FibMAThis study visually demonstrates Fibonacci moving averages.
The darker the color, the stronger the signal is for either buying or selling.
Buys/Sells only take place when each moving average is above/below the its adjactent fibonacci sequence, i.e 5<8<13<21<34<55<89<144 for buying..
Alerts are provided as BUY ASSET and SELL ASSET.
Multiple moving averages are also provided.
In den Scripts nach "buy sell" suchen
HiLoMAHiLoMA (High/Low Moving Average) was designed specifically for calculating moving average boundries similar to Bollinger Bands, but is derived from the highest and lowest prices of an asset, not just the closing price. The timeframe is configurable and the study displays arrows where buys (below) and sells (above) should take place.
On exchanges with low or discounted fees, the study does excessively well at scalping. Backtesting, in general, shows this study to be very robust in any market conditions.
The alert conditions are clearly identified as BUY ASSET and SELL ASSET for automated trading.
Buys only occur when the entire spread is below the momentum line.
Sells only take place when the entire spread is above the momentum line.
When the momentum line cuts through the spread, any potentional buys/sells are ignored as these are considered weak.
Be sure your calculate your momentum on the basis of your candlestick timeframe. If you are using 3 minutes candlesticks and you want a 24 hour momentum, you need to set your momentum to 480. This holds true for all timeframes.
Sep 24
Release Notes: Seperated buys/sells where spread crosses momentum.
Cyan (lighter blue) arrows are buy/sell signals that disregard momentum.
Buys/Sells that honour momentum are now labeled MOMBUY ASSET and MOMSELL ASSET.
Buys/Sells that disregard momentum are now BUY ASSET and SELL ASSET accordingly.
Oct 4
Release Notes: Momentum is now a band with an upper and lower boundry. Buys and sells must now be completely above the band or below the band respectively. The effect is to produce stronger signals for momentum precomditional trades.
Sell / Buy RatesThis script finds sell / buy rates and adds its linear regression to the chart. its aim is finding buying and selling power, then you can try to find trend reversals. Also you can find divergences, it's very important signal for trend reversal.
Linear regression is a basic and commonly used type of predictive analysis.
if you choose lower periods then it will be more sensitive. I choose 34 as it's one of fibonnaci number.
If you find my works useful, please consider a donation
BTC: 16XRqyS3Vgh1knAU1tCcruqhUrVm4QWWmR
Gunbot Machine Gun (trial version)Hello fellow Gunbotters, you have requested and I have delivered. Here is the trial version for Gunbot Machine Gun strategy.
Note:
1. This is the trial version so the customization settings are locked, subscribe to unlock features.
2. Green triangles = buy signals, Red triangles = sell signals.
3. Both buy and sell alerts are set-up so you can create alerts easily.
This is how the Gunbot Machine Gun works: I have 200 slots for alerts in Tradingview. I use all of those slots to set buy and sell alerts on BTC pairs. I have volatility filter in my script so the Machine Gun will only start firing out rounds (Buy alerts) when the volatility becomes high. Tradingview sends email to gmail. Gunbot waits for the email, once it reads it Gunbot will action the email (buy/sell depending on the message). Gunbot buys the coin based on email message received from Tradingview. It will be rapid fire, accumulating buys while coin is pumping up. Then when the dust settles and momentum starts dying, the script will throw a hand grenade (pink triangles), send a sell signal/email then Gunbot reads that email and executes the sell all trade.
Buys early during pumps. Finds coins that will pump soon. Sells at peak.
Legend:
Green triangles = buy signals
Pink triangles = sell signals
Note:
During period of low volatility there will rarely be any buy signals. The sell signals during this time is irrelevant (can only sell after you bought). But once high volatility is detected the script gets ready to activate. Then it starts sending buy signals close and during the pumps. Sells at peak.
Works on most coins and stocks.
Gunbot Machine GunGunbot Machine Gun Strategy
This is how the Gunbot Machine Gun works: I have 200 slots for alerts in Tradingview. I use all of those slots to set buy and sell alerts on BTC pairs. I have volatility filter in my script so the Machine Gun will only start firing out rounds (Buy alerts) when the volatility becomes high. Tradingview sends email to gmail. Gunbot waits for the email, once it reads it Gunbot will action the email (buy/sell depending on the message). Gunbot buys the coin based on email message received from Tradingview. It will be rapid fire, accumulating buys while coin is pumping up. Then when the dust settles and momentum starts dying, the script will throw a hand grenade (pink triangles), send a sell signal/email then Gunbot reads that email and executes the sell all trade.
Buys early during pumps. Finds coins that will pump soon. Sells at peak.
Legend:
Green triangles = buy signals
Pink triangles = sell signals
Note:
During period of low volatility there will rarely be any buy signals. The sell signals during this time is irrelevant (can only sell after you bought). But once high volatility is detected the script gets ready to activate. Then it starts sending buy signals close and during the pumps. Sells at peak.
Works on most coins and stocks.
Color CandlesUses 6 most common indicators to color candles when they give buy/sell signals.
Use line view to see candle colors.
Purple = 6 buy signals
Teal = 5 buy signals
Navy = 4 buy signals
Lime = 3 buy signals
Green = 2 buy signals
Pale Green = 1 Buy signal
White = neutral
Gray = 1 sell signal
Yellow = 2 sell signals
Orange = 3 sell signals
Red = 4 sell signals
Firebrick = 5 sell signals
Black = 6 sell signals
Parabolic SAR calculated as .02, .02, .2. Traditional Buy/Sell. Green/Red Dots.
Bollinger Band calculated as 20, 1. Buy/Sell when above or below band. Aqua filled band.
MACD calculated with emas 12, 26, 9. Traditional MACD/Signal cross Buy/Sell. Filled Blue/Orange band.
RSI length 14. Traditional Buy/Sell below 30 and above 70. Green/Yellow/Red line below price.
ADX/DI len 14. Traditional crossover Buy/Sell. Filled Lime/Green above price.
Stochastic 14/3/3. Traditional 20/80 Buy/Sell. Filled teal/orange above price.
NGRN MACD-X & RSI v5MACD-X, RSI & Volume Indicator & Alerts Study - Version 5
Overview
This study and it's associated strategy were modeled after the famous Philakone described algorithms on his now defunct instructional video series.
This indicator allows for full customisation of parameters and interaction between three indicators that allow users to shape their trading methods to their desired goals.
This associated strategy also allows users to backtest the study alerts script and find the best settings towards that end.
MACD + RSI + VOLUME - are of the most powerful and widely usded indicators, MACD/Histogram crosses, coupled with RSI & Volume increases/decreases will detects areas of deeply oversold / overbought and buys/sells on the reversal
Features
Full customisation - All parameters are open for customising to allow the trader to build their own strategy and adapt from market to market.
Clean/Simple UI - Facilitating ease of use.
Enable Buying OR Selling, - or have them both active at the same time.
Toggle off and on ALTERNATING Buy and Sell feature (pyramiding) - to allow for consecutive DCA style buys or SCALING out of an entry (partial sell).
Customizable Stop-Loss plot - to enable users to create a STOP-LOSS alert option or other alert(s) based on the plot location. See settings screenshot.
Toggle Auto Stop-Loss sell option - to enable users choose whether or not to automatically issue a sell signal when close crosses stop loss plot, or choose to toggle off if not profitable.
Customizable Take-Profit plot - to enable users to create a TAKE-PROFIT alert option or other alert(s) based on the plot location.
Study and associated Strategy - to use the TradingView ‘Strategy Tester’ back-testing features to find the best alert settings for specific coins in bear, bull and sideways markets.
Changes Version 5
Added STOP-LOSS time-out period where users may specify a duration of trading pause time after a stop-loss has been triggered. A value of zero disables the feature. Time out start is indicated by a red flag icon and resumption is indicated with a green flag.
Settings
SCREENSHOT LINKS:
BUY SETTINGS: prntscr.com
SELL SETTINGS: prntscr.com
Access
For a 4 DAYS TRAIL, sign up as an Explorer subscriber @ Patreon page: www.patreon.com
Full Access is 0.25 ETH , one time fee for LIFETIME access to the STUDY indicator, STRATEGY and future updates as well as support and SETTINGS for various markets on the Binance Exchange.
NGRN MACD-X & RSI v4MACD-X, RSI & Volume Indicator & Alerts Study - Version 4
Overview
This study and it's associated strategy were modeled after the famous Philakone described algorithms on his now defunct instructional video series.
This indicator allows for full customisation of parameters and interaction between three indicators that allow users to shape their trading methods to their desired goals.
This associated strategy also allows users to backtest the study alerts script and find the best settings towards that end.
MACD + RSI + VOLUME - are of the most powerful and widely usded indicators, MACD/Histogram crosses, coupled with RSI & Volume increases/decreases will detects areas of deeply oversold / overbought and buys/sells on the reversal
Features
Full customisation - All parameters are open for customising to allow the trader to build their own strategy and adapt from market to market.
Clean/Simple UI - Facilitating ease of use.
Enable Buying OR Selling, - or have them both active at the same time.
Toggle off and on ALTERNATING Buy and Sell feature (pyramiding) - to allow for consecutive DCA style buys or SCALING out of an entry (partial sell).
Customizable Stop-Loss plot - to enable users to create a STOP-LOSS alert option or other alert(s) based on the plot location. See settings screenshot.
Toggle Auto Stop-Loss sell option - to enable users choose whether or not to automatically issue a sell signal when close crosses stop loss plot, or choose to toggle off if not profitable.
Customizable Take-Profit plot - to enable users to create a TAKE-PROFIT alert option or other alert(s) based on the plot location.
Study and associated Strategy - to use the TradingView ‘Strategy Tester’ back-testing features to find the best alert settings for specific coins in bear, bull and sideways markets.
Changes Version 4
Improved STOP-LOSS plot draw (red line).
Added the option to automatically sell when stop-loss cross triggered or have the option disabled, in the event a better profit can be achieved.
Added new TAKE-PROFIT plot (aqua line) to visually guide users where to place the TAKE-PROFIT parameter as well as give users options to create alerts based on the TAKE-PROFIT plot.
Access
Full Access is 0.1 ETH , one time fee for LIFETIME access to the STUDY indicator, STRATEGY and future updates as well as support and SETTINGS for various markets on the Binance Exchange.
Settings
SCREENSHOT LINKS:
BUY SETTINGS: prntscr.com
SELL SETTINGS: prntscr.com
CryptogramTR with OPEN CODEIndicator is obtained by importing RSI(14) into HULL moving average source with 2 different periods, as one is long period and the other is short.
When green line (short period) cross upward the red line (long period) , this is a BUY; vice versa it is a SELL.
When HMA Short Period is set to 1 (one), yielding line is absolutely the same line of RSI (14). You can change it into 8(eight) preferably.
İndikatör, RSI(14) indikatörünün, hull hareketli ortalamasının kod kaynağı olarak atanması ile elde edilmiştir. Uzun ve kısa olmak üzere 2 ayrı periyot kullanılmıştır.
Yeşil çizgi yani kısa periyotlu çizgi, kırmızı yani uzun periyotlu olanı yukarı keserse AL, tersi durum SAT olarak düşünülmelidir.
Hull Kısa Periyodu 1 iken oluşan yeşil çizgi, RSI(14) indikatörünü vermektedir. Kısa periyot olarak tercihinize göre bu değeri 8 olarak da kullanabilirsiniz.
NGRN MACD-X & RSI v3.1 MACD-X, RSI & Volume Indicator & Alerts Study - Version 3.1
Overview
This study and it's associated strategy were modeled after the famous Philakone described algorithms on his now defunct instructional video series.
This indicator allows for full customisation of parameters and interaction between three indicators that allow users to shape their trading methods to their desired goals.
This associated strategy also allows users to backtest the study alerts script and find the best settings towards that end.
MACD + RSI + VOLUME - are of the most powerful and widely usded indicators, MACD/Histogram crosses, coupled with RSI & Volume increases/decreases will detects areas of deeply oversold / overbought and buys/sells on the reversal
Features
Full customisation - All parameters are open for customising to allow the trader to build their own strategy and adapt from market to market.
Clean/Simple UI - Facilitating ease of use.
Enable Buying or Selling, - or have them both active at the same time.
Toggle off and on ALTERNATING Buy and Sell feature (pyramiding) - to allow for consecutive DOLLAR COST AVERAGING style buys or SCALING out of an entry (partial sell).
Customizable Stop-Loss plot - to enable users to create a STOP-LOSS alert option or other alert(s) based on the plot location. See settings screenshot.
Study and associated Strategy - to use the TradingView ‘Strategy Tester’ back-testing features to find the best alert settings for specific coins in bear, bull and sideways markets.
Ideal for use with the Autoview trading bot
Changes Version 3.1
UI consolidates reduntant script inputs making the script easier to use.
Fixes STOP-LOSS algorithm.
Adds a STOP-LOSS Plot (red line) to enable users to create a STOP-LOSS alert option or other alert(s) based on the plot location. See settings screenshot.
Access
Full Access is 0.1 ETH , one time fee for LIFETIME access to the STUDY indicator, STRATEGY and future updates as well as support and SETTINGS for various markets on the Binance Exchange.
Settings
BUY SETTINGS: prntscr.com
SELL SETTINGS: prntscr.com
STOP-LOSS SETTINGS: prntscr.com
NGRN MACD-X & RSI v2 StudyMACD-X, RSI & Volume Indicator Study - Version 2.0
Overview
This study and it's associated strategy were modeled after the famous Philakone described algorithms on his now defunct instructional video series.
This indicator allows for full customisation of parameters and interaction between three indicators that allow users to shape their trading methods to their desired goals.
This associated strategy also allows users to backtest the study alerts script and find the best settings towards that end.
MACD + RSI + VOLUME - are of the most powerful and widely usded indicators, MACD/Histogram crosses, coupled with RSI & Volume increases/decreases will detects areas of deeply oversold / overbought and buys/sells on the reversal
Features
Full customisation - All parameters are open for customising to allow the trader to build their own strategy and adapt from market to market.
Toggle Buying and Selling, or have them both active at the same time.
Toggle off and on ALTERNATING Buy and Sell feature to allow for consecutive DCA style buys or SCALING out of an entry (partial sell).
Access
Full Access is 0.07 ETH, one time fee for full unlimited access to the indicator, strategy and future updates as well as support and SETTINGS for various markets on the Binance Exchange (currently only USDT)
チェリーボーイ//@version=6
indicator("チェリーボーイ", overlay=true, precision=2, max_labels_count=500, max_lines_count=500)
// ===================== GLOBAL HELPERS ===================== //
ma_func(_source, _length, _type) =>
switch _type
"SMA" => ta.sma(_source, _length)
"SMA + Bollinger Bands" => ta.sma(_source, _length)
"EMA" => ta.ema(_source, _length)
"SMMA (RMA)" => ta.rma(_source, _length)
"WMA" => ta.wma(_source, _length)
"VWMA" => ta.vwma(_source, _length)
=> na
// ===================== Display / Placement ===================== //
grpDisp = "Display"
showOscPlots = input.bool(false, "内部(Stoch/RCI/RVI/RSI)のプロットを表示", group=grpDisp, tooltip="価格スケールを壊す可能性があるため既定OFF")
showTextLabels = input.bool(true, "R/B/BUY/SELLラベルを表示", group=grpDisp)
// ===================== Master Toggles ===================== //
grpMain = "Modules"
useStoch = input.bool(true, "Enable Stoch→EMA(20/50/70)", group=grpMain)
useRCI = input.bool(true, "Enable RCI→EMA(20/50/70)", group=grpMain)
useRVI = input.bool(true, "Enable RVI→EMA(20/50/70)", group=grpMain)
usePrice3 = input.bool(true, "Enable Price 3EMA(10/50/200)", group=grpMain)
useRSI = input.bool(true, "Enable RSI→EMA(20/50/70)", group=grpMain)
// ===================== Reach Settings ===================== //
grpReach = "Reach Settings"
reachMode = input.string("On Enter", "Signal Mode", options= , group=grpReach)
needCount = input.int(4, "必要個数（N of M）", minval=1, maxval=5, group=grpReach)
// ===================== BINGO水平線（価格に描画） ===================== //
grpHL = "BINGO Horizontal Line"
drawHL = input.bool(true, "BINGO時に水平線を描く", group=grpHL)
hlHours = input.float(2.0, "水平線の長さ（時間）", minval=0.1, maxval=48.0, step=0.1, group=grpHL)
hlPriceSrc = input.string("Close", "ライン価格の基準", options= , group=grpHL)
hlW = input.int(2, "水平線の太さ", minval=1, maxval=5, group=grpHL)
// ライン価格
priceVal() =>
switch hlPriceSrc
"Close" => close
"Open" => open
"High" => high
"Low" => low
"HL2" => (high + low) / 2
"HLC3" => (high + low + close) / 3
=> close
// =====================================================
// 0) Price 3EMA → PO
// =====================================================
grpP = "Price 3EMA (internal)"
srcP = input.source(close, "Source", group=grpP)
len10 = input.int(10, "EMA10 Length", minval=1, group=grpP)
len50 = input.int(50, "EMA50 Length", minval=1, group=grpP)
len200 = input.int(200, "EMA200 Length", minval=1, group=grpP)
ema10 = ta.ema(srcP, len10)
ema50 = ta.ema(srcP, len50)
ema200 = ta.ema(srcP, len200)
poUp_price = usePrice3 and (ema10 > ema50 and ema50 > ema200)
poDown_price = usePrice3 and (ema10 < ema50 and ema50 < ema200)
sigUp_price = poUp_price and not poUp_price
sigDown_price = poDown_price and not poDown_price
// =====================================================
// 1) Stochastic → EMA PO
// =====================================================
periodK_s = 9
smoothK_s = 15
periodD_s = 3
k_raw_s = ta.stoch(high, low, close, periodK_s)
k_s = ta.sma(k_raw_s, smoothK_s)
d_s = ta.sma(k_s, periodD_s)
kE20_s = ta.ema(k_s, 20)
kE50_s = ta.ema(k_s, 50)
kE70_s = ta.ema(k_s, 70)
poUp_s = useStoch and (kE20_s > kE50_s and kE50_s > kE70_s)
poDown_s = useStoch and (kE20_s < kE50_s and kE50_s < kE70_s)
sigUp_s = ta.change(poUp_s) and poUp_s
sigDown_s = ta.change(poDown_s) and poDown_s
plot(showOscPlots and useStoch ? kE20_s : na, title=" EMA20", color=color.lime, linewidth=2)
plot(showOscPlots and useStoch ? kE50_s : na, title=" EMA50", color=color.orange, linewidth=2)
plot(showOscPlots and useStoch ? kE70_s : na, title=" EMA70", color=color.fuchsia, linewidth=2)
plot(showOscPlots and useStoch ? k_s : na, title=" %K", color=color.new(color.blue, 70))
plot(showOscPlots and useStoch ? d_s : na, title=" %D", color=color.new(color.red, 70))
// =====================================================
// 2) RCI → EMA PO
// =====================================================
grpRCI = "RCI Settings"
srcInput_r = input.source(close, "RCI Source", group=grpRCI)
lenRCI_r = input.int(10, "RCI Length", minval=1, group=grpRCI)
rci_r = ta.rci(srcInput_r, lenRCI_r)
lenE1_r = input.int(20, "EMA20", minval=1, group=grpRCI)
lenE2_r = input.int(50, "EMA50", minval=1, group=grpRCI)
lenE3_r = input.int(70, "EMA70", minval=1, group=grpRCI)
e20_r = ta.ema(rci_r, lenE1_r)
e50_r = ta.ema(rci_r, lenE2_r)
e70_r = ta.ema(rci_r, lenE3_r)
plot(showOscPlots and useRCI ? rci_r : na, title=" RCI", color=color.blue)
plot(showOscPlots and useRCI ? e20_r : na, title=" EMA20", color=color.orange, linewidth=2)
plot(showOscPlots and useRCI ? e50_r : na, title=" EMA50", color=color.fuchsia, linewidth=2)
plot(showOscPlots and useRCI ? e70_r : na, title=" EMA70", color=color.aqua, linewidth=2)
poUp_r = useRCI and (e20_r > e50_r and e50_r > e70_r)
poDown_r = useRCI and (e20_r < e50_r and e50_r < e70_r)
sigUp_r = poUp_r and not poUp_r
sigDown_r = poDown_r and not poDown_r
// =====================================================
// 3) RVI → EMA PO
// =====================================================
grpRVI = "RVI Core"
length_v = input.int(10, "RVI StdDev Length", minval=1, group=grpRVI)
lenEMA_v = input.int(14, "RVI EMA Len", minval=1, group=grpRVI)
src_v = close
stddev_v = ta.stdev(src_v, length_v)
upper_v = ta.ema(ta.change(src_v) <= 0 ? 0 : stddev_v, lenEMA_v)
lower_v = ta.ema(ta.change(src_v) > 0 ? 0 : stddev_v, lenEMA_v)
sumUL_v = upper_v + lower_v
rvi_v = sumUL_v != 0 ? upper_v / sumUL_v * 100.0 : na
lenE1_v = input.int(20, "EMA20 (on RVI)", minval=1, group=grpRVI)
lenE2_v = input.int(50, "EMA50 (on RVI)", minval=1, group=grpRVI)
lenE3_v = input.int(70, "EMA70 (on RVI)", minval=1, group=grpRVI)
rE20_v = ta.ema(rvi_v, lenE1_v)
rE50_v = ta.ema(rvi_v, lenE2_v)
rE70_v = ta.ema(rvi_v, lenE3_v)
plot(showOscPlots and useRVI ? rvi_v : na, title=" RVI", color=#7E57C2)
plot(showOscPlots and useRVI ? rE20_v : na, " EMA20", color=color.lime, linewidth=2)
plot(showOscPlots and useRVI ? rE50_v : na, " EMA50", color=color.teal, linewidth=2)
plot(showOscPlots and useRVI ? rE70_v : na, " EMA70", color=color.blue, linewidth=2)
poUp_v = useRVI and (rE20_v > rE50_v and rE50_v > rE70_v)
poDown_v = useRVI and (rE20_v < rE50_v and rE50_v < rE70_v)
sigUp_v = poUp_v and not poUp_v
sigDown_v = poDown_v and not poDown_v
// =====================================================
// 4) RSI → EMA PO
// =====================================================
grpRSI = "RSI Settings"
rsiLen = input.int(14, "RSI Length", minval=1, group=grpRSI)
rsiSrc = input.source(close, "RSI Source", group=grpRSI)
chg = ta.change(rsiSrc)
upR = ta.rma(math.max(chg, 0), rsiLen)
downR = ta.rma(-math.min(chg, 0), rsiLen)
rsi = downR == 0 ? 100 : upR == 0 ? 0 : 100 - (100 / (1 + upR / downR))
rsiE20 = ta.ema(rsi, 20)
rsiE50 = ta.ema(rsi, 50)
rsiE70 = ta.ema(rsi, 70)
plot(showOscPlots and useRSI ? rsi : na, title=" RSI", color=#7E57C2)
plot(showOscPlots and useRSI ? rsiE20 : na, title=" EMA20", color=color.lime, linewidth=2)
plot(showOscPlots and useRSI ? rsiE50 : na, title=" EMA50", color=color.orange, linewidth=2)
plot(showOscPlots and useRSI ? rsiE70 : na, title=" EMA70", color=color.fuchsia, linewidth=2)
poUp_rsi = useRSI and (rsiE20 > rsiE50 and rsiE50 > rsiE70)
poDown_rsi = useRSI and (rsiE20 < rsiE50 and rsiE50 < rsiE70)
sigUp_rsi = poUp_rsi and not poUp_rsi
sigDown_rsi = poDown_rsi and not poDown_rsi
// =====================================================
// 5) REACH (N of M) LOGIC
// =====================================================
activeCount =
(usePrice3 ? 1 : 0) +
(useStoch ? 1 : 0) +
(useRCI ? 1 : 0) +
(useRVI ? 1 : 0) +
(useRSI ? 1 : 0)
upCount =
(poUp_price ? 1 : 0) +
(poUp_s ? 1 : 0) +
(poUp_r ? 1 : 0) +
(poUp_v ? 1 : 0) +
(poUp_rsi ? 1 : 0)
downCount =
(poDown_price ? 1 : 0) +
(poDown_s ? 1 : 0) +
(poDown_r ? 1 : 0) +
(poDown_v ? 1 : 0) +
(poDown_rsi ? 1 : 0)
reachUp_raw = (upCount >= needCount) and (activeCount >= needCount)
reachDown_raw = (downCount >= needCount) and (activeCount >= needCount)
reachUp = reachMode == "On Enter" ? (reachUp_raw and not reachUp_raw ) : reachUp_raw
reachDown = reachMode == "On Enter" ? (reachDown_raw and not reachDown_raw ) : reachDown_raw
// ---- ラベル（ズレ防止：バー基準） ----
plotshape(showTextLabels and reachUp,
title=" Up", style=shape.labelup, location=location.belowbar,
text="R↑", textcolor=color.white, color=color.new(#00bcd4, 0), size=size.tiny)
plotshape(showTextLabels and reachDown,
title=" Down", style=shape.labeldown, location=location.abovebar,
text="R↓", textcolor=color.white, color=color.new(#ff7043, 0), size=size.tiny)
alertcondition(reachUp, title=" N/M Up", message="Reach Up: >= needCount modules are UP.")
alertcondition(reachDown, title=" N/M Down", message="Reach Down: >= needCount modules are DOWN.")
// =====================================================
// 6) BINGO (5 of 5) + 価格に水平線
// =====================================================
bingoUp_raw = (upCount == 5) and (activeCount == 5)
bingoDown_raw = (downCount == 5) and (activeCount == 5)
// 表示用（モード反映）
bingoUp = reachMode == "On Enter" ? (bingoUp_raw and not bingoUp_raw ) : bingoUp_raw
bingoDown = reachMode == "On Enter" ? (bingoDown_raw and not bingoDown_raw ) : bingoDown_raw
// 立ち上がり（水平線＆コンボ状態遷移のトリガ）
bingoUp_enter = ta.change(bingoUp_raw) and bingoUp_raw
bingoDown_enter = ta.change(bingoDown_raw) and bingoDown_raw
plotshape(showTextLabels and bingoUp,
title=" Up", style=shape.labelup, location=location.belowbar,
text="B↑", textcolor=color.white, color=color.new(color.green, 0), size=size.tiny)
plotshape(showTextLabels and bingoDown,
title=" Down", style=shape.labeldown, location=location.abovebar,
text="B↓", textcolor=color.white, color=color.new(color.red, 0), size=size.tiny)
alertcondition(bingoUp, title=" 5/5 Up", message="All 5 modules are UP (5/5 BINGO)")
alertcondition(bingoDown, title=" 5/5 Down", message="All 5 modules are DOWN (5/5 BINGO)")
// ---- BINGO時に2時間水平線（価格に描画） ----
twoHoursMs = int(math.round(hlHours * 60.0 * 60.0 * 1000.0))
newHL(_isUp) =>
_y = priceVal()
_col = _isUp ? color.new(color.green, 0) : color.new(color.red, 0)
line.new(x1=time, y1=_y, x2=time + twoHoursMs, y2=_y, xloc=xloc.bar_time, extend=extend.none, color=_col, width=hlW)
if drawHL and bingoUp_enter
newHL(true)
if drawHL and bingoDown_enter
newHL(false)
// =====================================================
// 7) コンボ：BINGO後にRSI-POが逆向きで発火
// BINGO↓ → RSI PO↑ = Buy
// BINGO↑ → RSI PO↓ = Sell
// =====================================================
var int lastBingoDir = 0 // +1=Up, -1=Down, 0=None
if bingoUp_enter
lastBingoDir := 1
if bingoDown_enter
lastBingoDir := -1
buySig = (lastBingoDir == -1) and sigUp_rsi
sellSig = (lastBingoDir == 1) and sigDown_rsi
if buySig or sellSig
lastBingoDir := 0
plotshape(showTextLabels and buySig,
title=" BUY", style=shape.labelup, location=location.belowbar,
text="BUY", textcolor=color.white, color=color.new(#26a69a, 0), size=size.tiny)
plotshape(showTextLabels and sellSig,
title=" SELL", style=shape.labeldown, location=location.abovebar,
text="SELL", textcolor=color.white, color=color.new(#ef5350, 0), size=size.tiny)
alertcondition(buySig, title=" BINGO↓ → RSI PO↑ (BUY)", message="BUY: BINGO Down followed by RSI-PO Up")
alertcondition(sellSig, title=" BINGO↑ → RSI PO↓ (SELL)", message="SELL: BINGO Up followed by RSI-PO Down")
THUẬN-VolumeOverall Purpose
This indicator is a powerful tool based on the foundational principles of the Wyckoff Method and Volume Spread Analysis (VSA). Its primary goal is to decode the story behind the price chart by analyzing the intricate relationship between price action (spread), volume (effort), and the closing price (result). By doing so, it helps traders identify supply and demand imbalances, anticipate potential trend changes, and spot the activity of institutional players or "Smart Money."
Core Concepts Explained
The indicator is built upon Richard Wyckoff's law of "Effort vs. Result."
Effort is represented by the volume on a price bar.
Result is represented by the price spread (the range from the high to the low of the bar).
By comparing the effort (volume) to the result (price spread), the indicator detects critical market confirmations and anomalies. For example, high volume (great effort) that results in a narrow price spread (poor result) signals a potential turning point.
Key Features
Relative Volume Analysis:
The indicator doesn't just show raw volume. It automatically analyzes and classifies volume levels by comparing the current bar's volume to a moving average of recent volume.
Volume bars are color-coded for instant interpretation:
Ultra-High Volume (Climactic): Signals potential trend exhaustion or major institutional activity.
High Volume: Confirms the strength behind a price move.
Average Volume: Represents normal market activity.
Low Volume: Indicates a lack of interest, often crucial for "No Supply" or "No Demand" signals.
VSA Signal Detection & On-Chart Labels:
The core of the indicator is its ability to automatically detect classic VSA patterns and display clear labels on the chart. These signals are grouped into signs of strength and weakness.
Signs of Strength - Bullish Signals:
Stopping Volume: An alert for ultra-high volume at the bottom of a downtrend, suggesting that massive buying is absorbing the selling pressure.
Test for Supply: A down-bar with a narrow spread on low volume, indicating that sellers are exhausted and the market is ready to move up.
No Supply Bar: A down-bar with low volume, showing a lack of selling interest, often confirming the path is clear for higher prices.
Signs of Weakness - Bearish Signals:
Upthrust Bar: A sharp move up that is quickly rejected, closing near the low. It signals that demand has been overwhelmed by supply.
No Demand Bar: An up-bar with low volume, indicating a lack of buying interest and warning that the uptrend is weak.
Selling Climax: An ultra-high volume bar at the top of an uptrend, signaling trend exhaustion and a potential reversal.
Customizable Settings:
Users can adjust the lookback period for the volume moving average, change the sensitivity for signal detection, and toggle specific signals on or off to declutter the chart and focus on their preferred setups.
How to Use in Trading
Confirmation: Use VSA signals to confirm price action at key support, resistance, or supply/demand zones. A "Test for Supply" at a support level is a strong confirmation for a long entry.
Trend Analysis: Spot trend weakness when you see consecutive "No Demand" bars in an uptrend or "No Supply" bars in a downtrend.
Anticipating Reversals: Climactic volume signals (Buying/Selling Climax, Stopping Volume) often appear at major market turning points, providing early warnings of a potential trend reversal.
In summary, this indicator allows traders to move beyond simple technical patterns and gain a deeper understanding of the market dynamics, helping to align their trades with the flow of institutional capital.
Wyckoff Smart Money Pro [MTF]Wyckoff Smart Money Pro detects trading ranges, phases, and events from the Wyckoff method and confirms them with VSA (Volume Spread Analysis), divergence checks, and a composite “smart money” strength index. It generates optional buy/sell signals only when multiple conditions align (phase, VSA, CO strength, effort vs. result, time/volume filters). The dashboard, POC/Value Area, and MTF backdrop help you manage context and risk in real time.
What this indicator does
Wyckoff Smart Money Pro is a multi-timeframe Wyckoff tool that:
⦁ Finds accumulation/distribution ranges and tracks Phases A–E.
⦁ Labels Wyckoff events (PS, SC, AR, ST, Spring/Test, SOS, LPS, UTAD, SOW, LPSY, TS…) and VSA patterns (No Demand/Supply, Stopping Volume, Upthrust, etc.).
⦁ Computes a Composite Operator (CO) Strength score from price/volume behavior to approximate “smart money” bias.
⦁ Adds divergence, effort vs. result, and a volume profile (POC & 70% value area) inside the detected range.
⦁ Provides buy/sell signals only when a configurable confluence is present (events + VSA + CO + EVR + phase + filters).
⦁ Supports MTF context (with a safe HTF resolver and fallbacks) and an Info Dashboard to summarize the current state.
It is designed to make the Wyckoff workflow visual and rules-based without promising results or automating decisions.
How it works (methods & calculations)
1) Range & Phase model
⦁ A sliding lookback searches for a valid range (recent highest high/lowest low), requiring width within 2–10× ATR(14) and a minimum bar count inside the bounds.
⦁ Once a range is active, the script derives Creek/Ice/Mid/Quartiles and classifies bars into Wyckoff Phases A–E using event recency (barssince) and where price sits relative to the range.
⦁ The background color reflects the current Phase; optional MTF events (from the chosen HTF) tint the background lightly for higher-timeframe context.
2) Wyckoff & VSA event engine
⦁ Events include PS, SC, AR, ST, Spring, Test, SOS, LPS, PSY, BC, UTAD, SOW, LPSY, TS, plus minor/multiple variants and Creek/Ice jumps.
⦁ VSA patterns detect No Demand/No Supply, Stopping Volume, Buying/Selling Climax, Upthrust/Pseudo Upthrust, Bag Holding, Shake-Out, Volume Dry-Up, etc., from spread vs. average spread and volume vs. average volume with tunable thresholds.
3) Smart-money (CO) Strength
⦁ CO Strength (0–100) blends: relative volume on up/down bars, professional accumulation/distribution, no-supply/no-demand, stopping volume, Springs/UTADs and Tests, SOS/SOW, price’s position inside the range, and volume-delta vs. its MA.
⦁ Persistent accumCount / distCount counters smooth temporary noise.
4) Divergence & Effort-vs-Result
⦁ Price vs. cum volume-delta divergence highlights weakening pushes.
⦁ EVR flags “High effort / no result” and potential Bullish/Bearish reversals, or “Low effort / high result” moves that are often unsustainable.
5) Volume Profile (inside range)
⦁ A 50-bin profile accumulates volume across the detected range to derive POC, VAH/VAL (70% value area). Lines update as the active range evolves.
6) Multi-Timeframe (MTF) safety
⦁ getHTF() converts your multiplier to a valid Pine timeframe string (e.g., 60, 240, 2D, 1W), and the script falls back to current timeframe values if an HTF request returns na.
⦁ If you enter a Custom HTF, it must be strictly higher than the chart’s timeframe (validated at runtime).
7) Signals & risk model
⦁ Signals are not tied to any single pattern. A buy may require Spring/Test/Shake-out/Creek Jump or SOS plus confirmation (VSA, CO>60, Phase C/D, divergence/EVR context).
⦁ Sell is symmetrical (UTAD/Failed Spring/SOW/Ice Jump + VSA + CO<40 + Phase C/D).
⦁ Minimum confidence is configurable; SL/TP and R:R lines are drawn from range edges or recent bar extremes.
⦁ Filters: trading hours, weekend avoidance, and a minimum volume threshold (relative to average) are available to suppress low-quality contexts.
⦁ Alerts include all major events, divergences, structure/phase changes, and the gated Buy/Sell signals (with a cooldown to reduce alert spam).
Inputs (key ones you’ll actually use)
⦁ Display Settings: toggle ranges, phases, events, VSA, signals, dashboard.
⦁ MTF: Enable HTF, set Multiplier or a Custom HTF (must be higher than current).
⦁ Range Detection: period / min bars / pivot strength.
⦁ VSA: volume sensitivity & climax multiplier.
⦁ Signal Settings: minimum confidence, risk/reward labels.
⦁ Advanced Filters: trading hours, weekend avoidance, and Min Volume Filter (× avg).
⦁ Colors: phase backgrounds, structure colors, and line styling.
How to use (practical flow)
1. Choose a symbol & timeframe you normally analyze (e.g., 5–60m for entries, 4H/D for context).
2. If using MTF, pick a multiplier (e.g., 5×) or a Custom HTF (e.g., 240/4H).
3. Wait for a range to form; watch Phase and CO Strength on the Dashboard.
4. When events (e.g., Spring/Test in Phase C or UTAD in distribution) appear with favorable VSA, CO, EVR, and volume/time filters, consider the signal and review R:R lines.
5. Use POC/VA and Creek/Ice/Mid as structure references; manage risk around the range edge that generated the setup.
On-chart legend (what the letters mean)
Wyckoff events (labels)
⦁ PS Preliminary Support, SC Selling Climax, AR Automatic Rally, ST Secondary Test
⦁ Spring Spring; Test Test of Spring
⦁ SOS Sign of Strength; LPS Last Point of Support
⦁ PSY Preliminary Supply, BC Buying Climax
⦁ UTAD Upthrust After Distribution; SOW Sign of Weakness; LPSY Last Point of Supply
⦁ TS Terminal Shakeout; MS Multiple Spring
⦁ CJ Creek Jump; IJ Ice Jump
⦁ mSOS / mSOW Minor Sign of Strength/Weakness
VSA patterns (tiny labels)
⦁ ND No Demand, NS No Supply, SV Stopping Volume, BC/SC Buying/Selling Climax
⦁ PA/PD Professional Accumulation/Distribution, BH Bag Holding, DU Volume Dry-Up
⦁ SO Shake-Out, TS Test for Supply (VSA test), UT Upthrust, PUT Pseudo Upthrust
Other visuals
⦁ Range box with Creek (upper third), Ice (lower third), Mid, Quartiles
⦁ POC/VAH/VAL: yellow solid (POC), purple dotted (value area)
⦁ VWAP and Dynamic S/R (stepline)
⦁ Green/Red triangles: gated Buy/Sell signals (only if min confidence & filters are met)
⦁ Risk label near the triangle: confidence /10 and R:R
Alerts included
⦁ Core events (Spring/Test/UTAD/SOS/SOW/TS), secondary events (SC/AR/BC/LPS/LPSY), VSA patterns, EVR states, Hidden Accumulation/Distribution, HTF events, Divergences, Phase/Structure changes, and the constrained Buy/Sell signals with a cooldown.
Notes, limits & best practices
⦁ This is not a buy/sell system; it’s a context & confirmation tool. Combine with your plan, risk limits, and execution criteria.
⦁ Long, illiquid, or news-driven bars can distort volume/spread logic; filters help but cannot eliminate this.
⦁ For MTF, if an exchange doesn’t support a specific HTF, the script falls back safely to current TF values to avoid na-propagation.
⦁ Dashboard rows/size/position are user-configurable to keep charts uncluttered.
Changelog (what’s new in this version)
⦁ MTF safety & validation (Custom HTF must be above current; graceful fallbacks for request.security() na results).
⦁ Performance caching for close position & up/down bar flags; drawing cleanup to stay under label/line limits.
⦁ Volume Profile upgraded to 50 bins; VA algorithm adjusted accordingly.
⦁ Signal gating with time/day/volume filters and alert cooldown to reduce noise.
⦁ Bug guards for parameter conflicts (e.g., rangeMinBars cannot exceed rangePeriod).
Disclaimer
This script is for educational and research purposes only and does not constitute financial advice or a recommendation to buy or sell any asset. Market risk is real; always test on a demo and trade at your own discretion.
Hopiplaka Goldbach System with SignalsThis tool builds a dynamic price framework around the current market using a PO3 range and a set of mathematically derived Goldbach levels. It then scores nearby levels for quality (reliability) and produces Buy/Sell signals only when multiple, independent factors line up (price level quality, trend/“Tesla Vortex” state, ICT AMD phase, time confluence, volume bias, and momentum). The goal is to identify high-confluence inflection points rather than constant signals.
Core Concepts & Why They’re Combined
1. PO3 Range Framework
Price is segmented into a primary range (lower → upper) determined by a configurable size (3× ladder: 3, 9, 27, …, 2187).
⦁ If price sits near a boundary (configurable sensitivity), the range can auto-expand to the next 3× size to better fit current volatility.
⦁ This gives a stable “map” of the active trading area and its boundaries.
2. Goldbach Levels (Pure Hopiplaka implementation)
For each even number ≤ your precision limit, the script evaluates all prime-sum partitions (Goldbach partitions) and converts their prime ratios into price levels inside the PO3 range.
⦁ Levels are classified as Premium / Standard / Discount based on properties of the prime pair and a mathematical weighting.
⦁ Strict minimum spacing rules (exact %, OB %, liquidity-void %) prevent clutter and keep only the most meaningful levels.
3. Tesla Vortex (trend/phase strength)
A volatility/trend-aware state machine estimates whether market is in MMxM (accumulation/mean-revert like) or TREND conditions and maps price interaction with high-quality levels to phases (e.g., Order Block Formation, Distribution).
⦁ This helps filter signals: buys favored in MMxM near supportive levels; sells favored in TREND near premium/liquidity levels, etc.
4. ICT Integration (AMD, IPDA bias hooks)
A lightweight AMD phase detector classifies the recent window into Accumulation / Manipulation / Distribution and marks market structure bias. This is used as confluence with level quality and trend state.
5. Time Confluence (Goldbach time)
Swing highs/lows are checked against Goldbach-valid timestamps (based on hour+minute sums decomposable into prime pairs). Repeated alignment adds time-bias confidence. When price and time align, level reliability is boosted.
6. Volume & Liquidity Context
A rolling volume baseline marks High/Low Volume Bias; levels can be volume-weighted (raising or lowering their reliability). Proximity to PO3 extremes flags pending liquidity sweeps.
Why this mashup?
The system blends price geometry (PO3 + Goldbach), state/trend (Tesla Vortex), market-microstructure (ICT AMD), time confluence, and volume/liquidity into one numerically scored signal. Each component answers a different question; together they reduce false positives and favor high-quality trades near meaningful levels.
What You’ll See on the Chart
⦁ PO3 Range Boundaries: two dashed lines (“lower” and “upper”). Auto-expand darkens the boundary style slightly.
⦁ Goldbach Levels: horizontal lines colored by classification and context:
⦁ Premium (strong premium band), Standard, Discount
⦁ OB (Order-Block candidate), LV (Liquidity Void)
⦁ TESLA node (trend/phase aligned)
⦁ Heavier width = higher reliability; dashed/dotted styles encode class differences.
⦁ PO3 Liquidity Boxes: narrow yellow shaded bands above/below each level (configurable pip distance).
⦁ Markers
⦁ ▲ Buy arrow below bar when a Buy signal triggers
⦁ ▼ Sell arrow above bar when a Sell signal triggers
⦁ ● Small dot when price touches a Goldbach level
⦁ Data-window plots:
⦁ Tesla Vortex Strength (numeric)
⦁ Time Bias (positive = bullish, negative = bearish)
⦁ Volume Bias (+1 high / −1 low)
⦁ Signal Strength (+ for buy / − for sell, zero when no signal)
⦁ Label Legend (on level tags)
⦁ TESLA – Tesla-aligned level node
⦁ OB – Order-block-quality zone
⦁ LV – Liquidity-void zone
⦁ Premium / Standard / Discount – Level class
⦁ Gxx – Even number used to build the level (Goldbach reference)
⦁ Reliability – Final score after time/volume/tesla weighting
⦁ Optional extras: Vol (relative volume weight), Time (time-confluence strength)
How Signals Are Generated
A signal is proposed when price comes within a minimum distance of a high-reliability level. It is then accepted only if enough of these independent checks pass (you control the required count):
1. Tesla Vortex state matches direction (e.g., MMxM with buy; TREND with sell).
2. ICT AMD phase aligns (Accumulation → buy bias; Distribution → sell bias).
3. Goldbach time bias supports the direction.
4. Volume bias supportive (high-volume context boosts conviction).
5. Level quality (TESLA node or Premium class) is high.
6. Momentum alignment (recent 2–3 bars in the same direction).
Only when confluence ≥ your threshold and confidence ≥ 0.5 (scaled by sensitivity) will a Buy/Sell arrow print. Cooldown prevents rapid repeats.
Inputs (key ones)
⦁ PO3 Settings: range size, auto-expansion toggle, expansion sensitivity, liquidity band distance.
⦁ Goldbach Mathematics: precision limit, exact spacing rules, spacing for OB/LV classes.
⦁ Trading Signals: master toggle, sensitivity, min reliability, confluence required, cooldown, min distance to level, markers on/off.
⦁ Tesla Vortex / ICT: enable Vortex, sensitivity; enable AMD/IPDA analysis and lookback.
⦁ Time & Volume: enable Goldbach time and weighting; volume lookback; liquidity-pool detection.
⦁ Display: show historical/future projections, number of future bars, labels, path/phase overlays.
⦁ Colors: full palette per class/context (premium/discount/OB/LV/Tesla/time/volume, buy/sell/goldbach hit).
Alerts Included
⦁ Signals: “BUY Signal Generated”, “SELL Signal Generated”
⦁ Level Interactions: “Goldbach Level Hit”; “Near Goldbach Level”; “Tesla Vortex Node”; “Premium Level Alert”
⦁ PO3: “PO3 Upper Break”, “PO3 Lower Break”, “PO3 Range Expansion”
⦁ State Changes: “Tesla Vortex Phase Change”
⦁ Context: “Liquidity Sweep Imminent”, “Strong Time Confluence”
You can wire these to webhooks or notifications.
Suggested Workflow
1. Choose PO3 size that matches your instrument’s volatility; keep Auto-Expansion ON initially.
2. Set confluence threshold (start at 3–4) and cooldown (e.g., 10 bars).
3. Keep Time and Volume modules ON for additional reliability weighting.
4. Use arrows as filters, not blind entries—confirm with your execution plan and risk rules.
5. Prefer signals near Premium/Discount TESLA nodes that also show time confluence and supportive volume.
Practical Notes & Limitations
⦁ The mathematical framework is deterministic, but market execution is not—always manage risk.
⦁ Future projections and heavy labeling can be resource-intensive; tune visibility if performance drops.
⦁ If a market is extremely illiquid or gap-prone, spacing/filters may hide many levels (by design).
Disclaimer
This script is for educational and research purposes only and is not financial advice. Trading involves risk. You are responsible for your own decisions.
Live Market - Performance MonitorLive Market — Performance Monitor
Study material (no code) — step-by-step training guide for learners
________________________________________
1) What this tool is — short overview
This indicator is a live market performance monitor designed for learning. It scans price, volume and volatility, detects order blocks and trendline events, applies filters (volume & ATR), generates trade signals (BUY/SELL), creates simple TP/SL trade management, and renders a compact dashboard summarizing market state, risk and performance metrics.
Use it to learn how multi-factor signals are constructed, how Greeks-style sensitivity is replaced by volatility/ATR reasoning, and how a live dashboard helps monitor trade quality.
________________________________________
2) Quick start — how a learner uses it (step-by-step)
1. Add the indicator to a chart (any ticker / timeframe).
2. Open inputs and review the main groups: Order Block, Trendline, Signal Filters, Display.
3. Start with defaults (OB periods ≈ 7, ATR multiplier 0.5, volume threshold 1.2) and observe the dashboard on the last bar.
4. Walk the chart back in time (use the last-bar update behavior) and watch how signals, order blocks, trendlines, and the performance counters change.
5. Run the hands-on labs below to build intuition.
________________________________________
3) Main configurable inputs (what you can tweak)
• Order Block Relevant Periods (default ~7): number of consecutive candles used to define an order block.
• Min. Percent Move for Valid OB (threshold): minimum percent move required for a valid order block.
• Number of OB Channels: how many past order block lines to keep visible.
• Trendline Period (tl_period): pivot lookback for detecting highs/lows used to draw trendlines.
• Use Wicks for Trendlines: whether pivot uses wicks or body.
• Extension Bars: how far trendlines are projected forward.
• Use Volume Filter + Volume Threshold Multiplier (e.g., 1.2): requires volume to be greater than multiplier × average volume.
• Use ATR Filter + ATR Multiplier: require bar range > ATR × multiplier to filter noise.
• Show Targets / Table settings / Colors for visualization.
________________________________________
4) Core building blocks — what the script computes (plain language)
Price & trend:
• Spot / LTP: current close price.
• EMA 9 / 21 / 50: fast, medium, slow moving averages to define short/medium trend.
o trend_bullish: EMA9 > EMA21 > EMA50
o trend_bearish: EMA9 < EMA21 < EMA50
o trend_neutral: otherwise
Volatility & noise:
• ATR (14): average true range used for dynamic target and filter sizing.
• dynamic_zone = ATR × atr_multiplier: minimum bar range required for meaningful move.
• Annualized volatility: stdev of price changes × sqrt(252) × 100 — used to classify volatility (HIGH/MEDIUM/LOW).
Momentum & oscillators:
• RSI 14: overbought/oversold indicator (thresholds 70/30).
• MACD: EMA(12)-EMA(26) and a 9-period signal line; histogram used for momentum direction and strength.
• Momentum (ta.mom 10): raw momentum over 10 bars.
Mean reversion / band context:
• Bollinger Bands (20, 2σ): upper, mid, lower.
o price_position measures where price sits inside the band range as 0–100.
Volume metrics:
• avg_volume = SMA(volume, 20) and volume_spike = volume > avg_volume × volume_threshold
o volume_ratio = volume / avg_volume
Support & Resistance:
• support_level = lowest low over 20 bars
• resistance_level = highest high over 20 bars
• current_position = percent of price between support & resistance (0–100)
________________________________________
5) Order Block detection — concept & logic
What it tries to find: a bar (the base) followed by N candles in the opposite direction (a classical order block setup), with a minimum % move to qualify. The script records the high/low of the base candle, averages them, and plots those levels as OB channels.
How learners should think about it (conceptual):
1. An order block is a signature area where institutions (theory) left liquidity — often seen as a large bar followed by a sequence of directional candles.
2. This indicator uses a configurable number of subsequent candles to confirm that the pattern exists.
3. When found, it stores and displays the base candle’s high/low area so students can see how price later reacts to those zones.
Implementation note for learners: the tool keeps a limited history of OB lines (ob_channels). When new OBs exceed the count, the oldest lines are removed — good practice to avoid clutter.
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6) Trendline detection — idea & interpretation
• The script finds pivot highs and lows using a symmetric lookback (tl_period and half that as right/left).
• It then computes a trendline slope from successive pivots and projects the line forward (extension_bars).
• Break detection: Resistance break = close crosses above the projected resistance line; Support break = close crosses below projected support.
Learning tip: trendlines here are computed from pivot points and time. Watch how changing tl_period (bigger = smoother, fewer pivots) alters the trendlines and break signals.
________________________________________
7) Signal generation & filters — step-by-step
1. Primary triggers:
o Bullish trigger: order block bullish OR resistance trendline break.
o Bearish trigger: bearish order block OR support trendline break.
2. Filters applied (both must pass unless disabled):
o Volume filter: volume must be > avg_volume × volume_threshold.
o ATR filter: bar range (high-low) must exceed ATR × atr_multiplier.
o Not in an existing trade: new trades only start if trade_active is false.
3. Trend confirmation:
o The primary trigger is only confirmed if trend is bullish/neutral for buys or bearish/neutral for sells (EMA alignment).
4. Result:
o When confirmed, a long or short trade is activated with TP/SL calculated from ATR multiples.
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8) Trade management — what the tool does after a signal
• Entry management: the script marks a trade as trade_active and sets long_trade or short_trade flags.
• TP & SL rules:
o Long: TP = high + 2×ATR ; SL = low − 1×ATR
o Short: TP = low − 2×ATR ; SL = high + 1×ATR
• Monitoring & exit:
o A trade closes when price reaches TP or SL.
o When TP/SL hit, the indicator updates win_count and total_pnl using a very simple calculation (difference between TP/SL and previous close).
o Visual lines/labels are drawn for TP and updated as the trade runs.
Important learner notes:
• The script does not store a true entry price (it uses close in its P&L math), so PnL is an approximation — treat this as a learning proxy, not a position accounting system.
• There’s no sizing, slippage, or fee accounted — students must manually factor these when translating to real trades.
• This indicator is not a backtesting strategy; strategy.* functions would be needed for rigorous backtest results.
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9) Signal strength & helper utilities
• Signal strength is a composite score (0–100) made up of four signals worth 25 points each:
1. RSI extreme (overbought/oversold) → 25
2. Volume spike → 25
3. MACD histogram magnitude increasing → 25
4. Trend existence (bull or bear) → 25
• Progress bars (text glyphs) are used to visually show RSI and signal strength on the table.
Learning point: composite scoring is a way to combine orthogonal signals — study how changing weights changes outcomes.
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10) Dashboard — how to read each section (walkthrough)
The dashboard is split into sections; here's how to interpret them:
1. Market Overview
o LTP / Change%: immediate price & daily % change.
2. RSI & MACD
o RSI value plus progress bar (overbought 70 / oversold 30).
o MACD histogram sign indicates bullish/bearish momentum.
3. Volume Analysis
o Volume ratio (current / average) and whether there’s a spike.
4. Order Block Status
o Buy OB / Sell OB: the average base price of detected order blocks or “No Signal.”
5. Signal Status
o 🔼 BUY or 🔽 SELL if confirmed, or ⚪ WAIT.
o No-trade vs Active indicator summarizing market readiness.
6. Trend Analysis
o Trend direction (from EMAs), market sentiment score (composite), volatility level and band/position metrics.
7. Performance
o Win Rate = wins / signals (percentage)
o Total PnL = cumulative PnL (approximate)
o Bull / Bear Volume = accumulated volumes attributable to signals
8. Support & Resistance
o 20-bar highest/lowest — use as nearby reference points.
9. Risk & R:R
o Risk Level from ATR/price as a percent.
o R:R Ratio computed from TP/SL if a trade is active.
10. Signal Strength & Active Trade Status
• Numeric strength + progress bar and whether a trade is currently active with TP/SL display.
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11) Alerts — what will notify you
The indicator includes pre-built alert triggers for:
• Bullish confirmed signal
• Bearish confirmed signal
• TP hit (long/short)
• SL hit (long/short)
• No-trade zone
• High signal strength (score > 75%)
Training use: enable alerts during a replay session to be notified when the indicator would have signalled.
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12) Labs — hands-on exercises for learners (step-by-step)
Lab A — Order Block recognition
1. Pick a 15–30 minute timeframe on a liquid ticker.
2. Use default OB periods (7). Mark each time the dashboard shows a Buy/Sell OB.
3. Manually inspect the chart at the base candle and the following sequence — draw the OB zone by hand and watch later price reactions to it.
4. Repeat with OB periods 5 and 10; note stability vs noise.
Lab B — Trendline break confirmation
1. Increase trendline period (e.g., 20), watch trendlines form from pivots.
2. When a resistance break is flagged, compare with MACD & volume: was momentum aligned?
3. Note false breaks vs confirmed moves — change extension_bars to see projection effects.
Lab C — Filter sensitivity
1. Toggle Use Volume Filter off, and record the number and quality of signals in a 2-day window.
2. Re-enable volume filter and change threshold from 1.2 → 1.6; note how many low-quality signals are filtered out.
Lab D — Trade management simulation
1. For each signalled trade, record the time, close entry approximation, TP, SL, and eventual hit/miss.
2. Compute actual PnL if you had entered at the open of the next bar to compare with the script’s PnL math.
3. Tabulate win rate and average R:R.
Lab E — Performance review & improvement
1. Build a spreadsheet of signals over 30–90 periods with columns: Date, Signal type, Entry price (real), TP, SL, Exit, PnL, Notes.
2. Analyze which filters or indicators contributed most to winners vs losers and adjust weights.
________________________________________
13) Common pitfalls, assumptions & implementation notes (things to watch)
• P&L simplification: total_pnl uses close as a proxy entry price. Real entry/exit prices and slippage are not recorded — so PnL is approximate.
• No position sizing or money management: the script doesn’t compute position size from equity or risk percent.
• Signal confirmation logic: composite "signal_strength" is a simple 4×25 point scheme — explore different weights or additional signals.
• Order block detection nuance: the script defines the base candle and checks the subsequent sequence. Be sure to verify whether the intended candle direction (base being bullish vs bearish) aligns with academic/your trading definition — read the code carefully and test.
• Trendline slope over time: slope is computed using timestamps; small differences may make lines sensitive on very short timeframes — using bar_index differences is usually more stable.
• Not a true backtester: to evaluate performance statistically you must transform the logic into a strategy script that places hypothetical orders and records exact entry/exit prices.
________________________________________
14) Suggested improvements for advanced learners
• Record true entry price & timestamp for accurate PnL.
• Add position sizing: risk % per trade using SL distance and account size.
• Convert to strategy. (Pine Strategy)* to run formal backtests with equity curves, drawdowns, and metrics (Sharpe, Sortino).
• Log trades to an external spreadsheet (via alerts + webhook) for offline analysis.
• Add statistics: average win/loss, expectancy, max drawdown.
• Add additional filters: news time blackout, market session filters, multi-timeframe confirmation.
• Improve OB detection: combine wick/body, volume spike at base bar, and liquidity sweep detection.
________________________________________
15) Glossary — quick definitions
• ATR (Average True Range): measure of typical range; used to size targets and stops.
• EMA (Exponential Moving Average): trend smoothing giving more weight to recent prices.
• RSI (Relative Strength Index): momentum oscillator; >70 overbought, <30 oversold.
• MACD: momentum oscillator using difference of two EMAs.
• Bollinger Bands: volatility bands around SMA.
• Order Block: a base candle area with subsequent confirmation candles; a zone of institutional interest (learning model).
• Pivot High/Low: local turning point defined by candles on both sides.
• Signal Strength: combined score from multiple indicators.
• Win Rate: proportion of signals that hit TP vs total signals.
• R:R (Risk:Reward): ratio of potential reward (TP distance) to risk (entry to SL).
________________________________________
16) Limitations & assumptions (be explicit)
• This is an indicator for learning — not a trading robot or broker connection.
• No slippage, fees, commissions or tie-in to real orders are considered.
• The logic is heuristic (rule-of-thumb), not a guarantee of performance.
• Results are sensitive to timeframe, market liquidity, and parameter choices.
________________________________________
17) Practical classroom / study plan (4 sessions)
• Session 1 — Foundations: Understand EMAs, ATR, RSI, MACD, Bollinger Bands. Run the indicator and watch how these numbers change on a single day.
• Session 2 — Zones & Filters: Study order blocks and trendlines. Test volume & ATR filters and note changes in false signals.
• Session 3 — Simulated trading: Manually track 20 signals, compute real PnL and compare to the dashboard.
• Session 4 — Improvement plan: Propose changes (e.g., better PnL accounting, alternative OB rule) and test their impact.
________________________________________
18) Quick reference checklist for each signal
1. Was an order block or trendline break detected? (primary trigger)
2. Did volume meet threshold? (filter)
3. Did ATR filter (bar size) show a real move? (filter)
4. Was trend aligned (EMA 9/21/50)? (confirmation)
5. Signal confirmed → mark entry approximation, TP, SL.
6. Monitor dashboard (Signal Strength, Volatility, No-trade zone, R:R).
7. After exit, log real entry/exit, compute actual PnL, update spreadsheet.
________________________________________
19) Educational caveat & final note
This tool is built for training and analysis: it helps you see how common technical building blocks combine into trade ideas, but it is not a trading recommendation. Use it to develop judgment, to test hypotheses, and to design robust systems with proper backtesting and risk control before risking capital.
________________________________________
20) Disclaimer (must include)
Training & Educational Only — This material and the indicator are provided for educational purposes only. Nothing here is investment advice or a solicitation to buy or sell financial instruments. Past simulated or historical performance does not predict future results. Always perform full backtesting and risk management, and consider seeking advice from a qualified financial professional before trading with real capital.
________________________________________
CandelaCharts - Mean Reversion Oscillator 📝 Overview
The Mean Reversion Oscillator (MRO) is a bounded 0–100 indicator that shows how far the price has deviated from its statistical mean. Normalizing deviations into a consistent scale helps traders spot overbought/oversold conditions, potential mean reversion setups, and momentum shifts around a moving average.
📦 Features
Bounded scale (0–100) for easy recognition of stretched conditions.
Customizable MA & StdDev periods for different trading horizons.
Dynamic coloring: Red = Overbought, Green = Oversold, Blue = Neutral
Visual aids: Background shading in OB/OS zones + 50 midline.
⚙️ Settings
MA Length – Period for the moving average baseline.
StdDev Length – Standard deviation window. Tip: match the MA length for smoother results.
Overbought Level – Threshold for stretched highs.
Oversold Level – Threshold for stretched lows.
⚡️ Showcase
Overbought/Oversold Zones
Divergences
📒 Usage
The Mean Reversion Oscillator (MRO) is best used as a context tool, not as a standalone buy/sell signal generator. Its primary purpose is to tell you when the price is statistically stretched relative to its average, so you can anticipate a potential return toward the mean.
Add to chart – Paste the script in TradingView and load it in a separate pane.
Set MA Length – Use 20–50 for intraday, 100–200 for swing/position trading.
Match StdDev Length – Keep it close to the MA Length to avoid distortion (e.g., MA 200 → StdDev 200).
Interpret readings:
>70 (Overbought) – Price stretched high, reversion or slowdown likely.
<30 (Oversold) – Price stretched low, bounce potential.
50 (Midline) – Neutral, momentum shift point.
Use with confluence – Strongest signals occur when MRO extremes align with S/R levels, trend filters, or volume cues.
Adjust thresholds – 70/30 is balanced; 80/20 gives fewer but stronger signals, 60/40 gives more but weaker ones.
Stay trend-aware – In strong trends, OB/OS can persist. Always check higher timeframe bias before fading moves.
🚨 Alerts
The indicator does not provide any alerts!
⚠️ Disclaimer
These tools are exclusively available on the TradingView platform.
Our charting tools are intended solely for informational and educational purposes and should not be regarded as financial, investment, or trading advice. They are not designed to predict market movements or offer specific recommendations. Users should be aware that past performance is not indicative of future results and should not rely on these tools for financial decisions. By using these charting tools, the purchaser agrees that the seller and creator hold no responsibility for any decisions made based on information provided by the tools. The purchaser assumes full responsibility and liability for any actions taken and their consequences, including potential financial losses or investment outcomes that may result from the use of these products.
By purchasing, the customer acknowledges and accepts that neither the seller nor the creator is liable for any undesired outcomes stemming from the development, sale, or use of these products. Additionally, the purchaser agrees to indemnify the seller from any liability. If invited through the Friends and Family Program, the purchaser understands that any provided discount code applies only to the initial purchase of Candela's subscription. The purchaser is responsible for canceling or requesting cancellation of their subscription if they choose not to continue at the full retail price. In the event the purchaser no longer wishes to use the products, they must unsubscribe from the membership service, if applicable.
We do not offer reimbursements, refunds, or chargebacks. Once these Terms are accepted at the time of purchase, no reimbursements, refunds, or chargebacks will be issued under any circumstances.
By continuing to use these charting tools, the user confirms their understanding and acceptance of these Terms as outlined in this disclaimer.
Moon Scalper v3 + VSAMoon Scalper v3 is a high-precision scalping indicator optimized for the 15-minute chart. It delivers clean buy/sell signals with TP1 (1:1 risk-reward) exits using layered confirmations:
• **Volatility Bands** — SMA + multiplier detect expansion zones
• **EMA Filter (200)** — ensures trades align with trend
• **RSI Range Filter** — avoids extreme overbought/oversold traps (buy: 52–62, sell: 38–48)
• **Volume Spike Filter** — filters for institutional activity (vol > 1.4×SMA)
• **VSA Confirmation** — requires wide-spread, high-volume bars with reclaim (volume × 1.4, spread × 1.5, reclaim 50%)
**Usage Notes:**
Best used on 15m timeframe for liquid pairs (e.g., BTCUSDT, ETHUSDT). Signals appear as “BUY” / “SELL” labels on chart. Defaults yield high TP1 hit rate; use only during active sessions (e.g., London/NY) for best accuracy.
**Disclaimer:**
This indicator is for educational purposes only. Past performance is not a guarantee of future results. Always backtest before live trading and manage risk responsibly.
EMA Oscillator [Alpha Extract]A precision mean reversion analysis tool that combines advanced Z-score methodology with dual threshold systems to identify extreme price deviations from trend equilibrium. Utilizing sophisticated statistical normalization and adaptive percentage-based thresholds, this indicator provides high-probability reversal signals based on standard deviation analysis and dynamic range calculations with institutional-grade accuracy for systematic counter-trend trading opportunities.
🔶 Advanced Statistical Normalization
Calculates normalized distance between price and exponential moving average using rolling standard deviation methodology for consistent interpretation across timeframes. The system applies Z-score transformation to quantify price displacement significance, ensuring statistical validity regardless of market volatility conditions.
// Core EMA and Oscillator Calculation
ema_values = ta.ema(close, ema_period)
oscillator_values = close - ema_values
rolling_std = ta.stdev(oscillator_values, ema_period)
z_score = oscillator_values / rolling_std
🔶 Dual Threshold System
Implements both statistical significance thresholds (±1σ, ±2σ, ±3σ) and percentage-based dynamic thresholds calculated from recent oscillator range extremes. This hybrid approach ensures consistent probability-based signals while adapting to varying market volatility regimes and maintaining signal relevance during structural market changes.
// Statistical Thresholds
mild_threshold = 1.0 // ±1σ (68% confidence)
moderate_threshold = 2.0 // ±2σ (95% confidence)
extreme_threshold = 3.0 // ±3σ (99.7% confidence)
// Percentage-Based Dynamic Thresholds
osc_high = ta.highest(math.abs(z_score), lookback_period)
mild_pct_thresh = osc_high * (mild_pct / 100.0)
moderate_pct_thresh = osc_high * (moderate_pct / 100.0)
extreme_pct_thresh = osc_high * (extreme_pct / 100.0)
🔶 Signal Generation Framework
Triggers buy/sell alerts when Z-score crosses extreme threshold boundaries, indicating statistically significant price deviations with high mean reversion probability. The system generates continuation signals at moderate levels and reversal signals at extreme boundaries with comprehensive alert integration.
// Extreme Signal Detection
sell_signal = ta.crossover(z_score, selected_extreme)
buy_signal = ta.crossunder(z_score, -selected_extreme)
// Dynamic Color Coding
signal_color = z_score >= selected_extreme ? #ff0303 : // Extremely Overbought
z_score >= selected_moderate ? #ff6a6a : // Overbought
z_score >= selected_mild ? #b86456 : // Mildly Overbought
z_score > -selected_mild ? #a1a1a1 : // Neutral
z_score > -selected_moderate ? #01b844 : // Mildly Oversold
z_score > -selected_extreme ? #00ff66 : // Oversold
#00ff66 // Extremely Oversold
🔶 Visual Structure Analysis
Provides a six-tier color gradient system with dynamic background zones indicating mild, moderate, and extreme conditions. The histogram visualization displays Z-score intensity with threshold reference lines and zero-line equilibrium context for precise mean reversion timing.
snapshot
4H
1D
🔶 Adaptive Threshold Selection
Features intelligent threshold switching between statistical significance levels and percentage-based dynamic ranges. The percentage system automatically adjusts to current volatility conditions using configurable lookback periods, while statistical thresholds maintain consistent probability-based signal generation across market cycles.
🔶 Performance Optimization
Utilizes efficient rolling calculations with configurable EMA periods and threshold parameters for optimal performance across all timeframes. The system includes comprehensive alert functionality with customizable notification preferences and visual signal overlay options.
🔶 Market Oscillator Interpretation
Z-score > +3σ indicates statistically significant overbought conditions with high reversal probability, while Z-score < -3σ signals extreme oversold levels suitable for counter-trend entries. Moderate thresholds (±2σ) capture 95% of normal price distributions, making breaches statistically significant for systematic trading approaches.
snapshot
🔶 Intelligent Signal Management
Automatic signal filtering prevents false alerts through extreme threshold crossover requirements, while maintaining sensitivity to genuine statistical deviations. The dual threshold system provides both conservative statistical approaches and adaptive market condition responses for varying trading styles.
Why Choose EMA Oscillator ?
This indicator provides traders with statistically-grounded mean reversion analysis through sophisticated Z-score normalization methodology. By combining traditional statistical significance thresholds with adaptive percentage-based extremes, it maintains effectiveness across varying market conditions while delivering high-probability reversal signals based on quantifiable price displacement from trend equilibrium, enabling systematic counter-trend trading approaches with defined statistical confidence levels and comprehensive risk management parameters.
Triple Momentum Indicator ALERT CODE (opt & fut )Nifty and Bank 🚀High Accuracy Triple Momentum Strategy - no repainting HIGH WINRATE
This system is designed for job holders who want to invest and trade using a proven, back tested strategy without needing to sit in front of charts all day.
📢 Need auto-trade alerts?
its an dedicated **indicator version with real-time BUY/SELL/EXIT alerts**
Strategy code review
📊 Results:
Historical Win Rate: 90.0% (314/349 signals)
Study Period: 1 Year on NIFTY Futures
Educational Return: 81.4% annualized
Max Drawdown: ₹49,132.50
📊 Optimized Parameters:
"This strategy achieves 90% win rate on NIFTY Futures using optimized settings:
📈PARAM A: 69
📉PARAM B: 34
⚡PARAM C : 10
🎯 Source: Close
📊PARAM D: 39
🔴 Use Live Bar Signals: Enabled (may repaint)
💰 Long Profit %: 0.09
💸 Short Profit %: 0.05
🔎 Clean BUY / SELL / EXIT logic, optimized for high-probability trades
📧 Educational Access:
Send TradingView message for access.
📌 **Important Notes:**
- 🧪 This tool has been **extensively tested**, and results shown are from actual backtests on TradingView
🔒 Access is invite-only for quality control
@How to Create Alerts in TradingView (Step by Step)
Add the Indicator to Your Chart
Open your chart in TradingView.
Add your custom indicator (from Pine Script) to the chart.
Set Your Indicator Parameters@
Click on the indicator’s name in the chart or in the “Indicators” list.
Click the gear/settings icon.
Enter the suggested parameters (Long Length: 69, Short Length: 34, etc.), then click OK.
Open the Alert Creation Window
Click the Alerts (clock/bell) icon at the top of the TradingView interface.
Or right-click on the chart and select “Add Alert”.
Configure Each Alert
In the “Condition” dropdown, select your indicator.
Choose the specific alert condition (e.g., Buy Alert, Sell Alert, Exit Buy Alert, Exit Sell Alert) from the list.
Set the “Options” to Once per bar close.
(Optional) Enter your webhook URL if you want alerts to be sent to another app or bot.
In the Message box, enter the JSON format for automation:
For Buy: {"SYMBOL":"{{ticker}}","ACTION":"BUY","PRICE":{{close}}}
For Sell: {"SYMBOL":"{{ticker}}","ACTION":"SELL","PRICE":{{close}}}
For Buy Exit: {"SYMBOL":"{{ticker}}","ACTION":"BUY_EXIT","PRICE":{{close}}}
For Sell Exit: {"SYMBOL":"{{ticker}}","ACTION":"SELL_EXIT","PRICE":{{close}}}
Save the Alert
Click Create to save your alert.
Repeat
Repeat steps (Buy, Sell, Buy Exit, Sell Exit).
Manage Alerts
You can edit, remove, or pause alerts any time in the “Alerts” panel at the bottom of TradingView.
⚠️ Disclaimer:
Shared for learning and research purposes only. Not financial advice. Past educational results don't guarantee future outcomes. Trading involves risk of loss. We are not SEBI registered.
#MomentumStrategy #TradingEducation #InviteOnly #NIFTYFutures #AlgoTrading #EducationalStrategy #NIFTYOptions
Vwapbot (VWAP + Ut Bot Alerts)Vwapbot (VWAP + Ut Bot Alerts) - Complete Guide
This Pine Script indicator combines two powerful trading tools: Volume Weighted Average Price (VWAP) and the UT Bot trend-following system. Here's a comprehensive breakdown:
What This Indicator Does
The indicator provides:
1. VWAP calculation with deviation bands
2. UT Bot trend signals with trailing stops
3. Combined confluence alerts when both indicators align
4. Visual information table showing current market conditions
Core Components
1. VWAP (Volume Weighted Average Price)
What it is: VWAP calculates the average price weighted by volume, giving more importance to high-volume periods.
Settings:
• VWAP Source: Price used for calculation (default: hlc3 - average of high, low, close)
• VWAP Anchor: Reset period (Session/Week/Month/Quarter/Year)
Usage:
• Price above VWAP = bullish bias
• Price below VWAP = bearish bias
• VWAP acts as dynamic support/resistance
2. VWAP Deviation Bands
What they show: Statistical boundaries around VWAP based on price volatility
Settings:
• Standard Deviation Multiplier: How far the bands extend (default: 1.0)
• Show Bands: Toggle visibility
Usage:
• Gray dashed lines: 1 standard deviation bands (normal price range)
• Red dotted lines: 2 standard deviation bands (extreme price levels)
• Price touching outer bands may indicate reversal opportunities
3. UT Bot (Ultimate Trend Bot)
What it does: Creates a trailing stop system that follows trends and signals reversals
Settings:
• Key Value: Sensitivity multiplier (1.0 = balanced, lower = more sensitive)
• ATR Period: Lookback period for volatility calculation (default: 10)
How it works:
• Uses ATR (Average True Range) to calculate dynamic support/resistance levels
• Green line = uptrend (trailing stop below price)
• Red line = downtrend (trailing stop above price)
4. UT Bot Alerts are integrated to the logic of Volume Profile i,e VWAP, the UT Bot Stop trailing line plot its data and change trends obtaining it's logic from the VWAP and Standard Deviation bands, thus it differs in it's logic of UT Bot alerts from other indicators.
Visual Elements
On-Chart Displays:
1. Blue line: VWAP
2. Gray lines: 1st deviation bands
3. Red lines: 2nd deviation bands
4. Green/Red thick line: UT Bot trailing stop
5. Green triangles up: Buy signals
6. Red triangles down: Sell signals
7. Background color: Light green (bullish) / Light red (bearish)
Information Table (Top Right):
• VWAP: Current VWAP value
• UT Bot: Current trailing stop level
• Trend: Bullish/Bearish status
• Price vs VWAP: Above/Below comparison
• Deviation: Percentage distance from VWAP
• Volume: Current bar volume
Trading Signals
Basic Signals:
1. UT Bot Buy: Green triangle when trend turns bullish
2. UT Bot Sell: Red triangle when trend turns bearish
3. VWAP Cross Above: Price crosses above VWAP
4. VWAP Cross Below: Price crosses below VWAP
Confluence Signals :
1. Bullish Confluence: UT Bot buy signal + Price above VWAP
2. Bearish Confluence: UT Bot sell signal + Price below VWAP
How to Use This Indicator
For Trend Following:
1. Enter long when you get a bullish confluence signal
2. Enter short when you get a bearish confluence signal
3. Exit when the UT Bot trend changes color
For Mean Reversion:
1. Look for reversals when price hits the 2nd deviation bands
2. Confirm with UT Bot signals
3. Target return to VWAP
For Support/Resistance:
1. Use VWAP as dynamic support in uptrends, resistance in downtrends
2. Watch for bounces at deviation bands
3. Confirm direction with UT Bot trend color
Best Practices
Timeframes:
• Intraday: Use Session VWAP anchor
• Swing trading: Use Weekly/Monthly anchors
• Position trading: Use Monthly/Quarterly anchors
Risk Management:
• Stop loss: Below/above the UT Bot trailing stop
• Position sizing: Smaller positions when price is at extreme deviation bands
• Confluence: Wait for both VWAP and UT Bot alignment for strongest signals
Market Conditions:
• Trending markets: Focus on UT Bot signals and VWAP direction bias
• Ranging markets: Use deviation bands for entry/exit points
• High volume periods: VWAP becomes more significant
Alert System
The indicator provides 6 types of alerts:
1. UT Bot buy/sell signals
2. VWAP crossover alerts
3. Confluence alerts (most important)
Set up alerts for confluence signals to catch the highest probability setups when both indicators align.
This indicator works best when combined with proper risk management and used in conjunction with market structure analysis. The confluence signals provide the highest probability entries, while the individual components help with market.
Advice from the publisher:
For using with Indices e.g NIFTY 50, BANKNIFTY etc. use parameters:
UT BOT Key Value : 1
UT BOT ATR Period : 10
Standard Deviation Multiplier : 1 {Default}
For using with commodities e.g NATURALGAS, CRUDEOIL etc. use parameters:
UT BOT Key Value : 2
UT BOT ATR Period : 7
Standard Deviation Multiplier : 1 {Default}
Advanced Volume Profile Pro Delta + POC + VAH/VAL# Advanced Volume Profile Pro - Delta + POC + VAH/VAL Analysis System
## WHAT THIS SCRIPT DOES
This script creates a comprehensive volume profile analysis system that combines traditional volume-at-price distribution with delta volume calculations, Point of Control (POC) identification, and Value Area (VAH/VAL) analysis. Unlike standard volume indicators that show only total volume over time, this script analyzes volume distribution across price levels and estimates buying vs selling pressure using multiple calculation methods to provide deeper market structure insights.
## WHY THIS COMBINATION IS ORIGINAL AND USEFUL
**The Problem Solved:** Traditional volume indicators show when volume occurs but not where price finds acceptance or rejection. Standalone volume profiles lack directional bias information, while basic delta calculations don't provide structural context. Traders need to understand both volume distribution AND directional sentiment at key price levels.
**The Solution:** This script implements an integrated approach that:
- Maps volume distribution across price levels using configurable row density
- Estimates delta (buying vs selling pressure) using three different methodologies
- Identifies Point of Control (highest volume price level) for key support/resistance
- Calculates Value Area boundaries where 70% of volume traded
- Provides real-time alerts for key level interactions and volume imbalances
**Unique Features:**
1. **Developing POC Visualization**: Real-time tracking of Point of Control migration throughout the session via blue dotted trail, revealing institutional accumulation/distribution patterns before they complete
2. **Multi-Method Delta Calculation**: Price Action-based, Bid/Ask estimation, and Cumulative methods for different market conditions
3. **Adaptive Timeframe System**: Auto-adjusts calculation parameters based on chart timeframe for optimal performance
4. **Flexible Profile Types**: N Bars Back (precise control), Days Back (calendar-based), and Session-based analysis modes
5. **Advanced Imbalance Detection**: Identifies and highlights significant buying/selling imbalances with configurable thresholds
6. **Comprehensive Alert System**: Monitors POC touches, Value Area entry/exit, and major volume imbalances
## HOW THE SCRIPT WORKS TECHNICALLY
### Core Volume Profile Methodology:
**1. Price Level Distribution:**
- Divides price range into user-defined rows (10-50 configurable)
- Calculates row height: `(Highest Price - Lowest Price) / Number of Rows`
- Distributes each bar's volume across price levels it touched proportionally
**2. Delta Volume Calculation Methods:**
**Price Action Method:**
```
Price Range = High - Low
Buy Pressure = (Close - Low) / Price Range
Sell Pressure = (High - Close) / Price Range
Buy Volume = Total Volume × Buy Pressure
Sell Volume = Total Volume × Sell Pressure
Delta = Buy Volume - Sell Volume
```
**Bid/Ask Estimation Method:**
```
Average Price = (High + Low + Close) / 3
Buy Volume = Close > Average ? Volume × 0.6 : Volume × 0.4
Sell Volume = Total Volume - Buy Volume
```
**Cumulative Method:**
```
Buy Volume = Close > Open ? Volume : Volume × 0.3
Sell Volume = Close ≤ Open ? Volume : Volume × 0.3
```
**3. Point of Control (POC) Identification:**
- Scans all price levels to find maximum volume concentration
- POC represents the price level with highest trading activity
- Acts as significant support/resistance level
- **Developing POC Feature**: Tracks POC evolution in real-time via blue dotted trail, showing how institutional interest migrates throughout the session. Upward POC migration indicates accumulation patterns, downward migration suggests distribution, providing early trend signals before price confirmation.
**4. Value Area Calculation:**
- Starts from POC and expands up/down to encompass 70% of total volume
- VAH (Value Area High): Upper boundary of value area
- VAL (Value Area Low): Lower boundary of value area
- Expansion algorithm prioritizes direction with higher volume
**5. Adaptive Range Selection:**
Based on profile type and timeframe optimization:
- **N Bars Back**: Fixed lookback period with performance optimization (20-500 bars)
- **Days Back**: Calendar-based analysis with automatic timeframe adjustment (1-365 days)
- **Session**: Current trading session or custom session times
### Performance Optimization Features:
- **Sampling Algorithm**: Reduces calculation load on large datasets while maintaining accuracy
- **Memory Management**: Clears previous drawings to prevent performance degradation
- **Safety Constraints**: Prevents excessive memory usage with configurable limits
## HOW TO USE THIS SCRIPT
### Initial Setup:
1. **Profile Configuration**: Select profile type based on trading style:
- N Bars Back: Precise control over data range
- Days Back: Intuitive calendar-based analysis
- Session: Real-time session development
2. **Row Density**: Set number of rows (30 default) - more rows = higher resolution, slower performance
3. **Delta Method**: Choose calculation method based on market type:
- Price Action: Best for trending markets
- Bid/Ask Estimate: Good for ranging markets
- Cumulative: Smoothed approach for volatile markets
4. **Visual Settings**: Configure colors, position (left/right), and display options
### Reading the Profile:
**Volume Bars:**
- **Length**: Represents relative volume at that price level
- **Color**: Green = net buying pressure, Red = net selling pressure
- **Intensity**: Darker colors indicate volume imbalances above threshold
**Key Levels:**
- **POC (Blue Line)**: Highest volume price - major support/resistance
- **VAH (Purple Dashed)**: Value Area High - upper boundary of fair value
- **VAL (Orange Dashed)**: Value Area Low - lower boundary of fair value
- **Value Area Fill**: Shaded region showing main trading range
**Developing POC Trail:**
- **Blue Dotted Lines**: Show real-time POC evolution throughout the session
- **Migration Patterns**: Upward trail indicates bullish accumulation, downward trail suggests bearish distribution
- **Early Signals**: POC movement often precedes price movement, providing advance warning of institutional activity
- **Institutional Footprints**: Reveals where smart money concentrated volume before final POC establishment
### Trading Applications:
**Support/Resistance Analysis:**
- POC acts as magnetic price level - expect reactions
- VAH/VAL provide intermediate support/resistance levels
- Profile edges show areas of low volume acceptance
**Developing POC Analysis:**
- **Upward Migration**: POC moving higher = institutional accumulation, bullish bias
- **Downward Migration**: POC moving lower = institutional distribution, bearish bias
- **Stable POC**: Tight clustering = balanced market, range-bound conditions
- **Early Trend Detection**: POC direction change often precedes price breakouts
**Entry Strategies:**
- Buy at VAL with POC as target (in uptrends)
- Sell at VAH with POC as target (in downtrends)
- Breakout plays above/below profile extremes
**Volume Imbalance Trading:**
- Strong buying imbalance (>60% threshold) suggests continued upward pressure
- Strong selling imbalance suggests continued downward pressure
- Imbalances near key levels provide high-probability setups
**Multi-Timeframe Context:**
- Use higher timeframe profiles for major levels
- Lower timeframe profiles for precise entries
- Session profiles for intraday trading structure
## SCRIPT SETTINGS EXPLANATION
### Volume Profile Settings:
- **Profile Type**: Determines data range for calculation
- N Bars Back: Exact number of bars (20-500 range)
- Days Back: Calendar days with timeframe adaptation (1-365 days)
- Session: Trading session-based (intraday focus)
- **Number of Rows**: Profile resolution (10-50 range)
- **Profile Width**: Visual width as chart percentage (10-50%)
- **Value Area %**: Volume percentage for VA calculation (50-90%, 70% standard)
- **Auto-Adjust**: Automatically optimizes for different timeframes
### Delta Volume Settings:
- **Show Delta Volume**: Enable/disable delta calculations
- **Delta Calculation Method**: Choose methodology based on market conditions
- **Highlight Imbalances**: Visual emphasis for significant volume imbalances
- **Imbalance Threshold**: Percentage for imbalance detection (50-90%)
### Session Settings:
- **Session Type**: Daily, Weekly, Monthly, or Custom periods
- **Custom Session Time**: Define specific trading hours
- **Previous Sessions**: Number of historical sessions to display
### Days Back Settings:
- **Lookback Days**: Number of calendar days to analyze (1-365)
- **Automatic Calculation**: Script automatically converts days to bars based on timeframe:
- Intraday: Accounts for 6.5 trading hours per day
- Daily: 1 bar per day
- Weekly/Monthly: Proportional adjustment
### N Bars Back Settings:
- **Lookback Bars**: Exact number of bars to analyze (20-500)
- **Precise Control**: Best for systematic analysis and backtesting
### Visual Customization:
- **Colors**: Bullish (green), Bearish (red), and level colors
- **Profile Position**: Left or Right side of chart
- **Profile Offset**: Distance from current price action
- **Labels**: Show/hide level labels and values
- **Smooth Profile Bars**: Enhanced visual appearance
### Alert Configuration:
- **POC Touch**: Alerts when price interacts with Point of Control
- **VA Entry/Exit**: Alerts for Value Area boundary interactions
- **Major Imbalance**: Alerts for significant volume imbalances
## VISUAL FEATURES
### Profile Display:
- **Horizontal Bars**: Volume distribution across price levels
- **Color Coding**: Delta-based coloring for directional bias
- **Smooth Rendering**: Optional smoothing for cleaner appearance
- **Transparency**: Configurable opacity for chart readability
### Level Lines:
- **POC**: Solid blue line with optional label
- **VAH/VAL**: Dashed colored lines with value displays
- **Extension**: Lines extend across relevant time periods
- **Value Area Fill**: Optional shaded region between VAH/VAL
### Information Table:
- **Current Values**: Real-time POC, VAH, VAL prices
- **VA Range**: Value Area width calculation
- **Positioning**: Multiple table positions available
- **Text Sizing**: Adjustable for different screen sizes
## IMPORTANT USAGE NOTES
**Realistic Expectations:**
- Volume profile analysis provides structural context, not trading signals
- Delta calculations are estimations based on price action, not actual order flow
- Past volume distribution does not guarantee future price behavior
- Combine with other analysis methods for comprehensive market view
**Best Practices:**
- Use appropriate profile types for your trading style:
- Day Trading: Session or Days Back (1-5 days)
- Swing Trading: Days Back (10-30 days) or N Bars Back
- Position Trading: Days Back (60-180 days)
- Consider market context (trending vs ranging conditions)
- Verify key levels with additional technical analysis
- Monitor profile development for changing market structure
**Performance Considerations:**
- Higher row counts increase calculation complexity
- Large lookback periods may affect chart performance
- Auto-adjust feature optimizes for most use cases
- Consider using session profiles for intraday efficiency
**Limitations:**
- Delta calculations are estimations, not actual transaction data
- Profile accuracy depends on available price/volume history
- Effectiveness varies across different instruments and market conditions
- Requires understanding of volume profile concepts for optimal use
**Data Requirements:**
- Requires volume data for accurate calculations
- Works best on liquid instruments with consistent volume
- May be less effective on very low volume or exotic instruments
This script serves as a comprehensive volume analysis tool for traders who need detailed market structure information with integrated directional bias analysis and real-time POC development tracking for informed trading decisions.
Dual Volume Profiles: Session + Rolling (Range Delineation)Dual Volume Profiles: Session + Rolling (Range Delineation)
INTRO
This is a probability-centric take on volume profile. I treat the volume histogram as an empirical PDF over price, updated in real time, which makes multi-modality (multiple acceptance basins) explicit rather than assumed away. The immediate benefit is operational: if we can read the shape of the distribution, we can infer likely reversion levels (POC), acceptance boundaries (VAH/VAL), and low-friction corridors (LVNs).
My working hypothesis is that what traders often label “fat tails” or “power-law behavior” at short horizons is frequently a tail-conditioned view of a higher-level Gaussian regime. In other words, child distributions (shorter periodicities) sit within parent distributions (longer periodicities); when price operates in the parent’s tail, the child regime looks heavy-tailed without being fundamentally non-Gaussian. This is consistent with a hierarchical/mixture view and with the spirit of the central limit theorem—Gaussian structure emerges at aggregate scales, while local scales can look non-Gaussian due to nesting and conditioning.
This indicator operationalizes that view by plotting two nested empirical PDFs: a rolling (local) profile and a session-anchored profile. Their confluence makes ranges explicit and turns “regime” into something you can see. For additional nesting, run multiple instances with different lookbacks. When using the default settings combined with a separate daily VP, you effectively get three nested distributions (local → session → daily) on the chart.
This indicator plots two nested distributions side-by-side:
Rolling (Local) Profile — short-window, prorated histogram that “breathes” with price and maps the immediate auction.
Session Anchored Profile — cumulative distribution since the current session start (Premkt → RTH → AH anchoring), revealing the parent regime.
Use their confluence to identify range floors/ceilings, mean-reversion magnets, and low-volume “air pockets” for fast traverses.
What it shows
POC (dashed): central tendency / “magnet” (highest-volume bin).
VAH & VAL (solid): acceptance boundaries enclosing an exact Value Area % around each profile’s POC.
Volume histograms:
Rolling can auto-color by buy/sell dominance over the lookback (green = buying ≥ selling, red = selling > buying).
Session uses a fixed style (blue by default).
Session anchoring (exchange timezone):
Premarket → anchors at 00:00 (midnight).
RTH → anchors at 09:30.
After-hours → anchors at 16:00.
Session display span:
Session Max Span (bars) = 0 → draw from session start → now (anchored).
> 0 → draw a rolling window N bars back → now, while still measuring all volume since session start.
Why it’s useful
Think in terms of nested probability distributions: the rolling node is your local Gaussian; the session node is its parent.
VA↔VA overlap ≈ strong range boundary.
POC↔POC alignment ≈ reliable mean-reversion target.
LVNs (gaps) ≈ low-friction corridors—expect quick moves to the next node.
Quick start
Add to chart (great on 5–10s, 15–60s, 1–5m).
Start with: bins = 240, vaPct = 0.68, barsBack = 60.
Watch for:
First test & rejection at overlapping VALs/VAHs → fade back toward POC.
Acceptance beyond VA (several closes + growing outer-bin mass) → traverse to the next node.
Inputs (detailed)
General
Lookback Bars (Rolling)
Count of most-recent bars for the rolling/local histogram. Larger = smoother node that shifts slower; smaller = more reactive, “breathing” profile.
• Typical: 40–80 on 5–10s charts; 60–120 on 1–5m.
• If you increase this but keep Number of Bins fixed, each bin aggregates more volume (coarser bins).
Number of Bins
Vertical resolution (price buckets) for both rolling and session histograms. Higher = finer detail and crisper LVNs, but more line objects (closer to platform limits).
• Typical: 120–240 on 5–10s; 80–160 on 1–5m.
• If you hit performance or object limits, reduce this first.
Value Area %
Exact central coverage for VAH/VAL around POC. Computed empirically from the histogram (no Gaussian assumption): the algorithm expands from POC outward until the chosen % is enclosed.
• Common: 0.68 (≈“1σ-like”), 0.70 for slightly wider core.
• Smaller = tighter VA (more breakout flags). Larger = wider VA (more reversion bias).
Max Local Profile Width (px)
Horizontal length (in pixels) of the rolling bars/lines and its VA/POC overlays. Visual only (does not affect calculations).
Session Settings
RTH Start/End (exchange tz)
Defines the current session anchor (Premkt=00:00, RTH=your start, AH=your end). The session histogram always measures from the most recent session start and resets at each boundary.
Session Max Span (bars, 0 = full session)
Display window for session drawings (POC/VA/Histogram).
• 0 → draw from session start → now (anchored).
• > 0 → draw N bars back → now (rolling look), while still measuring all volume since session start.
This keeps the “parent” distribution measurable while letting the display track current action.
Local (Rolling) — Visibility
Show Local Profile Bars / POC / VAH & VAL
Toggle each overlay independently. If you approach object limits, disable bars first (POC/VA lines are lighter).
Local (Rolling) — Colors & Widths
Color by Buy/Sell Dominance
Fast uptick/downtick proxy over the rolling window (close vs open):
• Buying ≥ Selling → Bullish Color (default lime).
• Selling > Buying → Bearish Color (default red).
This color drives local bars, local POC, and local VA lines.
• Disable to use fixed Bars Color / POC Color / VA Lines Color.
Bars Transparency (0–100) — alpha for the local histogram (higher = lighter).
Bars Line Width (thickness) — draw thin-line profiles or chunky blocks.
POC Line Width / VA Lines Width — overlay thickness. POC is dashed, VAH/VAL solid by design.
Session — Visibility
Show Session Profile Bars / POC / VAH & VAL
Independent toggles for the session layer.
Session — Colors & Widths
Bars/POC/VA Colors & Line Widths
Fixed palette by design (default blue). These do not change with buy/sell dominance.
• Use transparency and width to make the parent profile prominent or subtle.
• Prefer minimal? Hide session bars; keep only session VA/POC.
Reading the signals (detailed playbook)
Core definitions
POC — highest-volume bin (fair price “magnet”).
VAH/VAL — upper/lower bounds enclosing your Value Area % around POC.
Node — contiguous block of high-volume bins (acceptance).
LVN — low-volume gap between nodes (low friction path).
Rejection vs Acceptance (practical rule)
Rejection at VA edge: 0–1 closes beyond VA and no persistent growth in outer bins.
Acceptance beyond VA: ≥3 closes beyond VA and outer-bin mass grows (e.g., added volume beyond the VA edge ≥ 5–10% of node volume over the last N bars). Treat acceptance as regime change.
Confluence scores (make boundary/target quality objective)
VA overlap strength (range boundary):
C_VA = 1 − |VA_edge_local − VA_edge_session| / ATR(n)
Values near 1.0 = tight overlap (stronger boundary).
Use: if C_VA ≥ 0.6–0.8, treat as high-quality fade zone.
POC alignment (magnet quality):
C_POC = 1 − |POC_local − POC_session| / ATR(n)
Higher C_POC = greater chance a rotation completes to that fair price.
(You can estimate these by eye.)
Setups
1) Range Fade at VA Confluence (mean reversion)
Context: Local VAL/VAH near Session VAL/VAH (tight overlap), clear node, local color not screaming trend (or flips to your side).
Entry: First test & rejection at the overlapped band (wick through ok; prefer close back inside).
Stop: A tick/pip beyond the wider of the two VA edges or beyond the nearest LVN, a small buffer zone can be used to judge whether price is truly rejecting a VAL/VAH or simply probing.
Targets: T1 node mid; T2 POC (size up when C_POC is high).
Flip: If acceptance (rule above) prints, flip bias or stand down.
2) LVN Traverse (continuation)
Context: Price exits VA and enters an LVN with acceptance and growing outer-bin volume.
Entry: Aggressive—first close into LVN; Conservative—retest of the VA edge from the far side (“kiss goodbye”).
Stop: Back inside the prior VA.
Targets: Next node’s VA edge or POC (edge = faster exits; POC = fuller rotations).
Note: Flatter VA edge (shallower curvature) tends to breach more easily.
3) POC→POC Magnet Trade (rotation completion)
Context: Local POC ≈ Session POC (high C_POC).
Entry: Fade a VA touch or pullback inside node, aiming toward the shared POC.
Stop: Past the opposite VA edge or LVN beyond.
Target: The shared POC; optional runner to opposite VA if the node is broad and time-of-day is supportive.
4) Failed Break (Reversion Snap-back)
Context: Push beyond VA fails acceptance (re-enters VA, outer-bin growth stalls/shrinks).
Entry: On the re-entry close, back toward POC.
Stop/Target: Stop just beyond the failed VA; target POC, then opposite VA if momentum persists.
How to read color & shape
Local color = most recent sentiment:
Green = buying ≥ selling; Red = selling > buying (over the rolling window). Treat as context, not a standalone signal. A green local node under a blue session VAH can still be a fade if the parent says “over-valued.”
Shape tells friction:
Fat nodes → rotation-friendly (fade edges).
Sharp LVN gaps → traversal-friendly (momentum continuation).
Time-of-day intuition
Right after session anchor (e.g., RTH 09:30): Session profile is young and moves quickly—treat confluence cautiously.
Mid-session: Cleanest behavior for rotations.
Close / news: Expect more traverses and POC migrations; tighten risk or switch playbooks.
Risk & execution guidance
Use tight, mechanical stops at/just beyond VA or LVN. If you need wide stops to survive noise, your entry is late or the node is unstable.
On micro-timeframes, account for fees & slippage—aim for targets paying ≥2–3× average cost.
If acceptance prints, don’t fight it—flip, reduce size, or stand aside.
Suggested presets
Scalp (5–10s): bins 120–240, barsBack 40–80, vaPct 0.68–0.70, local bars thin (small bar width).
Intraday (1–5m): bins 80–160, barsBack 60–120, vaPct 0.68–0.75, session bars more visible for parent context.
Performance & limits
Reuses line objects to stay under TradingView’s max_lines_count.
Very large bins × multiple overlays can still hit limits—use visibility toggles (hide bars first).
Session drawings use time-based coordinates to avoid “bar index too far” errors.
Known nuances
Rolling buy/sell dominance uses a simple uptick/downtick proxy (close vs open). It’s fast and practical, but it’s not a full tape classifier.
VA boundaries are computed from the empirical histogram—no Gaussian assumption.
This script does not calculate the full daily volume profile. Several other tools already provide that, including TradingView’s built-in Volume Profile indicators. Instead, this indicator focuses on pairing a rolling, short-term volume distribution with a session-wide distribution to make ranges more explicit. It is designed to supplement your use of standard or periodic volume profiles, not replace them. Think of it as a magnifying lens that helps you see where local structure aligns with the broader session.
How to trade it (TL;DR)
Fade overlapping VA bands on first rejection → target POC.
Continue through LVN on acceptance beyond VA → target next node’s VA/POC.
Respect acceptance: ≥3 closes beyond VA + growing outer-bin volume = regime change.
FAQ
Q: Why 68% Value Area?
A: It mirrors the “~1σ” idea, but we compute it exactly from empirical volume, not by assuming a normal distribution.
Q: Why are my profiles thin lines?
A: Increase Bars Line Width for chunkier blocks; reduce for fine, thin-line profiles.
Q: Session bars don’t reach session start—why?
A: Set Session Max Span (bars) = 0 for full anchoring; any positive value draws a rolling window while still measuring from session start.
Changelog (v1.0)
Dual profiles: Rolling + Session with independent POC/VA lines.
Session anchoring (Premkt/RTH/AH) with optional rolling display span.
Dynamic coloring for the rolling profile (buying vs selling).
Fully modular toggles + per-feature colors/widths.
Thin-line rendering via bar line width.
