line: Reference for buy volume (green bars)
// • Lower line: Reference for sell volume (red bars)
// • Above yellow = Higher than average volume
// • Below yellow = Lower than average volume
Session High Low TrackerTracks the Asia, London, NY AM and NY PM swing highs and lows. What's different here is when a level is broken, it can continue to draw a dotted line so the levels stay on the chart until
end of day. Also has shading options for each session.
AMHA + 4 EMAs + EMA50/200 Counter + Avg10CrossesDescription:
This script combines two types of Heikin-Ashi visualization with multiple Exponential Moving Averages (EMAs) and a counting function for EMA50/200 crossovers. The goal is to make trends more visible, measure recurring market cycles, and provide statistical context without generating trading signals.
Logic in Detail:
Adaptive Median Heikin-Ashi (AMHA):
Instead of the classic Heikin-Ashi calculation, this method uses the median of Open, High, Low, and Close. The result smooths out price movements, emphasizes trend direction, and reduces market noise.
Standard Heikin-Ashi Overlay:
Classic HA candles are also drawn in the background for comparison and transparency. Both HA types can be shifted below the chart’s price action using a customizable Offset (Ticks) parameter.
EMA Structure:
Five exponential moving averages (21, 50, 100, 200, 500) are included to highlight different trend horizons. EMA50 and EMA200 are emphasized, as their crossovers are widely monitored as potential trend signals. EMA21 and EMA100 serve as additional structure layers, while EMA500 represents the long-term trend.
EMA50/200 Counter:
The script counts how many bars have passed since the last EMA50/200 crossover. This makes it easy to see the age of the current trend phase. A colored label above the chart displays the current counter.
Average of the Last 10 Crossovers (Avg10Crosses):
The script stores the last 10 completed count phases and calculates their average length. This provides historical context and allows traders to compare the current cycle against typical past behavior.
Benefits for Analysis:
Clearer trend visualization through adaptive Heikin-Ashi calculation.
Multi-EMA setup for quick structural assessment.
Objective measurement of trend phase duration.
Statistical insight from the average cycle length of past EMA50/200 crosses.
Flexible visualization through adjustable offset positioning below the price chart.
Usage:
Add the indicator to your chart.
For a clean look, you may switch your chart type to “Line” or hide standard candlesticks.
Interpret visual signals:
White candles = bullish phases
Orange candles = bearish phases
EMAs = structural trend filters (e.g., EMA200 as a long-term boundary)
The counter label shows the current number of bars since the last cross, while Avg10 represents the historical mean.
Special Feature:
This script is not a trading system. It does not provide buy/sell recommendations. Instead, it serves as a visual and statistical tool for market structure analysis. The unique combination of Adaptive Median Heikin-Ashi, multi-EMA framework, and EMA50/200 crossover statistics makes it especially useful for trend-followers and swing traders who want to add cycle-length analysis to their toolkit.