HTF Candle Highs and Lows with Labels + High Probability Signals█ OVERVIEW
This indicator overlays Weekly, Daily, and H4 High/Low levels directly onto your chart, allowing traders to visualize key support and resistance zones from higher timeframes. It also includes high probability breakout signals that appear one candle after a confirmed breakout above or below these levels, filtered by volume and candle strength.
Use this tool to identify breakout opportunities with greater confidence and clarity.
█ FEATURES
• Plots Weekly, Daily, and H4 High and Low levels using request.security. • Customizable line colors, widths, and label sizes. • Toggle visibility for each timeframe independently. • Signals appear one candle after a confirmed breakout: • Bullish: Close above HTF High, strong candle, high volume. • Bearish: Close below HTF Low, strong candle, high volume. • Signal shapes match the color of the broken level for visual clarity.
█ HOW TO USE
1 — Enable the timeframes you want to track using the input toggles. 2 — Watch for triangle-shaped signals: • Upward triangle = Bullish breakout. • Downward triangle = Bearish breakout. 3 — Confirm the breakout: • Candle closes beyond the HTF level by at least 0.1%. • Candle body shows momentum (close > open for bullish, close < open for bearish). • Volume exceeds 20-period average. 4 — Enter trade on the candle after the signal. 5 — Use the HTF level as a reference for stop-loss placement. 6 — Combine with other indicators (e.g., RSI, EMA) for confluence.
█ LIMITATIONS
• Signals may lag by one candle due to confirmation logic. • Not optimized for low-volume assets or illiquid markets. • Best used in trending environments; avoid during consolidation. • Does not include automatic alerts (can be added manually).
█ BEST PRACTICES
• Use on H1 or higher timeframes for cleaner signals. • Avoid trading during news events or low volatility. • Backtest thoroughly before live trading. • Adjust breakout percentage and volume filter based on asset volatility. • Maintain a trading journal to track performance.
在腳本中搜尋"bear"
SuperScript Filtered (Stable)🔎 What This Indicator Does
The indicator is a trend and momentum filter.
It looks at multiple well-known technical tools (T3 moving averages, RSI, TSI, and EMA trend) and assigns a score to the current market condition.
• If most tools are bullish → score goes up.
• If most tools are bearish → score goes down.
• Only when the score is very strong (above +75 or below -75), it prints a Buy or Sell signal.
This helps traders focus only on high-probability setups instead of reacting to every small wiggle in price.
________________________________________
⚙️ How It Works
1. T3 Trend Check
o Compares a fast and slow T3 moving average.
o If the fast T3 is above the slow T3 → bullish signal.
o If it’s below → bearish signal.
2. RSI Check
o Uses the Relative Strength Index.
o If RSI is above 50 → bullish momentum.
o If RSI is below 50 → bearish momentum.
3. TSI Check
o Uses the True Strength Index.
o If TSI is above its signal line → bullish momentum.
o If TSI is below → bearish momentum.
4. EMA Trend Check
o Looks at two exponential moving averages (fast and slow).
o If price is above both → bullish.
o If price is below both → bearish.
5. Score System
o Each condition contributes +25 (bullish) or -25 (bearish).
o The total score can range from -100 to +100.
o Score ≥ +75 → Strong Buy
o Score ≤ -75 → Strong Sell
6. Signal Filtering
o Only one buy is allowed until a sell appears (and vice versa).
o A minimum bar gap is enforced between signals to avoid clutter.
________________________________________
📊 How It Appears on the Chart
• Green “BUY” label below candles → when multiple signals agree and the market is strongly bullish.
• Red “SELL” label above candles → when multiple signals agree and the market is strongly bearish.
• Background softly shaded green or red → highlights bullish or bearish conditions.
No messy tables, no clutter — just clear trend-based entries.
________________________________________
🎯 How Traders Can Use It
This indicator is designed to help traders by:
1. Filtering Noise
o Instead of reacting to every small crossover or RSI blip, it waits until at least 3–4 conditions agree.
o This avoids entering weak trades.
2. Identifying Strong Trend Shifts
o When a Buy or Sell arrow appears, it usually signals a shift in momentum that can lead to a larger move.
3. Reducing Overtrading
o By limiting signals, traders won’t be tempted to jump in and out unnecessarily.
4. Trade Confirmation
o Traders can use the signals as confirmation for their own setups.
o Example: If your strategy says “go long” and the indicator also shows a strong Buy, that trade has more conviction.
5. Alert Automation
o Built-in alerts mean you don’t have to watch the chart all day.
o You’ll be notified only when a strong signal appears.
________________________________________
⚡ When It Helps the Most
• Works best in trending markets (bullish or bearish).
• Very useful on higher timeframes (1h, 4h, daily) for swing trading.
• Can also work on lower timeframes (5m, 15m) if combined with higher timeframe trend filtering.
________________________________________
👉 In short
This indicator is a signal filter + trend detector. It combines four powerful tools into one scoring system, and only tells you to act when the odds are stacked in your favor.
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Trend Speed Analyzer + alerts//@version=6
indicator('Trend Speed Analyzer + alerts', overlay = false)
//~~}
// ~~ Tooltips {
string t1 = 'Maximum Length: This parameter sets the upper limit for the number of bars considered in the dynamic moving average. A higher value smooths out the trend line, making it less reactive to minor fluctuations but slower to adapt to sudden price movements. Use higher values for long-term trend analysis and lower values for faster-moving markets.'
string t2 = 'Accelerator Multiplier: Adjusts the responsiveness of the dynamic moving average to price changes. A larger value makes the trend more reactive but can introduce noise in choppy markets. Lower values create a smoother trend but may lag behind rapid price movements. This is particularly useful in volatile markets where precise sensitivity is needed.'
string t5 = 'Enable Candles: When enabled, the candlesticks on the chart will be color-coded based on the calculated trend speed. This provides a visual representation of momentum, making it easier to spot shifts in market dynamics. Disable this if you prefer the standard candlestick colors.'
string t6 = 'Collection Period: Defines the number of bars used to normalize trend speed values. A higher value includes a broader historical range, smoothing out the speed calculation. Lower values make the speed analysis more sensitive to recent price changes, ideal for short-term trading.'
string t7 = 'Enable Table: Activates a statistical table that provides an overview of key metrics, such as average wave height, maximum wave height, dominance, and wave ratios. Useful for traders who want numerical insights to complement visual trend analysis.'
string t8 = 'Lookback Period: Determines how many historical bars are used for calculating bullish and bearish wave data. A longer lookback period provides a more comprehensive view of market trends but may dilute sensitivity to recent market conditions. Shorter periods focus on recent data.'
string t9 = 'Start Date: Sets the starting point for all calculations. This allows you to analyze data only from a specific date onward, which is useful for isolating trends within a certain period or avoiding historical noise.'
string t10 = 'Timer Option: Select between using a custom start date or starting from the first available bar on the chart. The \'Custom\' option works with the Start Date setting, while \'From start\' includes all available data.'
// Tooltips for Table Cells
string tt1 = 'Average Wave: Shows the average size of bullish or bearish waves during the lookback period. Use this to assess overall market strength. Larger values indicate stronger trends, and comparing bullish vs bearish averages can reveal market bias. For instance, a higher bullish average suggests a stronger uptrend.'
string tt2 = 'Max Wave: Displays the largest bullish or bearish wave during the lookback period. Use this to identify peak market momentum. A significantly higher bullish or bearish max wave indicates where the market may have shown extreme trend strength in that direction.'
string tt3 = 'Current Wave Ratio (Average): Compares the current wave\'s size to the average wave size for both bullish and bearish trends. A value above 1 indicates the current wave is stronger than the historical average, which may signal increased market momentum. Use this to evaluate if the current move is significant compared to past trends.'
string tt4 = 'Current Wave Ratio (Max): Compares the current wave\'s size to the maximum wave size for both bullish and bearish trends. A value above 1 suggests the current wave is setting new highs in strength, which could indicate a breakout or strong momentum in the trend direction.'
string tt5 = 'Dominance (Average): The net difference between the average bullish and bearish wave sizes. Positive values suggest bullish dominance over time, while negative values indicate bearish dominance. Use this to determine which side (bulls or bears) has had consistent control of the market over the lookback period.'
string tt6 = 'Dominance (Max): The net difference between the largest bullish and bearish wave sizes. Positive values suggest bulls have dominated with stronger individual waves, while negative values indicate bears have produced stronger waves. Use this to gauge the most significant power shifts in the market.'
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~}
max_length = input.int(50, minval = 1, title = 'Maximum Length', group = 'Dynamic Moving Average', tooltip = t1)
accel_multiplier = input.float(5.0, minval = 0.0, step = 1.1, title = 'Accelerator Multiplier', group = 'Dynamic Moving Average', tooltip = t2)
tbl_ = input.bool(true, title = 'Enable Table', group = 'Wave Analysis', tooltip = t7)
lookback_period = input.int(100, minval = 1, step = 1, title = 'Lookback Period', group = 'Wave Analysis', tooltip = t8)
candle = input.bool(true, title = 'Enable Candles', group = 'Trend Visualization', tooltip = t5)
collen = input.int(100, step = 10, minval = 5, title = 'Collection Period', group = 'Trend Visualization', tooltip = t6)
up_col = input.color(color.lime, title = 'Dynamic Trend', group = 'Trend Visualization', inline = 'Trend')
dn_col = input.color(color.red, title = '', group = 'Trend Visualization', inline = 'Trend')
up_hist_col = input.color(#82ffc3, title = 'Trend Speed Up', group = 'Trend Visualization', inline = 'up')
up_hist_col_ = input.color(color.lime, title = '', group = 'Trend Visualization', inline = 'up')
dn_hist_col = input.color(color.red, title = 'Trend Speed Dn', group = 'Trend Visualization', inline = 'dn')
dn_hist_col_ = input.color(#f78c8c, title = '', group = 'Trend Visualization', inline = 'dn')
start = input.time(timestamp('1 Jan 2020 00:00 +0000'), title = 'Start Date', group = 'Time Settings', tooltip = t9, inline = 'startdate')
timer = input.string('From start', title = 'Timer Option', options = , group = 'Time Settings', tooltip = t10, inline = 'startdate')
// ~~ Dynamic Average {
counts_diff = close
max_abs_counts_diff = ta.highest(math.abs(counts_diff), 200)
counts_diff_norm = (counts_diff + max_abs_counts_diff) / (2 * max_abs_counts_diff)
dyn_length = 5 + counts_diff_norm * (max_length - 5)
// ~~ Function to compute the accelerator factor with normalization of delta_counts_diff {
calc_accel_factor(float counts_diff, float prev_counts_diff) =>
delta_counts_diff = math.abs(counts_diff - prev_counts_diff)
float max_delta_counts_diff = ta.highest(delta_counts_diff, 200)
max_delta_counts_diff := max_delta_counts_diff == 0 ? 1 : max_delta_counts_diff
float accel_factor = delta_counts_diff / max_delta_counts_diff
accel_factor
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~}
// ~~ Function to adjust alpha using the accelerator factor {
adjust_alpha(float dyn_length, float accel_factor, float accel_multiplier) =>
alpha_base = 2 / (dyn_length + 1)
alpha = alpha_base * (1 + accel_factor * accel_multiplier)
alpha := math.min(1, alpha)
alpha
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~}
// ~~ Accelerator Factor
accel_factor = calc_accel_factor(counts_diff, nz(counts_diff ))
alpha = adjust_alpha(dyn_length, accel_factor, accel_multiplier)
// ~~ Compute dynamic Ema
var float dyn_ema = na
dyn_ema := na(dyn_ema ) ? close : alpha * close + (1 - alpha) * dyn_ema
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~}
// ~~ Trend Speed {
trend = dyn_ema
bullsrc = close
bearsrc = close
type TrendData
array change
array t
StartTime() =>
time > start
var bullish = TrendData.new(array.new(), array.new())
var bearish = TrendData.new(array.new(), array.new())
var x1 = int(na)
var y1 = float(na)
var pos = 0
var speed = 0.0
c = ta.rma(close, 10)
o = ta.rma(open, 10)
// ~~ First value {
if na(x1) and StartTime() or na(x1) and timer == 'From start'
x1 := bar_index
y1 := o
y1
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~}
// ~~ Trend direction {
if StartTime() or timer == 'From start'
if bullsrc > trend and bullsrc <= trend
bearish.change.unshift(ta.lowest(speed, bar_index - x1))
bearish.t.unshift(bar_index - x1)
x1 := bar_index
y1 := bullsrc
pos := 1
speed := c - o
speed
if bearsrc < trend and bearsrc >= trend
bullish.change.unshift(ta.highest(speed, bar_index - x1))
bullish.t.unshift(bar_index - x1)
x1 := bar_index
y1 := bearsrc
pos := -1
speed := c - o
speed
speed := speed + c - o
speedGradient = color.from_gradient(speed, ta.min(-speed / 3), ta.max(speed / 3), color.red, color.lime)
trendspeed = ta.hma(speed, 5)
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~}
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~}
// ~~ Plots {
rma_dyn_ema(x, p) =>
average = ta.rma(dyn_ema , p)
average
colour = ta.wma(close, 2) > dyn_ema ? up_col : dn_col
fillColor = rma_dyn_ema(0, 5) > rma_dyn_ema(1, 5) ? color.new(up_col, 70) : color.new(dn_col, 70)
p1 = plot(dyn_ema, color = colour, linewidth = 2, title = 'Dynamic Trend', force_overlay = true)
p2 = plot(ta.rma(hl2, 50), display = display.none, editable = false, force_overlay = true)
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~}
min_speed = ta.lowest(speed, collen)
max_speed = ta.highest(speed, collen)
normalized_speed = (speed - min_speed) / (max_speed - min_speed)
speedGradient1 = speed < 0 ? color.from_gradient(normalized_speed, 0.0, 0.5, dn_hist_col, dn_hist_col_) : color.from_gradient(normalized_speed, 0.5, 1.0, up_hist_col, up_hist_col_)
plot(StartTime() or timer == 'From start' ? trendspeed : na, title = 'Trend Speed', color = speedGradient1, style = plot.style_columns)
plotcandle(open, high, low, close, color = candle ? speedGradient1 : na, wickcolor = candle ? speedGradient1 : na, bordercolor = candle ? speedGradient1 : na, force_overlay = true)
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~}
// ~~ Table {
if barstate.islast and tbl_
bullish_recent = bullish.change.slice(0, math.min(lookback_period, bullish.change.size()))
bearish_recent = bearish.change.slice(0, math.min(lookback_period, bearish.change.size()))
bull_max = bullish_recent.max()
bear_max = bearish_recent.min()
bull_avg = bullish_recent.avg()
bear_avg = bearish_recent.avg()
wave_size_ratio_avg = bull_avg / math.abs(bear_avg)
wave_size_text_avg = str.tostring(math.round(wave_size_ratio_avg, 2)) + 'x'
wave_size_color_avg = wave_size_ratio_avg > 0 ? color.lime : color.red
wave_size_ratio_max = bull_max / math.abs(bear_max)
wave_size_text_max = str.tostring(math.round(wave_size_ratio_max, 2)) + 'x'
wave_size_color_max = wave_size_ratio_max > 0 ? color.lime : color.red
dominance_avg_value = bull_avg - math.abs(bear_avg)
dominance_avg_text = dominance_avg_value > 0 ? 'Bullish +' + str.tostring(math.round(wave_size_ratio_avg, 2)) + 'x' : 'Bearish -' + str.tostring(math.round(1 / wave_size_ratio_avg, 2)) + 'x'
dominance_avg_color = dominance_avg_value > 0 ? color.lime : color.red
dominance_max_value = bull_max - math.abs(bear_max)
dominance_max_text = dominance_max_value > 0 ? 'Bullish +' + str.tostring(math.round(wave_size_ratio_max, 2)) + 'x' : 'Bearish -' + str.tostring(math.round(1 / wave_size_ratio_max, 2)) + 'x'
dominance_max_color = dominance_max_value > 0 ? color.lime : color.red
current_wave = speed
current_wave_color = current_wave > 0 ? color.lime : color.red
current_ratio_avg = current_wave > 0 ? current_wave / bull_avg : current_wave / math.abs(bear_avg)
current_ratio_max = current_wave > 0 ? current_wave / bull_max : current_wave / math.abs(bear_max)
current_text_avg = str.tostring(math.round(current_ratio_avg, 2)) + 'x'
current_text_max = str.tostring(math.round(current_ratio_max, 2)) + 'x'
current_color_avg = current_ratio_avg > 0 ? color.lime : color.red
current_color_max = current_ratio_max > 0 ? color.lime : color.red
var tbl = table.new(position.top_right, 3, 3, force_overlay = true)
table.cell(tbl, 0, 0, '', text_color = chart.fg_color, tooltip = '')
table.cell(tbl, 0, 1, 'Average Wave', text_color = chart.fg_color, tooltip = tt1)
table.cell(tbl, 0, 2, 'Max Wave', text_color = chart.fg_color, tooltip = tt2)
table.cell(tbl, 1, 0, 'Current Wave Ratio', text_color = chart.fg_color, tooltip = '')
table.cell(tbl, 1, 1, current_text_avg, text_color = current_color_avg, tooltip = tt3)
table.cell(tbl, 1, 2, current_text_max, text_color = current_color_max, tooltip = tt4)
table.cell(tbl, 2, 0, 'Dominance', text_color = chart.fg_color, tooltip = '')
table.cell(tbl, 2, 1, dominance_avg_text, text_color = dominance_avg_color, tooltip = tt5)
table.cell(tbl, 2, 2, dominance_max_text, text_color = dominance_max_color, tooltip = tt6)
// ─────────────────────────────────────────────────────────────
// MTF BUY/SELL alerts: 10m & 1H agreement (no logic changes)
isGreen = ta.wma(close, 2) > dyn_ema
tf_fast = input.timeframe("10", "Fast TF (Buy/Sell check)", group = "MTF Alerts")
tf_slow = input.timeframe("60", "Slow TF (Buy/Sell check)", group = "MTF Alerts")
confirm_on_close = input.bool(true, "Confirm on bar close", group = "MTF Alerts")
green_fast = request.security(syminfo.tickerid, tf_fast, isGreen, lookahead = barmerge.lookahead_off)
green_slow = request.security(syminfo.tickerid, tf_slow, isGreen, lookahead = barmerge.lookahead_off)
buyCond = green_fast and green_slow
sellCond = not green_fast and not green_slow
triggerOK = confirm_on_close ? barstate.isconfirmed : true
// Single BUY / SELL alerts (messages unchanged)
alertcondition(buyCond and triggerOK, title = "MTF BUY (10m & 1H GREEN)", message = "{{ticker}} | TF={{interval}} | Dynamic line")
alertcondition(sellCond and triggerOK, title = "MTF SELL (10m & 1H RED)", message = "{{ticker}} | TF={{interval}} | Dynamic line")
// ─────────────────────────────────────────────────────────────
// NEW: 10m status repeated EVERY MINUTE (no logic changes)
// ─────────────────────────────────────────────────────────────
// 1-minute pulse: true once per closed 1m bar
m1_pulse = request.security(syminfo.tickerid, "1", barstate.isconfirmed, lookahead = barmerge.lookahead_off)
// Repeat ONLY the 10-minute status every minute
status10_green = green_fast
status10_red = not green_fast
alertcondition(status10_green and m1_pulse, title = "10m Status GREEN — repeat each minute", message = "{{ticker}} | TF=10 | Dynamic line — GREEN")
alertcondition(status10_red and m1_pulse, title = "10m Status RED — repeat each minute", message = "{{ticker}} | TF=10 | Dynamic line — RED")
how do the trend speed anlaysis work
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.
AI Trading Alerts v6 — SL/TP + Confidence + Panel (Fixed)Overview
This Pine Script is designed to identify high-probability trading opportunities in Forex, commodities, and crypto markets. It combines EMA trend filters, RSI, and Stochastic RSI, with automatic stop-loss (SL) & take-profit (TP) suggestions, and provides a confidence panel to quickly assess the trade setup strength.
It also includes TradingView alert conditions so you can set up notifications for Long/Short setups and EMA crosses.
⚙️ Features
EMA Trend Filter
Uses EMA 50, 100, 200 for trend confirmation.
Bull trend = EMA50 > EMA100 > EMA200
Bear trend = EMA50 < EMA100 < EMA200
RSI Filter
Bullish trades require RSI > 50
Bearish trades require RSI < 50
Stochastic RSI Filter
Prevents entries during overbought/oversold extremes.
Bullish entry only if %K and %D < 80
Bearish entry only if %K and %D > 20
EMA Proximity Check
Price must be near EMA50 (within ATR × adjustable multiplier).
Signals
Continuation Signals:
Long if all bullish conditions align.
Short if all bearish conditions align.
Cross Events:
Long Cross when price crosses above EMA50 in bull trend.
Short Cross when price crosses below EMA50 in bear trend.
Automatic SL/TP Suggestions
SL size adjusts depending on asset:
Gold/Silver (XAU/XAG): 5 pts
Bitcoin/Ethereum: 100 pts
FX pairs (default): 20 pts
TP = SL × Risk:Reward ratio (default 1:2).
Confidence Score (0–4)
Based on conditions met (trend, RSI, Stoch, EMA proximity).
Labels:
Strongest (4/4)
Strong (3/4)
Medium (2/4)
Low (1/4)
Visual Panel on Chart
Shows ✅/❌ for each condition (trend, RSI, Stoch, EMA proximity, signal now).
Confidence row with color-coded strength.
Alerts
Long Setup
Short Setup
Long Cross
Short Cross
🖥️ How to Use
1. Add the Script
Open TradingView → Pine Editor.
Paste the full script.
Click Add to chart.
Save as "AI Trading Alerts v6 — SL/TP + Confidence + Panel".
2. Configure Inputs
EMA Lengths: Default 50/100/200 (works well for swing trading).
RSI Length: 14 (standard).
Stochastic Length/K/D: Default 14/3/3.
Risk:Reward Ratio: Default 2.0 (can change to 1.5, 3.0, etc.).
EMA Proximity Threshold: Default 0.20 × ATR (adjust to be stricter/looser).
3. Read the Panel
Top-right of chart, you’ll see ✅ or ❌ for:
Trend → Are EMAs aligned?
RSI → Above 50 (bull) or below 50 (bear)?
Stoch OK → Not extreme?
Near EMA50 → Close enough to EMA50?
Above/Below OK → Price position vs. EMA50 matches trend?
Signal Now → Entry triggered?
Confidence row:
🟢 Green = Strongest
🟩 Light green = Strong
🟧 Orange = Medium
🟨 Yellow = Low
⬜ Gray = None
4. Alerts Setup
Go to TradingView Alerts (⏰ icon).
Choose the script under “Condition”.
Select alert type:
Long Setup
Short Setup
Long Cross
Short Cross
Set notification method (popup, sound, email, mobile).
Click Create.
Now TradingView will notify you automatically when signals appear.
5. Example Workflow
Wait for Confidence = Strong/Strongest.
Check if market session supports volatility (e.g., XAU in London/NY).
Review SL/TP suggestions:
Long → Entry: current price, SL: close - risk_pts, TP: close + risk_pts × RR.
Short → Entry: current price, SL: close + risk_pts, TP: close - risk_pts × RR.
Adjust based on your own price action analysis.
📊 Best Practices
Use on H1 + D1 combo → align higher timeframe bias with intraday entries.
Risk only 1–2% of account per trade (position sizing required).
Filter with market sessions (Asia, Europe, US).
Strongest signals work best with trending pairs (e.g., XAUUSD, USDJPY, BTCUSD).
TEWMA - [JTCAPITAL]TEWMA - is a modified way to use Triple Exponential Moving Average (TEMA) combined with Weighted Moving Average (WMA) and adaptive multi-length averaging for Trend-Following.
The indicator blends short- and extended-length smoothed signals into a single adaptive line, then assigns directional bias to highlight bullish or bearish phases more clearly.
The indicator works by calculating in the following steps:
Source Selection
The script begins with a selectable price source (default: Close, but can be changed to Open, High, Low, HL2, etc.). This ensures flexibility depending on the user’s preferred market perspective.
Dual-Length Calculation
A base length ( len ) is chosen, and then multiplied by a factor ( multi , default 1.75). This produces a secondary, longer period ( len2 ) that adapts proportionally to the base.
Weighted + Triple Exponential Smoothing
-First, a WMA (Weighted Moving Average) is applied to the price source.
-Then, the TEMA (Triple Exponential Moving Average) is applied to smooth the WMA even further.
-This process is repeated for both len and len2 , producing TEWMA1 and TEWMA2 .
Adaptive Averaging
The final TEWMA line is calculated as the average of TEWMA1 and TEWMA2, creating a blend between the short-term and extended-term signals. This balances reactivity and stability, reducing lag while avoiding excessive noise.
Trend Direction Detection
-If TEWMA is greater than its previous value → Bullish .
-If TEWMA is lower than its previous value → Bearish .
-A Signal variable is used to store this directional bias, ensuring continuity between bars.
Visual Plotting
-The main TEWMA is plotted with bold coloring (Blue for bullish, Purple for bearish).
-TEWMA1 and TEWMA2 are plotted as thinner supporting lines.
-Each line is given a shadow-fill (between 100% and 90% of its value) for emphasis and visual clarity.
Alerts
Custom alerts are defined:
- TEWMA Long → when bullish.
- TEWMA Short → when bearish.
-These alerts can be integrated into TradingView’s alerting system for automated notifications.
Buy and Sell Conditions :
- Buy : Triggered when TEWMA rises (bullish slope). The indicator colors the line blue and an alert can be fired.
- Sell : Triggered when TEWMA declines (bearish slope). The line turns purple, signaling potential short or exit points.
Features and Parameters :
- Source → Selectable price input (Close, Open, HL2, etc.).
- Length (len) → Base period for the WMA/TEMA calculation.
- Multiplier (multi) → Scales the secondary length to create a longer-term smoothing.
- Color-coded Trend Lines → Blue for bullish, Purple for bearish.
- Shadow Fill Effects → Provides depth and easier visualization of trend direction.
- Alert Conditions → Prebuilt alerts for both Long and Short scenarios.
Specifications :
Weighted Moving Average (WMA)
The WMA assigns more weight to recent price values, making it more responsive than a Simple Moving Average (SMA). This enhances early detection of market turns while reducing lag compared to longer-term averages.
Triple Exponential Moving Average (TEMA)
TEMA is designed to minimize lag by combining multiple EMA layers (EMA of EMA of EMA). It is smoother and more adaptive than traditional EMAs, making it ideal for detecting true market direction without overreacting to small fluctuations.
Multi-Length Averaging
By calculating two versions of WMA → TEMA with different lengths and then averaging them, the indicator balances responsiveness (short-term sensitivity) and reliability (long-term confirmation). This prevents whipsawing while keeping signals timely.
Adaptive Signal Assignment
Instead of simply flipping signals at crossovers, the indicator checks slope direction of TEWMA. This ensures smoother trend-following behavior, reducing false positives in sideways conditions.
Color-Coding & Visual Shading
Visual clarity is achieved by coloring bullish periods differently from bearish ones, with shaded fills beneath each line. This allows traders to instantly identify trend conditions and compare short- vs long-term signals.
Alert Conditions
Trading decisions can be automated by attaching alerts to the TEWMA’s bullish and bearish states. This makes it practical for active trading, swing setups, or algorithmic strategies.
Enjoy!
Market Pressure Oscillator█ OVERVIEW
The Market Pressure Oscillator is an advanced technical indicator for TradingView, enabling traders to identify potential trend reversals and momentum shifts through candle-based pressure analysis and divergence detection. It combines a smoothed oscillator with moving average signals, overbought/oversold levels, and divergence visualization, enhanced by customizable gradients, dynamic band colors, and alerts for quick decision-making.
█ CONCEPT
The indicator measures buying or selling pressure based on candle body size (open-to-close difference) and direction, with optional smoothing for clarity and divergence detection between price action and the oscillator. It relies solely on candle data, offering insights into trend strength, overbought/oversold conditions, and potential reversals with a customizable visual presentation.
█ WHY USE IT?
- Divergence Detection: Identifies bullish and bearish divergences to reinforce signals, especially near overbought/oversold zones.
- Candle Pressure Analysis: Measures pressure based on candle body size, normalized to a ±100 scale.
- Signal Generation: Provides buy/sell signals via overbought/oversold crossovers, zero-line crossovers, moving average zero-line crossovers, and dynamic band color changes.
- Visual Clarity: Uses dynamic colors, gradients, and fill layers for intuitive chart analysis.
Flexibility: Extensive settings allow customization to individual trading preferences.
█ HOW IT WORKS?
- Candle Pressure Calculation: Computes candle body size as math.abs(close - open), normalized against the average body size over a lookback period (avgBody = ta.sma(body, len)). - Candle direction (bullish: +1, bearish: -1, neutral: 0) is multiplied by body weight to derive pressure.
- Cumulative Pressure: Sums pressure values over the lookback period (Lookback Length) and normalizes to ±100 relative to the maximum possible value.
- Smoothing: Optionally applies EMA (Smoothing Length) to normalized pressure.
- Moving Average: Calculates SMA (Moving Average Length) for trend confirmation (Moving Average (SMA)).
- Divergence Detection: Identifies bullish/bearish divergences by comparing price and oscillator pivot highs/lows within a specified range (Pivot Length). Divergence signals appear with a delay equal to the Pivot Length.
- Signals: Generates signals for:
Crossing oversold upward (buy) or overbought downward (sell).
Crossing the zero line by the oscillator or moving average (buy/sell).
Bullish/bearish divergences, marked with labels, enhancing signals, especially near overbought/oversold zones.
Dynamic band color changes when the moving average crosses MA overbought/oversold thresholds (green for oversold, red for overbought).
- Visualization: Plots the oscillator and moving average with dynamic colors, gradient fills, transparent bands, and labels, with customizable overbought/oversold levels.
Alerts: Built-in alerts for divergences, overbought/oversold crossovers, and zero-line crossovers (oscillator and moving average).
█ SETTINGS AND CUSTOMIZATION
- Lookback Length: Period for aggregating candle pressure (default: 14).
- Smoothing Length (EMA): EMA length for smoothing the oscillator (default: 1). Higher values smooth the signal but may reduce signal frequency; adjust overbought/oversold levels accordingly.
- Moving Average Length (SMA): SMA length for the moving average (default: 14, minval=1). Higher values make SMA a trend indicator, requiring adjusted MA overbought/oversold levels.
- Pivot Length (Left/Right): Candles for detecting pivot highs/lows in divergence calculations (default: 2, minval=1). Higher values reduce noise but add delay equal to the set value.
- Enable Divergence Detection: Enables divergence detection (default: true).
- Overbought/Oversold Levels: Thresholds for the oscillator (default: 30/-30) and moving average (default: 10/-10). For the moving average, no arrows appear; bands change color from gray to green (oversold) or red (overbought), reinforcing entry signals.
- Signal Type: Select signals to display: "None", "Overbought/Oversold", "Zero Line", "MA Zero Line", "All" (default: "Overbought/Oversold").
- Colors and Gradients: Customize colors for bullish/bearish oscillator, moving average, zero line, overbought/oversold levels, and divergence labels.
- Transparency: Adjust gradient fill transparency (default: 70, minval=0, maxval=100) and band/label transparency (default: 40, minval=0, maxval=100) for consistent visuals.
- Visualizations: Enable/disable moving average, gradients for zero/overbought/oversold levels, and gradient fills.
█ USAGE EXAMPLES
- Momentum Analysis: Observe the MPO Oscillator above 0 for bullish momentum or below 0 for bearish momentum. The SMA, being smoother, reacts slower and can confirm trend direction as a noise filter.
- Reversal Signals: Look for buy triangles when the oscillator crosses oversold upward, especially when the SMA is below the MA oversold threshold and the band turns green. Similarly, seek sell triangles when crossing overbought downward, with the SMA above the MA overbought threshold and the band turning red.
- Using Divergences: Treat bullish (green labels) and bearish (red labels) divergences as reinforcement for other signals, especially near overbought/oversold zones, indicating stronger potential trend reversals.
- Customization: Adjust lookback length, smoothing, and moving average length to specific instruments and timeframes to minimize false signals.
█ USER NOTES
Combine the indicator with tools like Fibonacci levels or pivot points to enhance accuracy.
Test different settings for lookback length, smoothing, and moving average length on your chosen instrument and timeframe to find optimal values.
BOS + Liquidity Sweep Entries//@version=5
indicator("BOS + Liquidity Sweep Entries (Both Directions) — Fixed", overlay=true, shorttitle="BOS+LS")
// ===== INPUTS =====
swingLen = input.int(5, "Swing lookback", minval=1)
sweepATRmult = input.float(0.5, "Sweep wick threshold (ATR multiplier)", minval=0.0, step=0.1)
maxBarsSinceBOS = input.int(50, "Max bars to wait for sweep after BOS", minval=1)
showLabels = input.bool(true, "Show labels", inline="lbl")
showShapes = input.bool(true, "Show shapes", inline="lbl")
atr = ta.atr(14)
// ===== PIVOTS =====
ph_val = ta.pivothigh(high, swingLen, swingLen)
pl_val = ta.pivotlow(low, swingLen, swingLen)
// persist last pivots and their bar indices
var float lastPH = na
var int lastPH_bar = na
var float lastPL = na
var int lastPL_bar = na
if not na(ph_val)
lastPH := ph_val
lastPH_bar := bar_index - swingLen
if not na(pl_val)
lastPL := pl_val
lastPL_bar := bar_index - swingLen
// ===== BOS DETECTION (record the bar where BOS first confirmed) =====
var int bull_bos_bar = na
bull_bos = not na(lastPH) and close > lastPH and bar_index > lastPH_bar
if bull_bos
// store first confirmation bar (overwrite only if new)
if na(bull_bos_bar) or bar_index > bull_bos_bar
bull_bos_bar := bar_index
var int bear_bos_bar = na
bear_bos = not na(lastPL) and close < lastPL and bar_index > lastPL_bar
if bear_bos
if na(bear_bos_bar) or bar_index > bear_bos_bar
bear_bos_bar := bar_index
// If pivots update to a more recent pivot, clear older BOS/sweep markers that predate the new pivot
if not na(lastPH_bar) and not na(bull_bos_bar)
if bull_bos_bar <= lastPH_bar
bull_bos_bar := na
// clear bull sweep when pivot updates
var int last_bull_sweep_bar = na
if not na(lastPL_bar) and not na(bear_bos_bar)
if bear_bos_bar <= lastPL_bar
bear_bos_bar := na
var int last_bear_sweep_bar = na
// ensure sweep tracking vars exist (declared outside so we can reference later)
var int last_bull_sweep_bar = na
var int last_bear_sweep_bar = na
// ===== SWEEP DETECTION =====
// Bullish sweep: wick above BOS (lastPH) by threshold, then close back below the BOS level
bull_sweep = false
if not na(bull_bos_bar) and not na(lastPH)
bars_since = bar_index - bull_bos_bar
if bars_since <= maxBarsSinceBOS
wick_above = high - lastPH
if (wick_above > sweepATRmult * atr) and (close < lastPH)
bull_sweep := true
last_bull_sweep_bar := bar_index
// Bearish sweep: wick below BOS (lastPL) by threshold, then close back above the BOS level
bear_sweep = false
if not na(bear_bos_bar) and not na(lastPL)
bars_since = bar_index - bear_bos_bar
if bars_since <= maxBarsSinceBOS
wick_below = lastPL - low
if (wick_below > sweepATRmult * atr) and (close > lastPL)
bear_sweep := true
last_bear_sweep_bar := bar_index
// ===== ENTRY RULES (only after sweep happened AFTER BOS) =====
long_entry = false
if not na(last_bull_sweep_bar) and not na(bull_bos_bar)
if (last_bull_sweep_bar > bull_bos_bar) and (bar_index > last_bull_sweep_bar) and (close > lastPH)
long_entry := true
// avoid duplicate triggers from the same sweep
last_bull_sweep_bar := na
short_entry = false
if not na(last_bear_sweep_bar) and not na(bear_bos_bar)
if (last_bear_sweep_bar > bear_bos_bar) and (bar_index > last_bear_sweep_bar) and (close < lastPL)
short_entry := true
// avoid duplicate triggers from the same sweep
last_bear_sweep_bar := na
// ===== PLOTTING LINES =====
plot(lastPH, title="Last Swing High", color=color.orange, linewidth=2, style=plot.style_linebr)
plot(lastPL, title="Last Swing Low", color=color.teal, linewidth=2, style=plot.style_linebr)
// ===== LABELS & SHAPES (managed to avoid label flooding) =====
var label lb_bull_bos = na
var label lb_bear_bos = na
var label lb_bull_sweep = na
var label lb_bear_sweep = na
var label lb_long_entry = na
var label lb_short_entry = na
if showLabels
if bull_bos
if not na(lb_bull_bos)
label.delete(lb_bull_bos)
lb_bull_bos := label.new(bar_index, high, "Bull BOS ✓", yloc=yloc.abovebar, style=label.style_label_up, color=color.green, textcolor=color.white)
if bear_bos
if not na(lb_bear_bos)
label.delete(lb_bear_bos)
lb_bear_bos := label.new(bar_index, low, "Bear BOS ✓", yloc=yloc.belowbar, style=label.style_label_down, color=color.red, textcolor=color.white)
if bull_sweep
if not na(lb_bull_sweep)
label.delete(lb_bull_sweep)
lb_bull_sweep := label.new(bar_index, high, "Bull Sweep", yloc=yloc.abovebar, style=label.style_label_down, color=color.purple, textcolor=color.white)
if bear_sweep
if not na(lb_bear_sweep)
label.delete(lb_bear_sweep)
lb_bear_sweep := label.new(bar_index, low, "Bear Sweep", yloc=yloc.belowbar, style=label.style_label_up, color=color.purple, textcolor=color.white)
if long_entry
if not na(lb_long_entry)
label.delete(lb_long_entry)
lb_long_entry := label.new(bar_index, low, "LONG ENTRY", yloc=yloc.belowbar, style=label.style_label_up, color=color.lime, textcolor=color.black)
if short_entry
if not na(lb_short_entry)
label.delete(lb_short_entry)
lb_short_entry := label.new(bar_index, high, "SHORT ENTRY", yloc=yloc.abovebar, style=label.style_label_down, color=color.red, textcolor=color.white)
// optional shapes (good for quick visual scanning)
if showShapes
plotshape(bull_sweep, title="Bull Sweep Shape", location=location.abovebar, color=color.purple, style=shape.triangledown, size=size.tiny)
plotshape(bear_sweep, title="Bear Sweep Shape", location=location.belowbar, color=color.purple, style=shape.triangleup, size=size.tiny)
plotshape(long_entry, title="Long Shape", location=location.belowbar, color=color.lime, style=shape.triangleup, size=size.small)
plotshape(short_entry, title="Short Shape", location=location.abovebar, color=color.red, style=shape.triangledown, size=size.small)
// ===== ALERTS =====
alertcondition(bull_bos, title="Bullish BOS", message="Bullish BOS confirmed above swing high")
alertcondition(bear_bos, title="Bearish BOS", message="Bearish BOS confirmed below swing low")
alertcondition(bull_sweep, title="Bullish Sweep", message="Liquidity sweep above swing high detected")
alertcondition(bear_sweep, title="Bearish Sweep", message="Liquidity sweep below swing low detected")
alertcondition(long_entry, title="LONG Entry", message="LONG Entry: BOS -> sweep -> reclaim")
alertcondition(short_entry, title="SHORT Entry", message="SHORT Entry: BOS -> sweep -> reclaim")
Volume ClusteringThis Volume Clustering script is a powerful tool for analyzing intraday trading dynamics by combining two key metrics: volume Z-Score and Cumulative Volume Delta (CVD). By categorizing market activity into distinct clusters, it helps you identify high-conviction trading opportunities and understand underlying market pressure.
How It Works
The script operates on a simple, yet effective, premise: it classifies each trading bar based on its statistical significance (volume Z-Score) and buying/selling pressure (CVD).
Volume Z-Score
The volume Z-Score measures how far the current bar's volume is from its average, helping to identify periods of unusually high or low volume. This metric is a powerful way to spot when institutional or large players might be entering the market. A high Z-Score suggests a significant event is taking place, regardless of direction.
Cumulative Volume Delta (CVD)
CVD tracks the net buying and selling pressure across different timeframes. The script uses a lower timeframe (e.g., 1-minute) and anchors it to a higher timeframe (e.g., 1-day) to capture intraday pressure. A positive CVD indicates more buying pressure, while a negative CVD suggests more selling pressure.
Cluster Categories
The script analyzes the confluence of these two metrics to assign a cluster to each bar, providing actionable insights. The clusters are color-coded and labeled to make them easy to interpret:
🟢 High Conviction Bullish: Unusually high volume (high Z-Score) combined with significant buying pressure (high CVD). This cluster suggests strong bullish momentum.
🔴 High Conviction Bearish: Unusually high volume (high Z-Score) coupled with significant selling pressure (low CVD). This cluster suggests strong bearish momentum.
🟡 Low Conviction/Noise: Low to moderate volume and mixed buying/selling pressure. This represents periods of indecision or consolidation, where market noise is more prevalent.
🟣 Other Clusters: The script also identifies other combinations, such as high volume with moderate CVD, or low volume with high CVD, which can provide additional context for understanding market dynamics.
Key Features & Customization
The script offers several customizable settings to tailor the analysis to your specific trading style:
Z-Score Lookback Length: Adjust the lookback period for calculating the average volume. A shorter period focuses on recent volume trends, while a longer period provides a broader context.
CVD Anchor & Lower Timeframe: Define the timeframes used for CVD calculation. You can anchor the analysis to a daily or weekly timeframe while using a lower timeframe (e.g., 1-minute) to capture granular intraday pressure.
High/Low Volume Mode: Toggle between "High Volume" mode (which uses 90th and 10th percentiles for clustering) and "Low Volume" mode (which uses 75th and 25th percentiles). This allows you to choose whether to focus on extreme events or more subtle shifts in market sentiment.
Katz Impact Wave 🚀Overview of the Katz Impact Wave 🚀
The Katz Impact Wave is a momentum oscillator designed to visualize the battle between buyers and sellers. Instead of combining bullish and bearish pressure into a single line, it separates them into two distinct "Impact Waves."
Its primary goal is to generate clear trade signals by identifying when one side gains control, but only when the market has enough volatility to be considered "moving." This built-in filter helps to avoid signals during flat or choppy market conditions.
Indicator Components: Lines & Plots
Impact Waves & Fill
Green Wave (Total Up Impulses): This line represents the cumulative buying pressure. When this line is rising, it indicates that bulls are getting stronger.
Red Wave (Total Down Impulses): This line represents the cumulative selling pressure. When this line is rising, it indicates that bears are getting stronger.
Colored Fill: The shaded area between the two waves provides an at-a-glance view of who is in control.
Lime Fill: Bulls are dominant (Green Wave is above the Red Wave).
Red Fill: Bears are dominant (Red Wave is above the Green Wave).
Background Color
The background color provides crucial context about the market state according to the indicator's logic.
Green Background: The market is in a bullish state (Green Wave is dominant) AND the Rate of Change (ROC) filter confirms the market is actively moving.
Red Background: The market is in a bearish state (Red Wave is dominant) AND the ROC filter confirms the market is actively moving.
Gray Background: The market is considered "not moving" or is in a low-volatility chop. Signals that occur when the background is gray should be viewed with extreme caution or ignored.
Symbols & Pivot Lines
▲ Blue Triangle (Up): This is your long entry signal. It appears on the bar where the Green Wave crosses above the Red Wave while the market is moving.
▼ Orange Triangle (Down): This is your short entry signal. It appears on the bar where the Red Wave crosses above the Green Wave while the market is moving.
Pivot Lines (Solid Green/Red/White Lines): These lines mark confirmed peaks of exhaustion in momentum, not price.
Green Pivot Line: Marks a peak in the Green Wave, signaling buying momentum exhaustion. This can be a warning that the uptrend is losing steam.
Red Pivot Line: Marks a peak in the Red Wave, signaling selling momentum exhaustion. This can be a warning that the downtrend is losing steam.
▼ Yellow Triangle (Compression): This rare signal appears when buying and selling exhaustion pivots happen at the same level. It signifies a point of extreme indecision or equilibrium that often occurs before a major price expansion.
Trading Rules & Strategy
This indicator provides entry signals but does not provide explicit Take Profit or Stop Loss levels. You must use your own risk management rules.
Long Trade Rules
Entry Signal: Wait for a blue ▲ triangle to appear at the top of the indicator panel.
Confirmation: Ensure the background color is green, confirming the market is in a bullish, moving state.
Action: Enter a long (buy) trade at the open of the next candle after the signal appears.
Short Trade Rules
Entry Signal: Wait for an orange ▼ triangle to appear at the bottom of the indicator panel.
Confirmation: Ensure the background color is red, confirming the market is in a bearish, moving state.
Action: Enter a short (sell) trade at the open of the next candle after the signal appears.
Take Profit (TP) & Stop Loss (SL) Ideas
You must develop and test your own exit strategy. Here are some common approaches:
Stop Loss:
Place a stop loss below the most recent significant swing low on the price chart for a long trade, or above the recent swing high for a short trade.
Use an ATR (Average True Range) based stop, such as 2x the ATR value below your entry for a long, to account for market volatility.
Take Profit:
Opposite Signal: The simplest exit is to close your trade when the opposite signal appears (e.g., close a long trade when a short signal ▼ appears).
Momentum Exhaustion: For a long trade, consider taking partial or full profit when a green Pivot Line appears, signaling that buying momentum is peaking.
Fixed Risk/Reward: Use a predetermined risk/reward ratio (e.g., 1:1.5 or 1:2).
Disclaimer
This indicator is a tool for analysis, not a financial advisor or a guaranteed profit system. All trading and investment activities involve substantial risk. You should not risk more than you are prepared to lose. Past performance is not an indication of future results. You are solely responsible for your own trading decisions, risk management, and for backtesting this or any other tool before using it in a live trading environment. This indicator is for educational purposes only.
Katz Exploding PowerBand FilterUnderstanding the Katz Exploding PowerBand Filter (EPBF) v2.4
1. Indicator Overview
The Katz Exploding PowerBand Filter (EPBF) is an advanced technical indicator designed to identify moments of expanding bullish or bearish momentum, often referred to as "power." It operates as a standalone oscillator in a separate pane below the main price chart.
Its primary goal is to measure underlying market strength by calculating custom "Bull" and "Bear" power components. These components are then filtered through a versatile moving average and a dual signal line system to generate clear entry and exit signals. This indicator is not a simple momentum oscillator; it uses a unique calculation based on exponential envelopes of both price and squared price to derive its values.
2. On-Chart Lines and Components
The indicator pane consists of five main lines:
Bullish Component (Thick Green/Blue/Yellow/Gray Line): This is the core of the indicator. It represents the calculated bullish "power" or momentum in the market.
Bright Green: Indicates a strong, active long signal condition.
Blue: Shows the bull component is above the MA filter, but the filter itself is still pointing down—a potential sign of a reversal or weakening downtrend.
Yellow: A warning sign that bullish power is weakening and has fallen below the primary signal lines.
Gray: Represents neutral or insignificant bullish power.
Bearish Component (Thick Red/Purple/Yellow/Gray Line): This line represents the calculated bearish "power" or downward momentum.
Bright Red: Indicates a strong, active short signal condition.
Purple: Shows the bear component is above the MA filter, but the filter itself is still pointing down—a sign of potential trend continuation.
Yellow: A warning sign that bearish power is weakening.
Gray: Represents neutral or insignificant bearish power.
MA Filter (Purple Line): This is the main filter, calculated using the moving average type and length you select in the settings (e.g., HullMA, EMA). The Bull and Bear components are compared against this line to determine the underlying trend bias.
Signal Line 1 (Orange Line): A fast Exponential Moving Average (EMA) of the stronger power component. It acts as the first level of dynamic support or resistance for the power lines.
Signal Line 2 (Lime/Gray Line): A slower EMA that acts as a confirmation filter.
Lime Green: The line turns lime when it is rising and the faster Signal Line 1 is above it, indicating a confirmed bullish trend in momentum.
Gray: Indicates a neutral or bearish momentum trend.
3. On-Chart Symbols and Their Meanings
Various characters are plotted at the bottom of the indicator pane to provide clear, actionable signals.
L (Pre-Long Signal): The first sign of a potential long entry. It appears when the Bullish Component rises and crosses above both signal lines for the first time.
S (Pre-Short Signal): The first sign of a potential short entry. It appears when the Bearish Component rises and crosses above both signal lines for the first time.
▲ (Post-Long Signal): A stronger confirmation for a long entry. It appears with the 'L' signal only if the momentum trend is also confirmed bullish (i.e., the slower Signal Line 2 is lime green).
▼ (Post-Short Signal): A stronger confirmation for a short entry. It appears with the 'S' signal only if the momentum trend is confirmed bullish.
Exit / Take-Profit Symbols:
These symbols appear when a power component crosses below a line, suggesting that momentum is fading and it may be time to take profit.
⚠️ (Exit Signal 1): The Bull/Bear component has crossed below the main MA Filter. This is the first and most sensitive take-profit signal.
☣️ (Exit Signal 2): The Bull/Bear component has crossed below the faster Signal Line 1. This is a moderate take-profit signal.
🚼 (Exit Signal 3): The Bull/Bear component has crossed below the slower Signal Line 2. This is the slowest take-profit signal, suggesting the trend is more definitively exhausted.
4. Trading Strategy and Rules
Long Entry Rules:
Initial Signal: Wait for an L to appear at the bottom of the indicator. This confirms that bullish power is expanding.
Confirmation (Recommended): For a higher-probability trade, wait for a green ▲ symbol to appear. This confirms the underlying momentum trend aligns with the signal.
Entry: Enter a long (buy) position on the opening of the next candle after the signal appears.
Short Entry Rules:
Initial Signal: Wait for an S to appear at the bottom of the indicator. This confirms that bearish power is expanding.
Confirmation (Recommended): For a higher-probability trade, wait for a maroon ▼ symbol to appear. This confirms the underlying momentum trend aligns with the signal.
Entry: Enter a short (sell) position on the opening of the next candle after the signal appears.
Take Profit (TP) Rules:
The indicator provides three levels of take-profit signals. You can choose to exit your entire position or scale out at each level.
For a long trade, exit when you see ⚠️, ☣️, or 🚼 appear below the Bullish Component.
For a short trade, exit when you see ⚠️, ☣️, or 🚼 appear below the Bearish Component.
Stop Loss (SL) Rules:
The indicator does not provide an explicit stop loss. You must use your own risk management rules. Common methods include:
Swing High/Low: For a long position, place your stop loss below the most recent significant swing low on the price chart. For a short position, place it above the most recent swing high.
ATR-Based: Use an Average True Range (ATR) indicator to set a volatility-based stop loss.
Fixed Percentage: Risk a fixed percentage (e.g., 1-2%) of your account on the trade.
5. Disclaimer
This indicator is a tool for technical analysis and should not be considered financial advice. All trading involves significant risk, and past performance is not indicative of future results. The signals generated by this indicator are probabilistic and can result in losing trades. Always use proper risk management, such as setting a stop loss, and never risk more than you are willing to lose. It is recommended to backtest this indicator and use it in conjunction with other forms of analysis before trading with real capital. The indicator should only be used for educational purposes.
Combined Cluster & Market StructureI barrowed code from the Mxwll Price Action Suite script as appreciated the structure in which the script defined structure, however I renamed variables and reduced the original script to define only the outer structure. I added volume and CVD clustering to define ranges and initiation market structures and add the ADX to assist with determining trend strength prior to labeling market structure breaks.
Combined Cluster & Market Structure indicator, a powerful and comprehensive tool for technical analysis. This script integrates two core concepts to provide a holistic view of market dynamics:
Z-Score Clustering & Volume Analysis: The indicator calculates Z-scores for both volume and Cumulative Volume Delta (CVD) to categorize market activity into six distinct clusters:
High-Conviction Bullish/Bearish: Signals of strong directional momentum based on high volume and corresponding CVD.
Effort vs. Result: High volume with moderate CVD, suggesting potential indecision or absorption.
Quiet Accumulation/Distribution: Low-volume periods with strong CVD, often preceding major moves.
Low Conviction/Noise: Represents periods of low market participation and weak signals.
These clusters are visually marked on the chart to provide real-time insight into market sentiment.
Market Structure Mapping: The indicator automatically detects and labels significant structural points to help you navigate price action. It identifies:
Higher Highs (HH) and Lower Lows (LL) to show the primary trend direction.
Breaks of Structure (BoS), indicating trend continuation.
Changes of Character (CHoCH), signaling a potential trend reversal.
Additionally, the script features consolidation box detection, which automatically highlights periods of low-conviction market activity, helping you avoid choppy, sideways markets. An integrated ADX filter ensures that structural breaks are only labeled during periods of strong trend strength, reducing false signals.
I want to thank Mxwll Capital for their contribution to the Combined Cluster & Market Structure indicator.
Andean Oscillator (Version 3.0 Sr.K)Andean Oscillator (Version 3.0 Sr.K)
This indicator is a momentum-based oscillator that measures the balance between bullish and bearish pressure.
🔧 How it works:
It calculates two adaptive envelopes around price and derives a "bullish" and "bearish" component.
The oscillator value is simply Bull - Bear, showing which side dominates.
A signal line (EMA of the oscillator) smooths the raw value.
Optionally, ±1σ levels are plotted to highlight statistically strong moves.
📊 What you see:
Histogram: Positive bars = bullish momentum, negative bars = bearish.
Orange Line: Signal line (EMA) used to confirm or anticipate reversals.
Zero Line: The equilibrium point. Crosses of this level signal a shift in market bias.
Green / Red Triangles: Buy and sell signals, either when crossing zero or crossing the signal line (depending on selected mode).
⚡ Early Signal Mode:
When enabled, signals trigger earlier — at the crossover between the oscillator and its signal line — allowing traders to enter potential reversals before a full zero-cross confirmation.
✅ Use cases:
Identify momentum shifts before price reversals.
Spot potential long/short setups with reduced lag.
Combine with price action or support/resistance for confirmation.
⚠️ Note: This is a tool for discretionary/manual trading. It does not open or close trades automatically. Always confirm with your own analysis and risk management.
BioSwarm Imprinter™BioSwarm Imprinter™ — Agent-Based Consensus for Traders
What it is
BioSwarm Imprinter™ is a non-repainting, agent-based sentiment oscillator. It fuses many short-to-medium lookback “opinions” into one 0–100 consensus line that is easy to read at a glance (50 = neutral, >55 bullish bias, <45 bearish bias). The engine borrows from swarm intelligence: many simple voters (agents) adapt their influence over time based on how well they’ve been predicting price, so the crowd gets smarter as conditions change.
Use it to:
• Detect emerging trends sooner without overreacting to noise.
• Filter mean-reversion vs continuation opportunities.
• Gate entries with a confidence score that reflects both strength and persistence of the move.
• Combine with your execution tools (VWAP/ORB/levels) as a state filter rather than a trade signal by itself.
⸻
Why it’s different
• Swarm learning: Each agent improves or decays its “fitness” depending on whether its vote matched the next bar’s direction. High-fitness agents matter more; weak agents fade.
• Multi-horizon by design: The crowd is composed of fixed, simple lookbacks spread from lenMin to lenMax. You get a blended, robust view instead of a single fragile parameter.
• Two complementary lenses: Each agent evaluates RSI-style balance (via Wilder’s RMA) and momentum (EMA deviation). You decide the weight of each.
• No repaint, no MTF pitfalls: Everything runs on the chart’s timeframe with bar-close confirmation; no request.security() or forward references.
• Actionable UI: A clean consensus line, optional regime background, confidence heat, and triangle markers when thresholds are crossed.
⸻
What you see on the chart
• Consensus line (0–100): Smoothed to your preference; color/area makes bull/bear zones obvious.
• Regime coloring (optional): Light green in bull zone, light red in bear zone; neutral otherwise.
• Confidence heat: A small gauge/number (0–100) that combines distance from neutral and recent persistence.
• Markers (optional): Triangles when consensus crosses up through your bull threshold (e.g., 55) or down through your bear threshold (e.g., 45).
• Info panel (optional): Consensus value, regime, confidence, number of agents, and basic diagnostics.
⸻
How it works (under the hood)
1. Horizon bins: The range is divided into numBins. Each bin has a fixed, simple integer length (crucial for Pine’s safety rules).
2. Per-bin features (computed every bar):
• RSI-style balance using Wilder’s RMA (not ta.rsi()), then mapped to −1…+1.
• Momentum as (close − EMA(L)) / EMA(L) (dimensionless drift).
3. Agent vote: For its assigned bin, an agent forms a weighted score: score = wRSI*RSI_like + wMOM*Momentum. A small dead-band near zero suppresses chop; votes are +1/−1/0.
4. Fitness update (bar close): If the agent’s previous vote agreed with the next bar’s direction, multiply its fitness by learnGain; otherwise by learnPain. Fitness is clamped so it never explodes or dies.
5. Consensus: Weighted average of all votes using fitness as weights → map to 0–100 and smooth with EMA.
Why it doesn’t repaint:
• No future references, no MTF resampling, fitness updates only on confirmed bars.
• All TA primitives (RMA/EMA/deltas) are computed every bar unconditionally.
⸻
Signals & confidence
• Bullish bias: consensus ≥ bullThr (e.g., 55).
• Bearish bias: consensus ≤ bearThr (e.g., 45).
• Confidence (0–100):
• Distance score: how far consensus is from 50.
• Momentum score: how strong the recent change is versus its recent average.
• Combined into a single gate; start filtering entries at ≥60 for higher quality.
Tip: For range sessions, raise thresholds (60/40) and increase smoothing; for momentum sessions, lower smoothing and keep thresholds at 55/45.
⸻
Inputs you’ll actually tune
• Agents & horizons:
• N_agents (e.g., 64–128)
• lenMin / lenMax (e.g., 6–30 intraday, 10–60 swing)
• numBins (e.g., 12–24)
• Weights & smoothing:
• wRSI vs wMOM (e.g., 0.7/0.3 for FX & indices; 0.6/0.4 for crypto)
• deadBand (0.03–0.08)
• consSmooth (3–8)
• Thresholds & hygiene:
• bullThr/bearThr (55/45 default)
• cooldownBars to avoid signal spam
⸻
Playbooks (ready-to-use)
1) Breakout / Trend continuation
• Timeframe: 15m–1h for day/swing.
• Filter: Take longs only when consensus > 55 and confidence ≥ 60.
• Execution: Use your ORB/VWAP/pullback trigger for entry. Trail with swing lows or 1.5×ATR. Exit on a close back under 50 or when a bearish signal prints.
2) Mean reversion (fade)
• When: Sideways days or low-volatility clusters.
• Setup: Increase deadBand and consSmooth.
• Signal: Bearish fades when consensus rolls over below ≈55 but stays above 50; bullish fades when it rolls up above ≈45 but stays below 50.
• Targets: The neutral zone (~50) as the first take-profit.
3) Multi-TF alignment
• Keep BioSwarm on 1H for bias, execute on 5–15m:
• Only take entries in the direction of the 1H consensus.
• Skip counter-bias scalps unless confidence is very low (explicit mean-reversion plan).
⸻
Integrations that work
• DynamoSent Pro+ (macro bias): Only act when macro bias and swarm consensus agree.
• ORB + Session VWAP Pro: Trade London/NY ORB breakouts that retest while consensus >55 (long) or <45 (short).
• Levels/Orderflow: BioSwarm is your “go / no-go”; execution stays with your usual triggers.
⸻
Quick start
1. Drop the indicator on a 1H chart.
2. Start with: N_agents=64, lenMin=6, lenMax=30, numBins=16, deadBand=0.06, consSmooth=5, thresholds 55/45.
3. Trade only when confidence ≥ 60.
4. Add your favorite execution tool (VWAP/levels/OR) for entries & exits.
⸻
Non-repainting & safety notes
• No request.security(); no hidden lookahead.
• Bar-close confirmation for fitness and signals.
• All TA calls are unconditional (no “sometimes called” warnings).
• No series-length inputs to RSI/EMA — we use RMA/EMA formulas that accept fixed simple ints per bin.
⸻
Known limits & tips
• Too many signals? Raise deadBand, increase consSmooth, widen thresholds to 60/40.
• Too few signals? Lower deadBand, reduce consSmooth, narrow thresholds to 53/47.
• Over-fitting risk: Keep learnGain/learnPain modest (e.g., ×1.04 / ×0.96).
• Compute load: Large N_agents × numBins is heavier; scale to your device.
⸻
Example recipes
EURUSD 1H (swing):
lenMin=8, lenMax=34, numBins=16, wRSI=0.7, wMOM=0.3, deadBand=0.06, consSmooth=6, thr=55/45
Buy breakouts when consensus >55 and confidence ≥60; confirm with 5–15m pullback to VWAP or level.
SPY 15m (US session):
lenMin=6, lenMax=24, numBins=12, consSmooth=4, deadBand=0.05
On trend days, stay with longs as long as consensus >55; add on shallow pullbacks.
BTC 1H (24/7):
Increase momentum weight: wRSI=0.6, wMOM=0.4, extend lenMax to ~50. Use dynamic stops (ATR) and partials on strong verticals.
⸻
Final word
BioSwarm is a state engine: it tells you when the market is primed to continue or mean-revert. Pair it with your entries and risk framework to turn that state into trades. If you’d like, I can supply a companion strategy template that consumes the consensus and back-tests the three playbooks (Breakout/Fade/Flip) with standard risk management.
Supertrend DashboardOverview
This dashboard is a multi-timeframe technical indicator dashboard based on Supertrend. It combines:
Trend detection via Supertrend
Momentum via RSI and OBV (volume)
Volatility via a basic candle-based metric (bs)
Trend strength via ADX
Multi-timeframe analysis to see whether the trend is bullish across different timeframes
It then displays this info in a table on the chart with colors for quick visual interpretation.
2️⃣ Inputs
Dashboard settings:
enableDashboard: Toggle the dashboard on/off
locationDashboard: Where the table appears (Top right, Bottom left, etc.)
sizeDashboard: Text size in the table
strategyName: Custom name for the strategy
Indicator settings:
factor (Supertrend factor): Controls how far the Supertrend lines are from price
atrLength: ATR period for Supertrend calculation
rsiLength: Period for RSI calculation
Visual settings:
colorBackground, colorFrame, colorBorder: Control dashboard style
3️⃣ Core Calculations
a) Supertrend
Supertrend is a trend-following indicator that generates bullish or bearish signals.
Logic:
Compute ATR (atr = ta.atr(atrLength))
Compute preliminary bands:
upperBand = src + factor * atr
lowerBand = src - factor * atr
Smooth bands to avoid false flips:
lowerBand := lowerBand > prevLower or close < prevLower ? lowerBand : prevLower
upperBand := upperBand < prevUpper or close > prevUpper ? upperBand : prevUpper
Determine direction (bullish / bearish):
dir = 1 → bullish
dir = -1 → bearish
Supertrend line = lowerBand if bullish, upperBand if bearish
Output:
st → line to plot
bull → boolean (true = bullish)
b) Buy / Sell Trigger
Logic:
bull = ta.crossover(close, supertrend) → close crosses above Supertrend → buy signal
bear = ta.crossunder(close, supertrend) → close crosses below Supertrend → sell signal
trigger → checks which signal was most recent:
trigger = ta.barssince(bull) < ta.barssince(bear) ? 1 : 0
1 → Buy
0 → Sell
c) RSI (Momentum)
rsi = ta.rsi(close, rsiLength)
Logic:
RSI > 50 → bullish
RSI < 50 → bearish
d) OBV / Volume Trend (vosc)
OBV tracks whether volume is pushing price up or down.
Manual calculation (safe for all Pine versions):
obv = ta.cum( math.sign( nz(ta.change(close), 0) ) * volume )
vosc = obv - ta.ema(obv, 20)
Logic:
vosc > 0 → bullish
vosc < 0 → bearish
e) Volatility (bs)
Measures how “volatile” the current candle is:
bs = ta.ema(math.abs((open - close) / math.max(high - low, syminfo.mintick) * 100), 3)
Higher % → stronger candle moves
Displayed on dashboard as a number
f) ADX (Trend Strength)
= ta.dmi(14, 14)
Logic:
adx > 20 → Trending
adx < 20 → Ranging
g) Multi-Timeframe Supertrend
Timeframes: 1m, 3m, 5m, 10m, 15m, 30m, 1H, 2H, 4H, 12H, 1D
Logic:
for tf in timeframes
= request.security(syminfo.tickerid, tf, f_supertrend(ohlc4, factor, atrLength))
array.push(tf_bulls, bull_tf ? 1.0 : 0.0)
bull_tf ? 1.0 : 0.0 → converts boolean to number
Then we calculate user rating:
userRating = (sum of bullish timeframes / total timeframes) * 10
0 → Strong Sell, 10 → Strong Buy
4️⃣ Dashboard Table Layout
Row Column 0 (Label) Column 1 (Value)
0 Strategy strategyName
1 Technical Rating textFromRating(userRating) (color-coded)
2 Current Signal Buy / Sell (based on last Supertrend crossover)
3 Current Trend Bullish / Bearish (based on Supertrend)
4 Trend Strength bs %
5 Volume vosc → Bullish/Bearish
6 Volatility adx → Trending/Ranging
7 Momentum RSI → Bullish/Bearish
8 Timeframe Trends 📶 Merged cell
9-19 1m → Daily Bullish/Bearish for each timeframe (green/red)
5️⃣ Color Logic
Green shades → bullish / trending / buy
Red / orange → bearish / weak / sell
Yellow → neutral / ranging
Example:
dashboard_cell_bg(1, 1, colorFromRating(userRating))
dashboard_cell_bg(1, 2, trigger ? color.green : color.red)
dashboard_cell_bg(1, 3, superBull ? color.green : color.red)
Makes the dashboard visually intuitive
6️⃣ Key Logic Flow
Calculate Supertrend on current timeframe
Detect buy/sell triggers based on crossover
Calculate RSI, OBV, Volatility, ADX
Request Supertrend on multiple timeframes → convert to 1/0
Compute user rating (percentage of bullish timeframes)
Populate dashboard table with colors and values
✅ The result: You get a compact, fast, multi-timeframe trend dashboard that shows:
Current signal (Buy/Sell)
Current trend (Bullish/Bearish)
Momentum, volatility, and volume cues
Trend across multiple timeframes
Overall technical rating
It’s essentially a full trend-strength scanner directly on your chart.
My script//@version=6
strategy("Elite Option Signal Strategy", overlay=true, default_qty_type=strategy.percent_of_equity, default_qty_value=10)
// === INPUTS ===
fastLength = input.int(9, title="Fast MA Length")
slowLength = input.int(21, title="Slow MA Length")
trendLength = input.int(50, title="Trend MA Length")
rsiLength = input.int(14, title="RSI Length")
rsiOversold = input.int(30, title="RSI Oversold Level")
rsiOverbought = input.int(70, title="RSI Overbought Level")
useStopLoss = input.bool(true, title="Use Stop Loss?")
stopLossPercent = input.float(2.0, title="Stop Loss %", minval=0.1, maxval=10.0)
// === INDICATORS ===
fastMA = ta.sma(close, fastLength)
slowMA = ta.sma(close, slowLength)
trendMA = ta.sma(close, trendLength)
rsi = ta.rsi(close, rsiLength)
// === CONDITIONS ===
bullishTrend = close > trendMA
bearishTrend = close < trendMA
longCondition = ta.crossover(fastMA, slowMA) and bullishTrend and rsi < rsiOverbought
shortCondition = ta.crossunder(fastMA, slowMA) and bearishTrend and rsi > rsiOversold
// === EXECUTION ===
if longCondition
strategy.entry("Long", strategy.long)
if useStopLoss
strategy.exit("Exit Long", "Long", stop=close * (1 - stopLossPercent / 100))
if shortCondition
strategy.entry("Short", strategy.short)
if useStopLoss
strategy.exit("Exit Short", "Short", stop=close * (1 + stopLossPercent / 100))
// === PLOTS ===
plot(fastMA, color=color.green, title="Fast MA")
plot(slowMA, color=color.red, title="Slow MA")
plot(trendMA, color=color.blue, title="Trend MA")
plotshape(longCondition, title="Buy Signal", location=location.belowbar, color=color.green, style=shape.triangleup)
plotshape(shortCondition, title="Sell Signal", location=location.abovebar, color=color.red, style=shape.triangledown)
Wickless Heikin Ashi B/S [CHE]Wickless Heikin Ashi B/S \
Purpose.
Wickless Heikin Ashi B/S \ is built to surface only the cleanest momentum turns: it prints a Buy (B) when a bullish Heikin-Ashi candle forms with virtually no lower wick, and a Sell (S) when a bearish Heikin-Ashi candle forms with no upper wick. Optional Lock mode turns these into one-shot signals that hold the regime (bull or bear) until the opposite side appears. The tool can also project dashed horizontal lines from each signal’s price level to help you manage entries, stops, and partial take-profits visually.
How it works.
The indicator computes standard Heikin-Ashi values from your chart’s OHLC. A bar qualifies as bullish if its HA close is at or above its HA open; bearish if below. Then the wick on the relevant side is compared to the bar’s HA range. If that wick is smaller than your selected percentage threshold (plus a tiny tick epsilon to avoid rounding noise), the raw condition is considered “wickless.” Only one side can fire; on the rare occasion both raw conditions would overlap, the bar is ignored to prevent false dual triggers. When Lock is enabled, the first valid signal sets the active regime (background shaded light green for bull, light red for bear) and suppresses further same-side triggers until the opposite side appears, which helps reduce overtrading in chop.
Why wickless?
A missing wick on the “wrong” side of a Heikin-Ashi candle is a strong hint of persistent directional pressure. In practice, this filters out hesitation bars and many mid-bar flips. Traders who prefer entering only when momentum is decisive will find wickless bars useful for timing entries within an established bias.
Visuals you get.
When a valid buy appears, a small triangle “B” is plotted below the bar and a green dashed line can extend to the right from the signal’s HA open price. For sells, a triangle “S” above the bar and a red dashed line do the same. These lines act like immediate, price-anchored references for stop placement and profit scaling; you can shift the anchor left by a chosen number of bars if you prefer the line to start a little earlier for visual alignment.
How to trade it
Establish context first.
Pick a timeframe that matches your style: intraday index or crypto traders often use 5–60 minutes; swing traders might prefer 2–4 hours or daily. The tool is agnostic, but the cleanest results occur when the market is already trending or attempting a fresh breakout.
Entry.
When a B prints, the simplest rule is to enter long at or just after bar close. A conservative variation is to require price to take out the high of the signal bar in the next bar(s). For S, invert the logic: enter short on or after close, or only if price breaks the signal bar’s low.
Stop-loss.
Place the stop beyond the opposite extreme of the signal HA bar (for B: under the HA low; for S: above the HA high). If you prefer a static reference, use the dashed line level (signal HA open) or an ATR buffer (e.g., 1.0–1.5× ATR(14)). The goal is to give the trade enough room that normal noise does not immediately knock you out, while staying small enough to keep the risk contained.
Take-profit and management.
Two pragmatic approaches work well:
R-multiple scaling. Define your initial risk (distance from entry to stop). Scale out at 1R, 2R, and let a runner go toward 3R+ if structure holds.
Trailing logic. Trail behind a short moving average (e.g., EMA 20) or progressive swing points. Many traders also exit on the opposite signal when Lock flips, especially on faster timeframes.
Position sizing.
Keep risk per trade modest and consistent (e.g., 0.25–1% of account). The indicator improves timing; it does not replace risk control.
Settings guidance
Max lower wick for Bull (%) / Max upper wick for Bear (%).
These control how strict “wickless” must be. Tighter values (0.3–1.0%) yield fewer but cleaner signals and are great for strong trends or low-noise instruments. Looser values (1.5–3.0%) catch more setups in volatile markets but admit more noise. If you notice too many borderline bars triggering during high-volatility sessions, increase these thresholds slightly.
Lock (one-shot until opposite).
Keep Lock ON when you want one decisive signal per leg, reducing noise and signal clusters. Turn it OFF only if your plan intentionally scales into trends with multiple entries.
Extended lines & anchor offset.
Leave lines ON to maintain a visual memory of the last trigger levels. These often behave like near-term support/resistance. The offset simply lets you start that line one or more bars earlier if you prefer the look; it does not change the math.
Colors.
Use distinct bull/bear line colors you can read easily on your theme. The default lime/red scheme is chosen for clarity.
Practical examples
Momentum continuation (long).
Price is above your baseline (e.g., EMA 200). A B prints with a tight lower wick filter. Enter on close; stop under the signal HA low. Price pushes up in the next bars; you scale at 1R, trail the rest with EMA 20, and finally exit when a distant S appears or your trail is hit.
Breakout confirmation (short).
Following a range, price breaks down and prints an S with no upper wick. Enter short as the bar closes or on a subsequent break of the signal bar’s low. If the next bar immediately rejects and prints a bullish HA bar, your stop above the signal HA high limits damage. Otherwise, ride the move, harvesting partials as the red dashed line remains unviolated.
Alerts and automation
Set alerts to “Once Per Bar Close” for stability.
Bull ONE-SHOT fires when a valid buy prints (and Lock allows it).
Bear ONE-SHOT fires for sells analogously.
With Lock enabled, you avoid multiple pings in the same direction during a single leg—useful for webhooks or mobile notifications.
Reliability and limitations
The script calculates from completed bars and does not use higher-timeframe look-ahead or repainting tricks. Heikin-Ashi smoothing can lag turns slightly, which is expected and part of the design. In narrow ranges or whipsaw conditions, signals naturally thin out; if you must trade ranges, either tighten the wick filters and keep Lock ON, or add a trend/volatility filter (e.g., trade B only above EMA 200; S only below). Remember: this is an indicator, not a strategy. If you want exact statistics, port the triggers into a strategy and backtest with your chosen entry, stop, and exit rules.
Final notes
Wickless Heikin Ashi B/S \ is a precision timing tool: it waits for decisive, wickless HA bars, provides optional regime locking to reduce noise, and leaves clear price anchors on your chart for disciplined management. Use it with a simple framework—trend bias, fixed risk, and a straightforward exit plan—and it will keep your execution consistent without cluttering the screen or your decision-making.
Disclaimer: This indicator is for educational use and trade assistance only. It is not financial advice. You alone are responsible for your risk and results.
Enhance your trading precision and confidence with Wickless Heikin Ashi B/S ! 🚀
Happy trading
Chervolino
Structural Liquidity Signals [BullByte]Structural Liquidity Signals (SFP, FVG, BOS, AVWAP)
Short description
Detects liquidity sweeps (SFPs) at pivots and PD/W levels, highlights the latest FVG, tracks AVWAP stretch, arms percentile extremes, and triggers after confirmed micro BOS.
Full description
What this tool does
Structural Liquidity Signals shows where price likely tapped liquidity (stop clusters), then waits for structure to actually change before it prints a trigger. It spots:
Liquidity sweeps (SFPs) at recent pivots and at prior day/week highs/lows.
The latest Fair Value Gap (FVG) that often “pulls” price or serves as a reaction zone.
How far price is stretched from two VWAP anchors (one from the latest impulse, one from today’s session), scaled by ATR so it adapts to volatility.
A “percentile” extreme of an internal score. At extremes the script “arms” a setup; it only triggers after a small break of structure (BOS) on a closed bar.
Originality and design rationale, why it’s not “just a mashup”
This is not a mashup for its own sake. It’s a purpose-built flow that links where liquidity is likely to rest with how structure actually changes:
- Liquidity location: We focus on areas where stops commonly cluster—recent pivots and prior day/week highs/lows—then detect sweeps (SFPs) when price wicks beyond and closes back inside.
- Displacement context: We track the last Fair Value Gap (FVG) to account for recent inefficiency that often acts as a magnet or reaction zone.
- Stretch measurement: We anchor VWAP to the latest N-bar impulse and to the Daily session, then normalize stretch by ATR to assess dislocation consistently across assets/timeframes.
- Composite exhaustion: We combine stretch, wick skew, and volume surprise, then bend the result with a tanh transform so extremes are bounded and comparable.
- Dynamic extremes and discipline: Rather than triggering on every sweep, we “arm” at statistical extremes via percent-rank and only fire after a confirmed micro Break of Structure (BOS). This separates “interesting” from “actionable.”
Key concepts
SFP (liquidity sweep): A candle briefly trades beyond a level (where stops sit) and closes back inside. We detect these at:
Pivots (recent swing highs/lows confirmed by “left/right” bars).
Prior Day/Week High/Low (PDH/PDL/PWH/PWL).
FVG (Fair Value Gap): A small 3‑bar gap (bar2 high vs bar1 low, or vice versa). The latest gap often acts like a magnet or reaction zone. We track the most recent Up/Down gap and whether price is inside it.
AVWAP stretch: Distance from an Anchored VWAP divided by ATR (volatility). We use:
Impulse AVWAP: resets on each new N‑bar high/low.
Daily AVWAP: resets each new session.
PR (Percentile Rank): Where the current internal score sits versus its own recent history (0..100). We arm shorts at high PR, longs at low PR.
Micro BOS: A small break of the recent high (for longs) or low (for shorts). This is the “go/no‑go” confirmation.
How the parts work together
Find likely liquidity grabs (SFPs) at pivots and PD/W levels.
Add context from the latest FVG and AVWAP stretch (how far price is from “fair”).
Build a bounded score (so different markets/timeframes are comparable) and compute its percentile (PR).
Arm at extremes (high PR → short candidate; low PR → long candidate).
Only print a trigger after a micro BOS, on a closed bar, with spacing/cooldown rules.
What you see on the chart (legend)
Lines:
Teal line = Impulse AVWAP (resets on new N‑bar extreme).
Aqua line = Daily AVWAP (resets each session).
PDH/PDL/PWH/PWL = prior day/week levels (toggle on/off).
Zones:
Greenish box = latest Up FVG; Reddish box = latest Down FVG.
The shading/border changes after price trades back through it.
SFP labels:
SFP‑P = SFP at Pivot (dotted line marks that pivot’s price).
SFP‑L = SFP at Level (at PDH/PDL/PWH/PWL).
Throttle: To reduce clutter, SFPs are rate‑limited per direction.
Triggers:
Triangle up = long trigger after BOS; triangle down = short trigger after BOS.
Optional badge shows direction and PR at the moment of trigger.
Optional Trigger Zone is an ATR‑sized box around the trigger bar’s close (for visualization only).
Background:
Light green/red shading = a long/short setup is “armed” (not a trigger).
Dashboard (Mini/Pro) — what each item means
PR: Percentile of the internal score (0..100). Near 0 = bullish extreme, near 100 = bearish extreme.
Gauge: Text bar that mirrors PR.
State: Idle, Armed Long (with a countdown), or Armed Short.
Cooldown: Bars remaining before a new setup can arm after a trigger.
Bars Since / Last Px: How long since last trigger and its price.
FVG: Whether price is in the latest Up/Down FVG.
Imp/Day VWAP Dist, PD Dist(ATR): Distance from those references in ATR units.
ATR% (Gate), Trend(HTF): Status of optional regime filters (volatility/trend).
How to use it (step‑by‑step)
Keep the Safety toggles ON (default): triggers/visuals on bar‑close, optional confirmed HTF for trend slope.
Choose timeframe:
Intraday (5m–1h) or Swing (1h–4h). On very fast/thin charts, enable Performance mode and raise spacing/cooldown.
Watch the dashboard:
When PR reaches an extreme and an SFP context is present, the background shades (armed).
Wait for the trigger triangle:
It prints only after a micro BOS on a closed bar and after spacing/cooldown checks.
Use the Trigger Zone box as a visual reference only:
This script never tells you to buy/sell. Apply your own plan for entry, stop, and sizing.
Example:
Bullish: Sweep under PDL (SFP‑L) and reclaim; PR in lower tail arms long; BOS up confirms → long trigger on bar close (ATR-sized trigger zone shown).
Bearish: Sweep above PDH/pivot (SFP‑L/P) and reject; PR in upper tail arms short; BOS down confirms → short trigger on bar close (ATR-sized trigger zone shown).
Settings guide (with “when to adjust”)
Safety & Stability (defaults ON)
Confirm triggers at bar close, Draw visuals at bar close: Keep ON for clean, stable prints.
Use confirmed HTF values: Applies to HTF trend slope only; keeps it from changing until the HTF bar closes.
Performance mode: Turn ON if your chart is busy or laggy.
Core & Context
ATR Length: Bigger = smoother distances; smaller = more reactive.
Impulse AVWAP Anchor: Larger = fewer resets; smaller = resets more often.
Show Daily AVWAP: ON if you want session context.
Use last FVG in logic: ON to include FVG context in arming/score.
Show PDH/PDL/PWH/PWL: ON to see prior day/week levels that often attract sweeps.
Liquidity & Microstructure
Pivot Left/Right: Higher values = stronger/rarer pivots.
Min Wick Ratio (0..1): Higher = only more pronounced SFP wicks qualify.
BOS length: Larger = stricter BOS; smaller = quicker confirmations.
Signal persistence: Keeps SFP context alive for a few bars to avoid flicker.
Signal Gating
Percent‑Rank Lookback: Larger = more stable extremes; smaller = more reactive extremes.
Arm thresholds (qHi/qLo): Move closer to 0.5 to see more arms; move toward 0/1 to see fewer arms.
TTL, Cooldown, Min bars and Min ATR distance: Space out triggers so you’re not reacting to minor noise.
Regime Filters (optional)
ATR percentile gate: Only allow triggers when volatility is at/above a set percentile.
HTF trend gate: Only allow longs when the HTF slope is up (and shorts when it’s down), above a minimum slope.
Visuals & UX
Only show “important” SFPs: Filters pivot SFPs by Volume Z and |Impulse stretch|.
Trigger badges/history and Max badge count: Control label clutter.
Compact labels: Toggle SFP‑P/L vs full names.
Dashboard mode and position; Dark theme.
Reading PR (the built‑in “oscillator”)
PR ~ 0–10: Potential bullish extreme (long side can arm).
PR ~ 90–100: Potential bearish extreme (short side can arm).
Important: “Armed” ≠ “Enter.” A trigger still needs a micro BOS on a closed bar and spacing/cooldown to pass.
Repainting, confirmations, and HTF notes
By default, prints wait for the bar to close; this reduces repaint‑like effects.
Pivot SFPs only appear after the pivot confirms (after the chosen “right” bars).
PD/W levels come from the prior completed candles and do not change intraday.
If you enable confirmed HTF values, the HTF slope will not change until its higher‑timeframe bar completes (safer but slightly delayed).
Performance tips
If labels/zones clutter or the chart lags:
Turn ON Performance mode.
Hide FVG or the Trigger Zone.
Reduce badge history or turn badge history off.
If price scaling looks compressed:
Keep optional “score”/“PR” plots OFF (they overlay price and can affect scaling).
Alerts (neutral)
Structural Liquidity: LONG TRIGGER
Structural Liquidity: SHORT TRIGGER
These fire when a trigger condition is met on a confirmed bar (with defaults).
Limitations and risk
Not every sweep/extreme reverses; false triggers occur, especially on thin markets and low timeframes.
This indicator does not provide entries, exits, or position sizing—use your own plan and risk control.
Educational/informational only; no financial advice.
License and credits
© BullByte - MPL 2.0. Open‑source for learning and research.
Built from repeated observations of how liquidity runs, imbalance (FVG), and distance from “fair” (AVWAPs) combine, and how a small BOS often marks the moment structure actually shifts.
DeltaFlow Volume Profile [BigBeluga]🔵 OVERVIEW
The DeltaFlow Volume Profile builds a compact volume profile next to price and enriches every bin with flow context : bullish vs. bearish participation (%), a per-bin Delta % , an optional Delta Heat Map , and a PoC band with the bin’s absolute volume. This lets you see not just where volume clustered, but who (buyers or sellers) dominated inside each price slice.
🔵 CONCEPTS
Binned Volume Profile : Price range over a user-defined LookBack is split into Bins ; each bin aggregates traded volume.
Bull/Bear Split : Within every bin, volume is separated by candle direction into Bull Volume and Bear Volume , then normalized to % of the bin’s displayed size.
Delta % : The difference between Bull % and Bear % for the bin. Positive = buyer dominance; negative = seller dominance.
Delta Heat Map : Bin background shading that scales with both total volume strength and delta bias.
PoC (Point of Control) : The most significant bin gets a PoC band and a label with its absolute volume.
🔵 FEATURES
Profile with Flow : A clean horizontal volume bar per bin plus stacked Bull % and Bear % .
Per-Bin Delta Label : A readable “Δ xx%” tag at the start of each bin shows dominance at a glance.
Delta Heat Map : Optional gradient that intensifies with higher volume and stronger delta.
PoC Highlight : Optional PoC band colored separately, labeled with absolute volume (e.g., “1.23M”).
Configurable Inputs : LookBack, number of Bins (10–100), toggles for Delta, Heat Map, Volume Bars, and PoC color.
Readable Colors : Separate inputs for bullish (volume +) and bearish (volume –) hues.
🔵 HOW TO USE
Set the window : Choose LookBack and Bins to balance detail vs. performance (more bins = finer resolution).
Enable “Volume Bars” to display the bull/bear split as two stacked percent bars inside each bin.
High Bull % near support → constructive demand.
High Bear % near resistance → active supply.
Use Δ labels (toggle “Delta”) to quickly spot bins with clear buyer/seller control; combine with price position for confluence.
Turn on Delta Heat Map to prioritize areas with both large volume and strong imbalance.
Watch the PoC : The PoC band marks the most traded (and often magnet) level; its label shows absolute size for context.
Trade ideas :
Breakout continuation when Δ stays positive across consecutive upper bins.
Reversion risk when price enters a large bearish-Δ cluster below.
Manage risk around the PoC; reactions there can be sharp.
🔵 CONCLUSION
DeltaFlow Volume Profile upgrades a classic profile with flow intelligence. The bull/bear split, explicit Δ %, heat-weighted backdrop, and PoC volume label make dominant participation and key price shelves obvious. Use it to filter levels, time entries with imbalance, and validate breakouts or fades with objective volume-flow evidence.
Fractal FU//@version=5
indicator("Fractal FU", shorttitle="Fractal FU", overlay=true, max_labels_count=500)
// ===== Inputs
showBull = input.bool(true, "Show aligned bullish balls")
showBear = input.bool(true, "Show aligned bearish balls")
bullCol = input.color(color.blue, "Bull ball color")
bearCol = input.color(color.red, "Bear ball color")
ballSize = input.string("small", "Ball size", options= )
gateTo15 = input.bool(true, "Gate to 15m close (clean, fewer signals)")
showDebug = input.bool(false, "Show per-timeframe debug dots")
// ===== Helpers
// one-liner you asked for:
f_sig(res) => request.security(syminfo.tickerid, res, (high > high and low < low ) ? (close > open ? 1 : close < open ? -1 : 0) : 0, barmerge.gaps_off, barmerge.lookahead_off)
// Pull confirmed signals from each TF
sig1 = f_sig("1")
sig5 = f_sig("5")
sig10 = f_sig("10")
sig15 = f_sig("15")
// Alignment (all four agree)
bullAll = showBull and (sig1 == 1 and sig5 == 1 and sig10 == 1 and sig15 == 1)
bearAll = showBear and (sig1 == -1 and sig5 == -1 and sig10 == -1 and sig15 == -1)
// Emit control
emit15 = ta.change(time("15"))
emit = gateTo15 ? emit15 : barstate.isconfirmed // if not gated, show wherever alignment is true
// ===== Debug (tiny dots at bar to verify which TFs are firing)
plotshape(showDebug and sig1 == 1, title="1m bull", style=shape.circle, size=size.tiny, color=color.new(color.blue, 0), location=location.bottom)
plotshape(showDebug and sig5 == 1, title="5m bull", style=shape.circle, size=size.tiny, color=color.new(color.aqua, 0), location=location.bottom)
plotshape(showDebug and sig10 == 1, title="10m bull", style=shape.circle, size=size.tiny, color=color.new(color.teal, 0), location=location.bottom)
plotshape(showDebug and sig15 == 1, title="15m bull", style=shape.circle, size=size.tiny, color=color.new(color.navy, 0), location=location.bottom)
plotshape(showDebug and sig1 == -1, title="1m bear", style=shape.circle, size=size.tiny, color=color.new(color.red, 0), location=location.top)
plotshape(showDebug and sig5 == -1, title="5m bear", style=shape.circle, size=size.tiny, color=color.new(color.orange, 0), location=location.top)
plotshape(showDebug and sig10 == -1, title="10m bear", style=shape.circle, size=size.tiny, color=color.new(color.maroon, 0), location=location.top)
plotshape(showDebug and sig15 == -1, title="15m bear", style=shape.circle, size=size.tiny, color=color.new(color.purple, 0), location=location.top)
// ===== Markers (size must be const → gate each size)
off = gateTo15 ? -1 : 0 // when gated, place on the just-closed 15m bar
// ── Marker offset control stays the same ──
off2 = gateTo15 ? -1 : 0
// ── Bullish balls exactly at LOW ──
plot(bullAll and emit and ballSize == "tiny" ? low : na, title="Bullish tiny", style=plot.style_circles, color=bullCol, linewidth=1, offset=off2)
plot(bullAll and emit and ballSize == "small" ? low : na, title="Bullish small", style=plot.style_circles, color=bullCol, linewidth=2, offset=off2)
plot(bullAll and emit and ballSize == "normal" ? low : na, title="Bullish normal", style=plot.style_circles, color=bullCol, linewidth=3, offset=off2)
plot(bullAll and emit and ballSize == "large" ? low : na, title="Bullish large", style=plot.style_circles, color=bullCol, linewidth=4, offset=off2)
plot(bullAll and emit and ballSize == "huge" ? low : na, title="Bullish huge", style=plot.style_circles, color=bullCol, linewidth=5, offset=off2)
// ── Bearish balls exactly at HIGH ──
plot(bearAll and emit and ballSize == "tiny" ? high : na, title="Bearish tiny", style=plot.style_circles, color=bearCol, linewidth=1, offset=off2)
plot(bearAll and emit and ballSize == "small" ? high : na, title="Bearish small", style=plot.style_circles, color=bearCol, linewidth=2, offset=off2)
plot(bearAll and emit and ballSize == "normal" ? high : na, title="Bearish normal", style=plot.style_circles, color=bearCol, linewidth=3, offset=off2)
plot(bearAll and emit and ballSize == "large" ? high : na, title="Bearish large", style=plot.style_circles, color=bearCol, linewidth=4, offset=off2)
plot(bearAll and emit and ballSize == "huge" ? high : na, title="Bearish huge", style=plot.style_circles, color=bearCol, linewidth=5, offset=off2)
// Alerts
alertcondition(bullAll and emit, title="Aligned Bullish Outside (1/5/10/15)", message="Aligned bullish outside bar on 1/5/10/15m")
alertcondition(bearAll and emit, title="Aligned Bearish Outside (1/5/10/15)", message="Aligned bearish outside bar on 1/5/10/15m")
alertcondition((bullAll or bearAll) and emit, title="Aligned Any (1/5/10/15)", message="Aligned outside bar (bull or bear) on 1/5/10/15m")
Information Flow Analysis[b🔄 Information Flow Analysis: Systematic Multi-Component Market Analysis Framework
SYSTEM OVERVIEW AND ANALYTICAL FOUNDATION
The Information Flow Kernel - Hybrid combines established technical analysis methods into a unified analytical framework. This indicator systematically processes three distinct data streams - directional price momentum, volume-weighted pressure dynamics, and intrabar development patterns - integrating them through weighted mathematical fusion to produce statistically normalized market flow measurements.
COMPREHENSIVE MATHEMATICAL FRAMEWORK
Component 1: Directional Flow Analysis
The directional component analyzes price momentum through three mathematical vectors:
Price Vector: p = C - O (intrabar directional bias)
Momentum Vector: m = C_t - C_{t-1} (bar-to-bar velocity)
Acceleration Vector: a = m_t - m_{t-1} (momentum rate of change)
Directional Signal Integration:
S_d = \text{sgn}(p) \cdot |p| + \text{sgn}(m) \cdot |m| \cdot 0.6 + \text{sgn}(a) \cdot |a| \cdot 0.3
The signum function preserves directional information while absolute values provide magnitude weighting. Coefficients create a hierarchy emphasizing intrabar movement (100%), momentum (60%), and acceleration (30%).
Final Directional Output: K_1 = S_d \cdot w_d where w_d is the directional weight parameter.
Component 2: Volume-Weighted Pressure Analysis
Volume Normalization: r_v = \frac{V_t}{\overline{V_n}} where \overline{V_n} represents the n-period simple moving average of volume.
Base Pressure Calculation: P_{base} = \Delta C \cdot r_v \cdot w_v where \Delta C = C_t - C_{t-1} and w_v is the velocity weighting factor.
Volume Confirmation Function:
f(r_v) = \begin{cases}
1.4 & \text{if } r_v > 1.2 \
0.7 & \text{if } r_v < 0.8 \
1.0 & \text{otherwise}
\end{cases}
Final Pressure Output: K_2 = P_{base} \cdot f(r_v)
Component 3: Intrabar Development Analysis
Bar Position Calculation: B = \frac{C - L}{H - L} when H - L > 0 , else B = 0.5
Development Signal Function:
S_{dev} = \begin{cases}
2(B - 0.5) & \text{if } B > 0.6 \text{ or } B < 0.4 \
0 & \text{if } 0.4 \leq B \leq 0.6
\end{cases}
Final Development Output: K_3 = S_{dev} \cdot 0.4
Master Integration and Statistical Normalization
Weighted Component Fusion: F_{raw} = 0.5K_1 + 0.35K_2 + 0.15K_3
Sensitivity Scaling: F_{master} = F_{raw} \cdot s where s is the sensitivity parameter.
Statistical Normalization Process:
Rolling Mean: \mu_F = \frac{1}{n}\sum_{i=0}^{n-1} F_{master,t-i}
Rolling Standard Deviation: \sigma_F = \sqrt{\frac{1}{n}\sum_{i=0}^{n-1} (F_{master,t-i} - \mu_F)^2}
Z-Score Computation: z = \frac{F_{master} - \mu_F}{\sigma_F}
Boundary Enforcement: z_{bounded} = \max(-3, \min(3, z))
Final Normalization: N = \frac{z_{bounded}}{3}
Flow Metrics Calculation:
Intensity: I = |z|
Strength Percentage: S = \min(100, I \times 33.33)
Extreme Detection: \text{Extreme} = I > 2.0
DETAILED INPUT PARAMETER SPECIFICATIONS
Sensitivity (0.1 - 3.0, Default: 1.0)
Global amplification multiplier applied to the master flow calculation. Functions as: F_{master} = F_{raw} \cdot s
Low Settings (0.1 - 0.5): Enhanced precision for subtle market movements. Optimal for low-volatility environments, scalping strategies, and early detection of minor directional shifts. Increases responsiveness but may amplify noise.
Moderate Settings (0.6 - 1.2): Balanced sensitivity for standard market conditions across multiple timeframes.
High Settings (1.3 - 3.0): Reduced sensitivity to minor fluctuations while emphasizing significant flow changes. Ideal for high-volatility assets, trending markets, and longer timeframes.
Directional Weighting (0.1 - 1.0, Default: 0.7)
Controls emphasis on price direction versus volume and positioning factors. Applied as: K_{1,weighted} = K_1 \times w_d
Lower Values (0.1 - 0.4): Reduces directional bias, favoring volume-confirmed moves. Optimal for ranging markets where momentum may generate false signals.
Higher Values (0.7 - 1.0): Amplifies directional signals from price vectors and acceleration. Ideal for trending conditions where directional momentum drives price action.
Velocity Weighting (0.1 - 1.0, Default: 0.6)
Scales volume-confirmed price change impact. Applied in: P_{base} = \Delta C \times r_v \times w_v
Lower Values (0.1 - 0.4): Dampens volume spike influence, focusing on sustained pressure patterns. Suitable for illiquid assets or news-sensitive markets.
Higher Values (0.8 - 1.0): Amplifies high-volume directional moves. Optimal for liquid markets where volume provides reliable confirmation.
Volume Length (3 - 20, Default: 5)
Defines lookback period for volume averaging: \overline{V_n} = \frac{1}{n}\sum_{i=0}^{n-1} V_{t-i}
Short Periods (3 - 7): Responsive to recent volume shifts, excellent for intraday analysis.
Long Periods (13 - 20): Smoother averaging, better for swing trading and higher timeframes.
DASHBOARD SYSTEM
Primary Flow Gauge
Bilaterally symmetric visualization displaying normalized flow direction and intensity:
Segment Calculation: n_{active} = \lfloor |N| \times 15 \rfloor
Left Fill: Bearish flow when N < -0.01
Right Fill: Bullish flow when N > 0.01
Neutral Display: Empty segments when |N| \leq 0.01
Visual Style Options:
Matrix: Digital blocks (▰/▱) for quantitative precision
Wave: Progressive patterns (▁▂▃▄▅▆▇█) showing flow buildup
Dots: LED-style indicators (●/○) with intensity scaling
Blocks: Modern squares (■/□) for professional appearance
Pulse: Progressive markers (⎯ to █) emphasizing intensity buildup
Flow Intensity Visualization
30-segment horizontal bar graph with mathematical fill logic:
Segment Fill: For i \in : filled if \frac{i}{29} \leq \frac{S}{100}
Color Coding System:
Orange (S > 66%): High intensity, strong directional conviction
Cyan (33% ≤ S ≤ 66%): Moderate intensity, developing bias
White (S < 33%): Low intensity, neutral conditions
Extreme Detection Indicators
Circular markers flanking the gauge with state-dependent illumination:
Activation: I > 2.0 \land |N| > 0.3
Bright Yellow: Active extreme conditions
Dim Yellow: Normal conditions
Metrics Display
Balance Value: Raw master flow output ( F_{master} ) showing absolute directional pressure
Z-Score Value: Statistical deviation ( z_{bounded} ) indicating historical context
Dynamic Narrative System
Context-sensitive interpretation based on mathematical thresholds:
Extreme Flow: I > 2.0 \land |N| > 0.6
Moderate Flow: 0.3 < |N| \leq 0.6
High Volatility: S > 50 \land |N| \leq 0.3
Neutral State: S \leq 50 \land |N| \leq 0.3
ALERT SYSTEM SPECIFICATIONS
Mathematical Trigger Conditions:
Extreme Bullish: I > 2.0 \land N > 0.6
Extreme Bearish: I > 2.0 \land N < -0.6
High Intensity: S > 80
Bullish Shift: N_t > 0.3 \land N_{t-1} \leq 0.3
Bearish Shift: N_t < -0.3 \land N_{t-1} \geq -0.3
TECHNICAL IMPLEMENTATION AND PERFORMANCE
Computational Architecture
The system employs efficient calculation methods minimizing processing overhead:
Single-pass mathematical operations for all components
Conditional visual rendering (executed only on final bar)
Optimized array operations using direct calculations
Real-Time Processing
The indicator updates continuously during bar formation, providing immediate feedback on changing market conditions. Statistical normalization ensures consistent interpretation across varying market regimes.
Market Applicability
Optimal performance in liquid markets with consistent volume patterns. May require parameter adjustment for:
Low-volume or after-hours sessions
News-driven market conditions
Highly volatile cryptocurrency markets
Ranging versus trending market environments
PRACTICAL APPLICATION FRAMEWORK
Market State Classification
This indicator functions as a comprehensive market condition assessment tool providing:
Trend Analysis: High intensity readings ( S > 66% ) with sustained directional bias indicate strong trending conditions suitable for momentum strategies.
Reversal Detection: Extreme readings ( I > 2.0 ) at key technical levels may signal potential trend exhaustion or reversal points.
Range Identification: Low intensity with neutral flow ( S < 33%, |N| < 0.3 ) suggests ranging market conditions suitable for mean reversion strategies.
Volatility Assessment: High intensity without clear directional bias indicates elevated volatility with conflicting pressures.
Integration with Trading Systems
The normalized output range facilitates integration with automated trading systems and position sizing algorithms. The statistical basis provides consistent interpretation across different market conditions and asset classes.
LIMITATIONS AND CONSIDERATIONS
This indicator combines established technical analysis methods and processes historical data without predicting future price movements. The system performs optimally in liquid markets with consistent volume patterns and may produce false signals in thin trading conditions or during news-driven market events. This indicator is provided for educational and analytical purposes only and does not constitute financial advice. Users should combine this analysis with proper risk management, position sizing, and additional confirmation methods before making any trading decisions. Past performance does not guarantee future results.
Note: The term "kernel" in this context refers to modular calculation components rather than mathematical kernel functions in the formal computational sense.
As quantitative analyst Ralph Vince noted: "The essence of successful trading lies not in predicting market direction, but in the systematic processing of market information and the disciplined management of probability distributions."
— Dskyz, Trade with insight. Trade with anticipation.
Z-Score Volume with CVD TrendZ-Score Volume & CVD Trend with Exhaustion Signals
This powerful, all-in-one indicator combines statistical volume analysis, Cumulative Volume Delta (CVD), and a custom clustering algorithm to provide a clear and dynamic view of market sentiment. It is designed to help traders identify the prevailing trend and spot potential reversals or trend exhaustion before they happen.
Important Note: This indicator is specifically designed and optimized for use during the Regular Trading Hours (RTH) New York session, which is typically characterized by high volume and volatility. Its signals may be less reliable in low-volume or overnight sessions.
Core Concepts
1. Volume Z-Score
The script first calculates a Z-score for volume, which measures how many standard deviations a bar's volume is from a moving average. This helps to identify statistically significant volume spikes that may signal institutional activity or a major shift in sentiment.
2. Cumulative Volume Delta (CVD)
CVD plots the net difference between buying and selling volume over time. A rising CVD indicates a surplus of buying pressure, while a falling CVD shows a surplus of selling pressure. This provides a clear look at the direction of momentum.
3. Custom Clustering
By combining the Volume Z-score and CVD delta, the script classifies each bar into one of six distinct "clusters." The purpose is to simplify complex data into actionable signals.
High Conviction Bullish: High Z-score volume with strong CVD buying.
High Conviction Bearish: High Z-score volume with strong CVD selling.
Effort vs. Result: High Z-score volume with no clear CVD bias, indicating indecision or a struggle between buyers and sellers.
Quiet Accumulation: Low volume with subtle CVD buying, suggesting passive accumulation.
Quiet Distribution: Low volume with subtle CVD selling, suggesting passive distribution.
Low Conviction/Noise: Low volume and low CVD, representing general market noise.
Trend and Exhaustion Logic
Trend Establishment: The indicator determines the overall trend (Bullish, Bearish, or Neutral) by analyzing the majority of recent clusters over a configurable lookback period.
A Bullish Trend is confirmed when a majority of recent bars are either "High Conviction Bullish" or "Quiet Accumulation."
A Bearish Trend is confirmed when a majority of recent bars are either "High Conviction Bearish" or "Quiet Distribution."
Trend Exhaustion: This is a key feature for identifying potential reversals. The script looks for a divergence between price action and CVD within a confirmed trend.
Bullish Exhaustion Signal: Occurs during a confirmed "Bullish Trend" when you see a bearish divergence (price makes a higher high, but CVD shows negative delta and a close lower than the open). This is a strong sign the uptrend may be running out of steam.
Bearish Exhaustion Signal: Occurs during a confirmed "Bearish Trend" when you see a bullish divergence (price makes a lower low, but CVD shows positive delta and a close higher than the open). This indicates the downtrend may be exhausted.
How to Interpret the Visuals
Volume Bars: Colored to match the cluster they belong to.
Background Color: Shows the overall trend (light green for bullish, light red for bearish).
Circle Markers (bottom): Green circles indicate a bullish trend, and red circles indicate a bearish trend.
Triangles and Circles (top): Represent the specific cluster of each bar.
Trend Exhaustion Markers: Triangles above/below the bar signal potential trend exhaustion.
Info Table: An optional table provides a real-time summary of all key metrics for the current bar.
Settings
Volume EMA Length: Adjusts the moving average used for the Volume Z-score calculation.
Z-Score Look Back: Defines the number of bars to use for the volume and CVD percentile calculation.
Lower/Upper Cluster Percentile: Use these to adjust the sensitivity of the clustering. Tighter ranges (e.g., 25/75) capture more data, while wider ranges (e.g., 10/90) will only signal truly extreme events.
Trend Lookback Bars: Controls how many recent bars are considered when determining the trend.
This script offers a comprehensive and easy-to-read way to integrate volume, momentum, and trend analysis into your trading.
Happy Trading!
Penguin Volatility State StrategyThe Penguin Volatility State Strategy is a comprehensive technical analysis framework designed to identify the underlying "state" or "regime" of the market. Instead of just providing simple buy or sell signals, its primary goal is to classify the market into one of four distinct states by combining trend, momentum, and volatility analysis.
The core idea is to trade only when these three elements align, focusing on periods of volatility expansion (a "squeeze breakout") that occur in the direction of a confirmed trend and are supported by strong momentum.
Key Components
The strategy is built upon two main engines
The Volatility Engine (Bollinger Bands vs. Keltner Channels)
This engine detects periods of rapidly increasing volatility. It measures the percentage difference (diff) between the upper bands of Bollinger Bands (which are based on standard deviation) and Keltner Channels (based on Average True Range). During a volatility "squeeze," both bands are close. When price breaks out, the Bollinger Band expands much faster than the Keltner Channel, causing the diff value to become positive. A positive diff signals a volatility breakout, which is the moment the strategy becomes active.
The Trend & Momentum Engine (Multi-EMA System)
This engine determines the market's direction and strength. It uses:
A Fast EMA (e.g., 12-period) and a Slow EMA (e.g., 26-period): The crossover of these two moving averages defines the primary, underlying trend (similar to a MACD).
An Ultra-Fast EMA (e.g., 2-period of ohlc4): This is used to measure the immediate, short-term momentum of the price.
The Four Market States
By combining the Trend and Momentum engines, the strategy categorizes the market into four visually distinct states, represented by the chart's background color. This is the most crucial aspect of the system.
💚 Green State: Strong Bullish
The primary trend is UP (Fast EMA > Slow EMA) AND the immediate momentum is STRONG (Price > Fast EMA).
Interpretation: This represents a healthy, robust uptrend where both the underlying trend and short-term price action are aligned. It is considered the safest condition for taking long positions.
❤️ Red State: Strong Bearish
Condition: The primary trend is DOWN (Fast EMA < Slow EMA) AND the immediate momentum is WEAK (Price < Fast EMA).
Interpretation: This represents a strong, confirmed downtrend. It is considered the safest condition for taking short positions.
💛 Yellow State: Weakening Bullish / Pullback
Condition: The primary trend is UP (Fast EMA > Slow EMA) BUT the immediate momentum is WEAK (Price < Fast EMA).
Interpretation: This is a critical warning signal for bulls. While the larger trend is still up, the short-term price action is showing weakness. This could be a minor pullback, a period of consolidation, or the very beginning of a trend reversal. Caution is advised.
💙 Blue State: Weakening Bearish / Relief Rally
Condition: The primary trend is DOWN (Fast EMA < Slow EMA) BUT the immediate momentum is STRONG (Price > Fast EMA).
Interpretation: This signals that a downtrend is losing steam. It often represents a short-covering rally (a "bear market rally") or the first potential sign of a market bottom. Bears should be cautious and consider taking profits.
How the Strategy Functions
The strategy uses these four states as its foundation for making trading decisions. The entry and exit arrows (Long, Short, Close) are generated based on a set of rules that can be customized by the user. For instance, a trader can configure the strategy to
Only take long trades during the Green State.
Require a confirmed volatility breakout (diff > 0) before entering a trade.
Use the "RSI on Diff" indicator to ensure that the breakout is supported by accelerating momentum.
Summary
In essence, the Penguin Volatility State Strategy provides a powerful "dashboard" for viewing the market. It moves beyond simple indicators to offer a contextual understanding of price action. By waiting for the alignment of Trend (the State), Volatility (the Breakout), and Momentum (the Acceleration), it helps traders to identify higher-probability setups and, just as importantly, to know when it is better to stay out of the market.
License / disclaimer
© waranyu.trkm — MIT License. Educational use only; not financial advice.
