Adv EMA Cloud v6 (ADX, Alerts)Summary:
This indicator provides a multi-faceted view of market trends using Exponential Moving Averages (EMAs) arranged in visually intuitive clouds, enhanced with an optional ADX-based range filter and configurable alerts for key market conditions. It aims to help traders quickly gauge trend alignment across short, medium, and long timeframes while filtering signals during potentially choppy market conditions.
Key Features:
Multiple EMAs: Displays 10-period (Fast), 20-period (Mid), and 50-period (Slow) EMAs.
Long-Term Trend Filter: Includes a 200-period EMA to provide context for the overall dominant trend direction.
Dual EMA Clouds:
Fast/Mid Cloud (10/20 EMA): Fills the area between the 10 and 20 EMAs. Defaults to Green when 10 > 20 (bullish short-term momentum) and Red when 10 < 20 (bearish short-term momentum).
Mid/Slow Cloud (20/50 EMA): Fills the area between the 20 and 50 EMAs. Defaults to Aqua when 20 > 50 (bullish mid-term trend) and Fuchsia when 20 < 50 (bearish mid-term trend).
Optional ADX Range Filter: Uses the Average Directional Index (ADX) to identify potentially non-trending or choppy markets. When enabled and ADX falls below a user-defined threshold, the EMA clouds will turn grey, visually warning that trend-following signals may be less reliable.
Configurable Alerts: Provides several built-in alert conditions using Pine Script's alertcondition function:
Confluence Condition: Triggers when a 10/20 EMA crossover occurs while both EMA clouds show alignment (both bullish/green/aqua or both bearish/red/fuchsia) and price respects the 200 EMA filter and the ADX filter indicates a trend (if filters are enabled).
MA Filter Cross: Triggers when price crosses above or below the 200 EMA filter line.
Full Alignment Start: Triggers on the first bar where full bullish or bearish alignment occurs (both clouds aligned + MA filter respected + ADX trending, if filters are enabled).
How It Works:
EMA Calculation: Standard Exponential Moving Averages are calculated for the 10, 20, 50, and 200 periods based on the closing price.
Cloud Creation: The fill() function visually shades the area between the 10 & 20 EMAs and the 20 & 50 EMAs.
Cloud Coloring: The color of each cloud is determined by the relationship between the two EMAs that define it (e.g., if EMA 10 is above EMA 20, the first cloud is bullish-colored).
ADX Filter Logic: The script calculates the ADX value. If the "Use ADX Trend Filter?" input is checked and the calculated ADX is below the specified "ADX Trend Threshold", the script considers the market potentially ranging.
ADX Visual Effect: During detected ranging periods (if the ADX filter is active), the plotCloud12Color and plotCloud23Color variables are assigned a neutral grey color instead of their normal bullish/bearish colors before being passed to the fill() function.
Alert Logic: Boolean variables track the specific conditions (crossovers, cloud alignment, filter positions, ADX state). The alertcondition() function creates triggerable alerts based on these pre-defined conditions.
Potential Interpretation (Not Financial Advice):
Trend Alignment: When both clouds share the same directional color (e.g., both bullish - Green & Aqua) and price is on the corresponding side of the 200 EMA filter, it may suggest a stronger, more aligned trend. Conversely, conflicting cloud colors may indicate indecision or transition.
Dynamic Support/Resistance: The EMA lines themselves (especially the 20, 50, and 200) can sometimes act as dynamic levels where price might react.
Range Warning: Greyed-out clouds (when ADX filter is enabled) serve as a visual warning that trend-based strategies might face increased difficulty or whipsaws.
Confluence Alerts: The specific confluence alerts signal moments where multiple conditions align (crossover + cloud agreement + filters), which some traders might view as higher-probability setups.
Customization:
All EMA lengths (10, 20, 50, 200) are adjustable via the Inputs menu.
The ADX length and threshold are configurable.
The MA Trend Filter and ADX Trend Filter can be independently enabled or disabled.
Disclaimer:
This indicator is provided for informational and educational purposes only. Trading financial markets involves significant risk. Past performance is not indicative of future results. Always conduct your own thorough analysis and consider your risk tolerance before making any trading decisions. This indicator should be used in conjunction with other analysis methods and tools. Do not trade based solely on the signals or visuals provided by this indicator.
Indicatori e strategie
Custom EMAs, SMA y VWAP con Puntos en CrucesHighly configurable moving average indicator for each person's trading strategy.
PunkAlgo Oscillator [1.0]//@version=5
indicator(title='PunkAlgo Oscillator ', shorttitle='Punk Oscillator')
n1 = input(4, 'Channel Length')
n2 = input(15, 'Average Length')
obLevel1 = input(88, 'Over Bought Level 1')
obLevel2 = input(81, 'Over Bought Level 2')
osLevel1 = input(-83, 'Over Sold Level 1')
osLevel2 = input(-76, 'Over Sold Level 2')
ap = hlc3
esa = ta.ema(ap, n1)
d = ta.ema(math.abs(ap - esa), n1)
ci = (ap - esa) / (0.015 * d)
tci = ta.ema(ci, n2)
wt1 = tci
wt2 = ta.sma(wt1, 4)
var indbot=0
var indtop=0
if wt1 > wt2 and wt1 < wt2
indbot := bar_index
if wt1 < wt2 and wt1 > wt2
indtop := bar_index
bott = bar_index - indbot
topp = bar_index - indtop
// Histogram
lookbackPeriod = input(35, "Lookback Period")
// Calculate the percentage change in price for each bar
priceChange = close - close
priceChangePercentage = priceChange / close * 100
// Calculate the average volume over the lookback period
averageVolume = ta.ema(volume, lookbackPeriod)
// Initialize the counters for upward and downward trends
upwardTrends = 0
downwardTrends = 0
// Iterate over the lookback period and count the number of upward and downward trends
for i = 1 to lookbackPeriod
if priceChangePercentage > 0
upwardTrends := upwardTrends + 1
else if priceChangePercentage < 0
downwardTrends := downwardTrends + 1
// Calculate the probabilities of upward, downward, and neutral trends
totalTrends = upwardTrends + downwardTrends
probabilityUpward = math.round(upwardTrends / totalTrends, 2) * 100
probabilityDownward = math.round(downwardTrends / totalTrends, 2) * 100
// Determine the probability trend based on the probabilities
probabilityTrend = ""
if probabilityUpward > probabilityDownward
probabilityTrend := "Upward"
else if probabilityUpward < probabilityDownward
probabilityTrend := "Downward"
// Calculate the oscillator value based on the difference between upward and downward trends
oscillatorValue = probabilityUpward - probabilityDownward
// Determine the histogram color based on the difference between the oscillator value and zero line
histogramColor = oscillatorValue >= 0 ? (oscillatorValue < oscillatorValue ? color.new(#089981, 50) : color.new(#089981, 50)) : (oscillatorValue < oscillatorValue ? color.new(#f23645, 50) : color.new(#f23645, 50))
// Smoothning the Histogram
smooth_hist = input.bool(true, "Smoothen Histogram", inline="smooth_hist")
smoothning_scale = input.int(defval=3, title="", minval=1, maxval=10, step=1, inline="smooth_hist")
smooth_len = smoothning_scale * 2
smooth_hist_val = smooth_hist ? ta.ema(oscillatorValue, smooth_len) : oscillatorValue
// Plot the histogram
plot(smooth_hist_val, color=histogramColor, style=plot.style_area, linewidth=1, title="Probability Histogram")
// Histogram
plot(0, color=color.new(#787b86, 100))
top1 = plot(obLevel1, color=color.new(#4caf4f, 100))
top2 = plot(osLevel1, color=color.new(#ff5252, 100))
bottom1 = plot(obLevel2, color=color.new(#4caf4f, 100))
bottom2 = plot(osLevel2, color=color.new(#ff5252, 100))
fill(plot1=top1, plot2=bottom1, color=wt2 > 0 and (wt1 - wt2) > 0 ? #089981 : wt2 > 0 or (wt1 - wt2) > 0 ?color.new(#363a45, 60) : color.new(#363a45, 70))
fill(plot1=top2, plot2=bottom2, color=wt2 < 0 and (wt1 - wt2) < 0 ? #f23645 : wt2 < 0 or (wt1 - wt2) < 0 ? color.new(#363a45, 60) : color.new(#363a45, 70))
plot1 = plot(wt1, color=wt1 > wt2 ? color.new(color.green, 0) : color.gray ,title="Signal")
plot2 = plot(wt2, color=color.new(#ff5252, 100),title="Signal Dots")
fill(plot1=plot1, plot2=plot2, color=wt1 > wt2 ? color.rgb(8, 153, 129, 80) : color.rgb(120, 123, 134, 80),title="Signal Shadow")
plot(ta.cross(wt1, wt2) ? wt2 : na, color=color.new(color.black, 0), style=plot.style_circles, linewidth=3,title="Dot Shadows")
plot(ta.cross(wt1, wt2) ? wt2 : na, color=wt2 - wt1 > 0 ? color.gray : color.green , style=plot.style_circles, linewidth=2)
// Divergences Module
tsi1 = wt1
tsi2 = ta.sma(wt2, 4)
long = n1
short = n2
signal22 = n2
price = hlc3
src2 = hlc3
src = hlc3
input_src = tsi1
// Divergences Options
up = ta.rma(math.max(ta.change(src), 0), short)
down = ta.rma(-math.min(ta.change(src), 0), short)
lbR = input(title='Divergence Pivot Lookback Right', defval=1)
lbL = input(title='Divergence Pivot Lookback Left', defval=5)
rangeUpper = input(title='Max of Lookback Range', defval=100)
rangeLower = input(title='Min of Lookback Range', defval=2)
plotBull = input(title='Plot Bullish', defval=true)
plotHiddenBull = input(title='Plot Hidden Bullish', defval=false)
plotBear = input(title='Plot Bearish', defval=true)
plotHiddenBear = input(title='Plot Hidden Bearish', defval=false)
bearColor = color.new(#f23645, 10)
bullColor = color.new(#2157f3, 10)
hiddenBullColor = color.new(color.aqua, 0)
hiddenBearColor = color.new(color.orange, 0)
textColor = color.new(color.white, 0)
noneColor = color.new(color.white, 100)
osc = tsi1
plFound = na(ta.pivotlow(osc, lbL, lbR)) ? false : true
phFound = na(ta.pivothigh(osc, lbL, lbR)) ? false : true
_inRange(cond) =>
bars = ta.barssince(cond == true)
rangeLower <= bars and bars <= rangeUpper
//------------------------------------------------------------------------------
// Regular Bullish
// Osc: Higher Low
oscHL = osc > ta.valuewhen(plFound, osc , 1) and _inRange(plFound )
// Price: Lower Low
priceLL = low < ta.valuewhen(plFound, low , 1)
bullCond = plotBull and priceLL and oscHL and plFound
plot(plFound ? osc : na, offset=-lbR, title='Regular Bullish', linewidth=1, color=bullCond ? bullColor : noneColor, transp=0)
//------------------------------------------------------------------------------
// Hidden Bullish
// Osc: Lower Low
oscLL = osc < ta.valuewhen(plFound, osc , 1) and _inRange(plFound )
// Price: Higher Low
priceHL = low > ta.valuewhen(plFound, low , 1)
hiddenBullCond = plotHiddenBull and priceHL and oscLL and plFound
plot(plFound ? osc : na, offset=-lbR, title='Hidden Bullish', linewidth=1, color=hiddenBullCond ? hiddenBullColor : noneColor, transp=0)
//------------------------------------------------------------------------------
// Regular Bearish
// Osc: Lower High
oscLH = osc < ta.valuewhen(phFound, osc , 1) and _inRange(phFound )
// Price: Higher High
priceHH = high > ta.valuewhen(phFound, high , 1)
bearCond = plotBear and priceHH and oscLH and phFound
plot(phFound ? osc : na, offset=-lbR, title='Regular Bearish', linewidth=1, color=bearCond ? bearColor : noneColor, transp=0)
//------------------------------------------------------------------------------
// Hidden Bearish
// Osc: Higher High
oscHH = osc > ta.valuewhen(phFound, osc , 1) and _inRange(phFound )
// Price: Lower High
priceLH = high < ta.valuewhen(phFound, high , 1)
hiddenBearCond = plotHiddenBear and priceLH and oscHH and phFound
plot(phFound ? osc : na, offset=-lbR, title='Hidden Bearish', linewidth=1, color=hiddenBearCond ? hiddenBearColor : noneColor, transp=0)
// Signals Module
string TT_HARSI = 'Period for the RSI calculations used to generate the' + 'candles. This seperate from the RSI plot/histogram length.'
string TT_PBIAS = 'Smoothing feature for the OPEN of the HARSI candles.' + ' Increases bias toward the prior open value which can' + ' help provide better visualisation of trend strength.' + ' ** By changing the Open values, High and Low can also' + ' be distorted - however Close will remain unchanged.'
string TT_SMRSI = 'This option smoothes the RSI in a manner similar to HA' + ' open, but uses the realtime rsi rather than the prior' + ' close value.'
string TT_STOCH = 'Uses the RSI generated by the above settings, and as such' + ' will be affected by the smoothing option.'
string TT_STFIT = 'Adjusts the vertical scaling of the stochastic, can help' + ' to prevent distortion of other data in the channel.' + ' Has no impact cross conditions.'
////////////////////////////////////////////////////////////////////////////////
// //
// ====== INPUTS ====== //
// //
////////////////////////////////////////////////////////////////////////////////
// -- Candle config
string GROUP_CAND = 'Config » HARSI Candles'
i_lenHARSI = input.int(10, 'Length', group=GROUP_CAND, minval=1, tooltip=TT_HARSI)
i_smoothing = input.int(5, 'Open Smoothing', group=GROUP_CAND, minval=1, maxval=100, tooltip=TT_PBIAS)
string INLINE_COL = 'Colour Pallette'
i_colUp = input.color(color.teal, 'Colour Pallette ', group=GROUP_CAND, inline=INLINE_COL)
i_colDown = input.color(color.red, ' ', group=GROUP_CAND, inline=INLINE_COL)
i_colWick = input.color(color.gray, ' ', group=GROUP_CAND, inline=INLINE_COL)
// -- RSI plot config
string GROUP_PLOT = 'Config » RSI Plot'
i_source = input.source(ohlc4, 'Source', group=GROUP_PLOT)
i_lenRSI = input.int(7, 'Length', group=GROUP_PLOT, minval=1)
i_mode = input.bool(true, 'Smoothed Mode RSI?', group=GROUP_PLOT, tooltip=TT_SMRSI)
i_showPlot = input.bool(true, 'Show RSI Plot?', group=GROUP_PLOT)
i_showHist = input.bool(true, 'Show RSI Histogram?', group=GROUP_PLOT)
// -- Channel OB/OS config
string GROUP_CHAN = 'Config » OB/OS Boundaries'
i_upper = input.int(50, 'OB', group=GROUP_CHAN, inline='OB', minval=1, maxval=50)
i_upperx = input.int(30, 'OB Extreme', group=GROUP_CHAN, inline='OB', minval=1, maxval=50)
i_lower = input.int(-50, 'OS', group=GROUP_CHAN, inline='OS', minval=-50, maxval=-1)
i_lowerx = input.int(-30, 'OS Extreme', group=GROUP_CHAN, inline='OS', minval=-50, maxval=-1)
// Settins
// WaveTrend
wwttShow = input(false, title='Show WaveTrend')
wwttBuyShow = input(true, title='Show Buy dots')
wwttGoldShow = input(true, title='Show Gold dots')
wwttSellShow = input(true, title='Show Sell dots')
wwttDivShow = input(true, title='Show Div. dots')
vwapShow = input(true, title='Show Fast wwtt')
wwttChannelLen = input(9, title='wwtt Channel Length')
wwttAverageLen = input(12, title='wwtt Average Length')
wwttMASource = input(hlc3, title='wwtt MA Source')
wwttMALen = input(3, title='wwtt MA Length')
// WaveTrend Overbought & Oversold lines
OOBBLevel = input(53, title='wwtt Overbought Level 1')
OOBBLevel2 = input(60, title='wwtt Overbought Level 2')
OOBBLevel3 = input(100, title='wwtt Overbought Level 3')
oosLevel = input(-53, title='wwtt Oversold Level 1')
oosLevel2 = input(-60, title='wwtt Oversold Level 2')
oosLevel3 = input(-75, title='wwtt Oversold Level 3')
// Divergence wwtt
wwttShowDiv = input(true, title='Show wwtt Regular Divergences')
wwttShowHiddenDiv = input(false, title='Show wwtt Hidden Divergences')
showHiddenDiv_nl = input(true, title='Not apply OB/OS Limits on Hidden Divergences')
wwttDivOOBBLevel = input(45, title='wwtt Bearish Divergence min')
wwttDivoosLevel = input(-65, title='wwtt Bullish Divergence min')
// Divergence extra range
wwttDivOOBBLevel_addshow = input(true, title='Show 2nd wwtt Regular Divergences')
wwttDivOOBBLevel_add = input(15, title='wwtt 2nd Bearish Divergence')
wwttDivoosLevel_add = input(-40, title='wwtt 2nd Bullish Divergence 15 min')
// RSI+MFI
rsiMFIShow = input(true, title='Show MFI')
rsiMFIperiod = input(60, title='MFI Period')
rsiMFIMultiplier = input.float(150, title='MFI Area multiplier')
rsiMFIPosY = input(2.5, title='MFI Area Y Pos')
// RSI
rsiShow = input(false, title='Show RSI')
rsiSRC = input(close, title='RSI Source')
rsiLen = input(14, title='RSI Length')
rsiOversold = input.int(30, title='RSI Oversold', minval=29, maxval=100)
rsiOverbought = input.int(60, title='RSI Overbought', minval=0, maxval=60)
// Divergence RSI
rsiShowDiv = input(false, title='Show RSI Regular Divergences')
rsiShowHiddenDiv = input(false, title='Show RSI Hidden Divergences')
rsiDivOOBBLevel = input(60, title='RSI Bearish Divergence min')
rsiDivoosLevel = input(30, title='RSI Bullish Divergence min')
// Colors
colorRed = #ff0000
colorPurple = #e600e6
colorGreen = #3fff00
colorOrange = #e2a400
colorYellow = #ffe500
colorWhite = #ffffff
colorPink = #ff00f0
colorBluelight = #31c0ff
colorwwtt1 = #49536195
colorwwtt2 = #7b9fd596
colorwwtt2_ = #131722
colormacdwwtt1a = #4caf58
colormacdwwtt1b = #af4c4c
colormacdwwtt1c = #7ee57e
colormacdwwtt1d = #ff3535
colormacdwwtt2a = #305630
colormacdwwtt2b = #310101
colormacdwwtt2c = #132213
colormacdwwtt2d = #770000
////////////////////////////////////////////////////////////////////////////////
// //
// ====== FUNCTIONS ====== //
// //
////////////////////////////////////////////////////////////////////////////////
// FUNCTIONS
// zero median rsi helper function, just subtracts 50.
f_zrsi(_source, _length) =>
ta.rsi(_source, _length) - 50
// zero median stoch helper function, subtracts 50 and includes % scaling
f_zstoch(_source, _length, _smooth, _scale) =>
float _zstoch = ta.stoch(_source, _source, _source, _length) - 50
float _smoothed = ta.sma(_zstoch, _smooth)
float _scaled = _smoothed / 100 * _scale
_scaled
// mode selectable rsi function for standard, or smoothed output
f_rsi(_source, _length, _mode) =>
// get base rsi
float _zrsi = f_zrsi(_source, _length)
// smoothing in a manner similar to HA open, but rather using the realtime
// rsi in place of the prior close value.
var float _smoothed = na
_smoothed := na(_smoothed ) ? _zrsi : (_smoothed + _zrsi) / 2
// return the requested mode
_mode ? _smoothed : _zrsi
// RSI Heikin-Ashi generation function
f_rsiHeikinAshi(_length) =>
// get close rsi
float _closeRSI = f_zrsi(close, _length)
// emulate "open" simply by taking the previous close rsi value
float _openRSI = nz(_closeRSI , _closeRSI)
// the high and low are tricky, because unlike "high" and "low" by
// themselves, the RSI results can overlap each other. So first we just go
// ahead and get the raw results for high and low, and then..
float _highRSI_raw = f_zrsi(high, _length)
float _lowRSI_raw = f_zrsi(low, _length)
// ..make sure we use the highest for high, and lowest for low
float _highRSI = math.max(_highRSI_raw, _lowRSI_raw)
float _lowRSI = math.min(_highRSI_raw, _lowRSI_raw)
// ha calculation for close
float _close = (_openRSI + _highRSI + _lowRSI + _closeRSI) / 4
// ha calculation for open, standard, and smoothed/lagged
var float _open = na
_open := na(_open ) ? (_openRSI + _closeRSI) / 2 : (_open * i_smoothing + _close ) / (i_smoothing + 1)
// ha high and low min-max selections
float _high = math.max(_highRSI, math.max(_open, _close))
float _low = math.min(_lowRSI, math.min(_open, _close))
// return the OHLC values
// Divergences
f_top_fractal(src) =>
src < src and src < src and src > src and src > src
f_bot_fractal(src) =>
src > src and src > src and src < src and src < src
f_fractalize(src) =>
f_top_fractal(src) ? 1 : f_bot_fractal(src) ? -1 : 0
f_findDivs(src, topLimit, botLimit, useLimits) =>
fractalTop = f_fractalize(src) > 0 and (useLimits ? src >= topLimit : true) ? src : na
fractalBot = f_fractalize(src) < 0 and (useLimits ? src <= botLimit : true) ? src : na
highPrev = ta.valuewhen(fractalTop, src , 0)
highPrice = ta.valuewhen(fractalTop, high , 0)
lowPrev = ta.valuewhen(fractalBot, src , 0)
lowPrice = ta.valuewhen(fractalBot, low , 0)
bearSignal = fractalTop and high > highPrice and src < highPrev
bullSignal = fractalBot and low < lowPrice and src > lowPrev
bearDivHidden = fractalTop and high < highPrice and src > highPrev
bullDivHidden = fractalBot and low > lowPrice and src < lowPrev
// RSI+MFI
f_rsimfi(_period, _multiplier, _tf) =>
request.security(syminfo.tickerid, _tf, ta.sma((close - open) / (high - low) * _multiplier, _period) - rsiMFIPosY)
// WaveTrend
f_wavetrend(src, chlen, avg, malen, tf) =>
tfsrc = request.security(syminfo.tickerid, tf, src)
esa = ta.ema(tfsrc, chlen)
de = ta.ema(math.abs(tfsrc - esa), chlen)
ci = (tfsrc - esa) / (0.015 * de)
wwtt1 = request.security(syminfo.tickerid, tf, ta.ema(ci, avg))
wwtt2 = request.security(syminfo.tickerid, tf, ta.sma(wwtt1, malen))
wwttVwap = wwtt1 - wwtt2
wwttOversold = wwtt2 <= oosLevel
wwttOverbought = wwtt2 >= OOBBLevel
wwttCross = ta.cross(wwtt1, wwtt2)
wwttCrossUp = wwtt2 - wwtt1 <= 0
wwttCrossDown = wwtt2 - wwtt1 >= 0
wwttCrosslast = ta.cross(wwtt1 , wwtt2 )
wwttCrossUplast = wwtt2 - wwtt1 <= 0
wwttCrossDownlast = wwtt2 - wwtt1 >= 0
// MACD
f_macd(src, fastlen, slowlen, sigsmooth, tf) =>
fast_ma = request.security(syminfo.tickerid, tf, ta.ema(src, fastlen))
slow_ma = request.security(syminfo.tickerid, tf, ta.ema(src, slowlen))
macd = fast_ma - slow_ma
signal = request.security(syminfo.tickerid, tf, ta.sma(macd, sigsmooth))
hist = macd - signal
// Get higher timeframe candle
f_getTFCandle(_tf) =>
_open = request.security(ticker.heikinashi(syminfo.tickerid), _tf, open, barmerge.gaps_off, barmerge.lookahead_on)
_close = request.security(ticker.heikinashi(syminfo.tickerid), _tf, close, barmerge.gaps_off, barmerge.lookahead_on)
_high = request.security(ticker.heikinashi(syminfo.tickerid), _tf, high, barmerge.gaps_off, barmerge.lookahead_on)
_low = request.security(ticker.heikinashi(syminfo.tickerid), _tf, low, barmerge.gaps_off, barmerge.lookahead_on)
hl2 = (_high + _low) / 2.0
newBar = ta.change(_open)
candleBodyDir = _close > _open
////////////////////////////////////////////////////////////////////////////////
// //
// ====== SERIES, LINES and LABELS ====== //
// //
////////////////////////////////////////////////////////////////////////////////
// CALCULATE INDICATORS {
// RSI
rsi = ta.rsi(rsiSRC, rsiLen)
rsiColor = rsi <= rsiOversold ? colorGreen : rsi >= rsiOverbought ? colorRed : colorPurple
// Calculates WaveTrend
= f_wavetrend(wwttMASource, wwttChannelLen, wwttAverageLen, wwttMALen, timeframe.period)
// wwtt Divergences
= f_findDivs(wwtt2, wwttDivOOBBLevel, wwttDivoosLevel, true)
= f_findDivs(wwtt2, wwttDivOOBBLevel_add, wwttDivoosLevel_add, true)
= f_findDivs(wwtt2, 0, 0, false)
wwttBearDivHidden_ = showHiddenDiv_nl ? wwttBearDivHidden_nl : wwttBearDivHidden
wwttBullDivHidden_ = showHiddenDiv_nl ? wwttBullDivHidden_nl : wwttBullDivHidden
wwttBearDivColor = wwttShowDiv and wwttBearDiv or wwttShowHiddenDiv and wwttBearDivHidden_ ? colorRed : na
wwttBullDivColor = wwttShowDiv and wwttBullDiv or wwttShowHiddenDiv and wwttBullDivHidden_ ? colorGreen : na
wwttBearDivColor_add = wwttShowDiv and wwttDivOOBBLevel_addshow and wwttBearDiv_add or wwttShowHiddenDiv and wwttDivOOBBLevel_addshow and wwttBearDivHidden_add ? #9a0202 : na
wwttBullDivColor_add = wwttShowDiv and wwttDivOOBBLevel_addshow and wwttBullDiv_add or wwttShowHiddenDiv and wwttDivOOBBLevel_addshow and wwttBullDivHidden_add ? #1b5e20 : na
// RSI Divergences
= f_findDivs(rsi, rsiDivOOBBLevel, rsiDivoosLevel, true)
= f_findDivs(rsi, 0, 0, false)
rsiBearDivHidden_ = showHiddenDiv_nl ? rsiBearDivHidden_nl : rsiBearDivHidden
rsiBullDivHidden_ = showHiddenDiv_nl ? rsiBullDivHidden_nl : rsiBullDivHidden
rsiBearDivColor = rsiShowDiv and rsiBearDiv or rsiShowHiddenDiv and rsiBearDivHidden_ ? colorRed : na
rsiBullDivColor = rsiShowDiv and rsiBullDiv or rsiShowHiddenDiv and rsiBullDivHidden_ ? colorGreen : na
// Buy signal.
buySignal = wwttCross and wwttCrossUp and wwttOversold
buySignalDiv = wwttShowDiv and wwttBullDiv or wwttShowDiv and wwttBullDiv_add or rsiShowDiv and rsiBullDiv
buySignalDiv_color = wwttBullDiv ? colorGreen : wwttBullDiv_add ? color.new(colorGreen, 60) : rsiShowDiv ? colorGreen : na
// Sell signal
sellSignal = wwttCross and wwttCrossDown and wwttOverbought
sellSignalDiv = wwttShowDiv and wwttBearDiv or wwttShowDiv and wwttBearDiv_add or rsiShowDiv and rsiBearDiv
sellSignalDiv_color = wwttBearDiv ? colorRed : wwttBearDiv_add ? color.new(colorRed, 60) : rsiBearDiv ? colorRed : na
// standard, or ha smoothed rsi for the line plot and/or histogram
float RSI = f_rsi(i_source, i_lenRSI, i_mode)
// get OHLC values to use in the plotcandle()
= f_rsiHeikinAshi(i_lenHARSI)
// shadow, invisible
color colShadow = color.rgb(0, 0, 0, 100)
color colNone = color.rgb(0, 0, 0, 100)
// rsi color
//color colRSI = RSI >=30 ? color.red : color.gray
color colRSI = RSI < -31 ? color.lime : RSI > 31 ? color.red : color.gray
cross_up = RSI > 30
cross_down = RSI < -30
// candle body colouring
color bodyColour = C > O ? i_colUp : i_colDown
color wickColour = i_colWick
////////////////////////////////////////////////////////////////////////////////
// //
// ====== DRAWING and PLOTTING ====== //
// //
////////////////////////////////////////////////////////////////////////////////
plotchar(cross_down and wwttBuyShow and buySignal ? -107 : na, title='Buy circle', char='·', color=color.new(colorGreen, 10), location=location.absolute, size=size.small)
plotchar(cross_up and wwttSellShow and sellSignal ? 105 : na, title='Sell circle', char='·', color=color.new(colorRed, 10), location=location.absolute, size=size.small)
plotchar(cross_down and wwttDivShow and buySignalDiv and wwttBuyShow and buySignal ? -106 : na, title='Divergence buy circle', char='▲', color=buySignalDiv_color, location=location.absolute, size=size.tiny, offset=-2, transp=10)
plotchar(cross_up and wwttDivShow and sellSignalDiv and wwttSellShow and sellSignal ? 106 : na, title='Divergence sell circle', char='▼', color=sellSignalDiv_color, location=location.absolute, size=size.tiny, offset=-2, transp=10)
//Alerts
alertcondition((cross_down and wwttBuyShow and buySignal and wwttDivShow and buySignalDiv) or (cross_up and wwttSellShow and sellSignal and wwttDivShow and sellSignalDiv), title='Buy/Sell Signal', message='Buy/Sell Signal')
Price Level Indicator StaticThe Price Level Indicator Static (PLIS) is a versatile tool for traders who need precise price levels for support, resistance, and potential liquidation zones. This indicator calculates multiple price levels based on a user-defined input value, creating a comprehensive map of critical zones above and below the specified price.
The indicator displays a set of horizontal lines representing different percentage deviations from your entry point, helping you visualize potential stop-loss placements, take-profit targets, and liquidation thresholds.
Features:
User-defined base price level input
Multiple percentage deviation levels (x2, x5, x10, x20, x50, x75, x100)
Color-coded lines for easy identification
Different line styles to distinguish between levels
Separate calculations for long and short positions
Median price calculation from the last 1024 candles
Informational panel displaying the current median price
Use Cases:
Set precise stop-loss and take-profit levels
Identify potential liquidation zones for leveraged positions
Create a visual price map for trading decisions
Monitor price action around critical percentage thresholds
Develop structured risk management strategies
This indicator is essential for traders who want to approach the market with predefined levels and a clear understanding of potential price movements relative to their entry points.
Qullamaggie [Modified] | FractalystWhat's the purpose of this strategy?
The strategy aims to identify high-probability breakout setups in trending markets, inspired by Kristjan "Qullamaggie" Kullamägi’s approach.
It focuses on capturing explosive price moves after periods of consolidation, using technical criteria like moving averages, breakouts, trailing stop-loss and momentum confirmation.
Ideal for swing traders seeking to ride strong trends while managing risk.
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How does the strategy work?
The strategy follows a systematic process to capture high-momentum breakouts:
Pre-Breakout Criteria:
Prior Price Surge: Identifies stocks that have rallied 30-100%+ in recent month(s), signaling strong underlying momentum (per Qullamaggie’s volatility expansion principles).
Consolidation Phase: Looks for a tightening price range (e.g., flag, pennant, or tight base), indicating a potential "coiling" before continuation.
Trend Confirmation: Uses moving averages (e.g., 20/50/200 EMA) to ensure the stock is trading above key averages on the daily chart, confirming an uptrend.
Price Break: Enters when price clears the consolidation high with conviction.
Risk Management:
Initial Stop Loss: Placed below the consolidation low or a recent swing point to limit downside.
Break-Even Adjustment: Moves stop loss to breakeven once the trade reaches 1.5x risk-to-reward (RR), securing a "free trade" while letting winners run.
Trailing Stop (Unique Edge):
Market Structure Trailing: Instead of trailing via moving averages, the stop is dynamically adjusted using structural invalidation level. This adapts to price action, allowing the trade to stay open during volatile retracements while locking in gains as new structure forms.
Why This Matters: Most strategies use rigid trailing stops (e.g., below the 10EMA), which often exit prematurely in choppy markets. By trailing based on structure, this strategy avoids "noise" and captures larger trends, directly boosting overall returns.
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What markets or timeframes is this suited for?
This is a long-only strategy designed for trending markets, and it performs best in:
Markets: Stocks (especially high-growth, liquid equities), cryptocurrencies (major pairs with strong volatility), commodities (e.g., oil, gold), and futures (index/commodity futures).
Timeframes: Primarily daily charts for swing trades (1-30 day holds), though weekly charts can help confirm broader trends.
Key Advantage: The TradingView script allows instant backtesting with adjustable parameters
You can:
- Test historical performance across multiple markets to identify which assets align best with the strategy.
- Optimize settings (e.g., trailing stop sensitivity, moving averages etc.) to match a market’s volatility profile.
Build a diversified portfolio by filtering for markets that show consistent profitability in backtests.
For example, you might discover cryptos require tighter trailing stops due to volatility, while stocks thrive with wider structural stops. The script automates this analysis, letting you to trade confidently.
----
What indicators or tools does the strategy use?
The strategy combines customizable technical tools with strict anti-lookahead safeguards:
Core Indicators:
Moving Averages: Adjustable periods (e.g., 20/50/200 EMA or SMA) and timeframes (daily/weekly) to confirm trend alignment. Users can test combinations (e.g., 10EMA vs. 20EMA) to optimize for specific markets.
Breakout Parameters:
Consolidation Length: Adjustable window to define the "tightness" of the pre-breakout pattern.
Entry Models: Flexible entry logics (Breakouts and fractals)
Anti-Lookahead Design:
All calculations (e.g., moving averages, consolidation ranges, volume averages) use only closed/confirmed data available at the time of the signal.
----
How do I manage risk with this strategy?
The strategy prioritizes customizable risk controls to align with your trading style and account size:
User-Defined Risk Inputs:
Risk Per Trade: Set a % of Equity (e.g., 1-2%) to determine position size. The strategy auto-calculates shares/contracts to match your selected risk per trade.
Flexibility: Choose between fixed risk or equity-based scaling.
The script adjusts position sizing dynamically based on your selection.
Pyramiding Feature:
Customizable Entries: Adjust the number of pyramiding trades allowed (e.g., 1-3 additional positions) in the strategy settings. Each new entry is triggered only if the prior trade hits its 1.5x RR target and the trend remains intact.
Risk-Scaled Additions: New positions use profits from prior trades, compounding gains without increasing initial risk.
Risk-Free Trade Mechanic:
Once a trade reaches 1.5x RR, the stop loss is moved to breakeven, eliminating downside risk.
The strategy then opens a new position (if pyramiding is enabled) using a portion of the locked-in profit. This "snowballs" winners while keeping total capital exposure stable.
Impact on Net Profit & Drawdown:
Net Profit Boost: Pyramiding lets you ride multi-leg trends aggressively. For example, a 100% runner could generate 2-3x more profit vs. a single-entry approach.
Controlled Drawdowns: Since new positions are funded by profits (not initial capital), max drawdown stays anchored to your original risk per trade (e.g., 1-2% of account). Even if later entries fail, the breakeven stop on prior trades protects overall equity.
Why This Works: Most strategies either over-leverage (increasing drawdowns) or exit too early. By recycling profits into new positions only after securing risk-free capital, this approach mimics hedge fund "scaling in" tactics while staying retail-trader friendly.
----
How does the strategy identify market structure for its trailing stoploss?
The strategy identifies market structure by utilizing an efficient logic with for loops to pinpoint the first swing candle that features a pivot of 2. This marks the beginning of the break of structure, where the market's previous trend or pattern is considered invalidated or changed.
----
What are the underlying calculations?
The underlying calculations involve:
Identifying Swing Points: The strategy looks for swing highs (marked with blue Xs) and swing lows (marked with red Xs). A swing high is identified when a candle's high is higher than the highs of the candles before and after it. Conversely, a swing low is when a candle's low is lower than the lows of the candles before and after it.
Break of Structure (BOS):
Bullish BOS: This occurs when the price breaks above the swing high level of the previous structure, indicating a potential shift to a bullish trend.
Bearish BOS: This happens when the price breaks below the swing low level of the previous structure, signaling a potential shift to a bearish trend.
Structural Liquidity and Invalidation:
Structural Liquidity: After a break of structure, liquidity levels are updated to the first swing high in a bullish BOS or the first swing low in a bearish BOS.
Structural Invalidation: If the price moves back to the level of the first swing low before the bullish BOS or the first swing high before the bearish BOS, it invalidates the break of structure, suggesting a potential reversal or continuation of the previous trend.
This method provides users with a technical approach to filter market regimes, offering an advantage by minimizing the risk of overfitting to historical data, which is often a concern with traditional indicators like moving averages.
By focusing on identifying pivotal swing points and the subsequent breaks of structure, the strategy maintains a balance between sensitivity to market changes and robustness against historical data anomalies, ensuring a more adaptable and potentially more reliable market analysis tool.
----
What entry criteria are used in this script?
The script uses two entry models for trading decisions: BreakOut and Fractal.
Underlying Calculations:
Breakout: The script records the most recent swing high by storing it in a variable. When the price closes above this recorded level, and all other predefined conditions are satisfied, the script triggers a breakout entry. This approach is considered conservative because it waits for the price to confirm a breakout above the previous high before entering a trade. As shown in the image, as soon as the price closes above the new candle (first tick), the long entry gets taken. The stop-loss is initially set and then moved to break-even once the price moves in favor of the trade.
Fractal: This method involves identifying a swing low with a period of 2, which means it looks for a low point where the price is lower than the two candles before and after it. Once this pattern is detected, the script executes the trade. This is an aggressive approach since it doesn't wait for further price confirmation. In the image, this is represented by the 'Fractal 2' label where the script identifies and acts on the swing low pattern.
----
What type of stop-loss identification method are used in this strategy?
This strategy employs two types of stop-loss methods: Initial Stop-loss and Trailing Stop-Loss.
Underlying Calculations:
Initial Stop-loss:
ATR Based: The strategy uses the Average True Range (ATR) to set an initial stop-loss, which helps in accounting for market volatility without predicting price direction.
Calculation:
- First, the True Range (TR) is calculated for each period, which is the greatest of:
- Current Period High - Current Period Low
- Absolute Value of Current Period High - Previous Period Close
- Absolute Value of Current Period Low - Previous Period Close
- The ATR is then the moving average of these TR values over a specified period, typically 14 periods by default. This ATR value can be used to set the stop-loss at a distance from the entry price that reflects the current market volatility.
Swing Low Based:
For this method, the stop-loss is set based on the most recent swing low identified in the market structure analysis. This approach uses the lowest point of the recent price action as a reference for setting the stop-loss.
Trailing Stop-Loss:
The strategy uses structural liquidity and structural invalidation levels across multiple timeframes to adjust the stop-loss once the trade is profitable. This method involves:
Detecting Structural Liquidity: After a break of structure, the liquidity levels are updated to the first swing high in a bullish scenario or the first swing low in a bearish scenario. These levels serve as potential areas where the price might find support or resistance, allowing the stop-loss to trail the price movement.
Detecting Structural Invalidation: If the price returns to the level of the first swing low before a bullish break of structure or the first swing high before a bearish break of structure, it suggests the trend might be reversing or invalidating, prompting the adjustment of the stop-loss to lock in profits or minimize losses.
By using these methods, the strategy dynamically adjusts the initial stop-loss based on market volatility, helping to protect against adverse price movements while allowing for enough room for trades to develop. The ATR-based stop-loss adapts to the current market conditions by considering the volatility, ensuring that the stop-loss is not too tight during volatile periods, which could lead to premature exits, nor too loose during calm markets, which might result in larger losses. Similarly, the swing low based stop-loss provides a logical exit point if the market structure changes unfavorably.
Each market behaves differently across various timeframes, and it is essential to test different parameters and optimizations to find out which trailing stop-loss method gives you the desired results and performance. This involves backtesting the strategy with different settings for the ATR period, the distance from the swing low, and how the trailing stop-loss reacts to structural liquidity and invalidation levels.
Through this process, you can tailor the strategy to perform optimally in different market environments, ensuring that the stop-loss mechanism supports the trade's longevity while safeguarding against significant drawdowns.
----
What type of break-even method is used in this strategy? What are the underlying calculations?
Moves the initial stop-loss to the entry price when the price reaches a certain RR ratio.
Calculation:
Break-even level = Entry Price + (Initial Risk * RR Ratio)
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What tables are available in this script?
- Summary: Provides a general overview, displaying key performance parameters such as Net Profit, Profit Factor, Max Drawdown, Average Trade, Closed Trades and more.
Total Commission: Displays the cumulative commissions incurred from all trades executed within the selected backtesting window. This value is derived by summing the commission fees for each trade on your chart.
Average Commission: Represents the average commission per trade, calculated by dividing the Total Commission by the total number of closed trades. This metric is crucial for assessing the impact of trading costs on overall profitability.
Avg Trade: The sum of money gained or lost by the average trade generated by a strategy. Calculated by dividing the Net Profit by the overall number of closed trades. An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.
MaxDD: Displays the largest drawdown of losses, i.e., the maximum possible loss that the strategy could have incurred among all of the trades it has made. This value is calculated separately for every bar that the strategy spends with an open position.
Profit Factor: The amount of money a trading strategy made for every unit of money it lost (in the selected currency). This value is calculated by dividing gross profits by gross losses.
Avg RR: This is calculated by dividing the average winning trade by the average losing trade. This field is not a very meaningful value by itself because it does not take into account the ratio of the number of winning vs losing trades, and strategies can have different approaches to profitability. A strategy may trade at every possibility in order to capture many small profits, yet have an average losing trade greater than the average winning trade. The higher this value is, the better, but it should be considered together with the percentage of winning trades and the net profit.
Winrate: The percentage of winning trades generated by a strategy. Calculated by dividing the number of winning trades by the total number of closed trades generated by a strategy. Percent profitable is not a very reliable measure by itself. A strategy could have many small winning trades, making the percent profitable high with a small average winning trade, or a few big winning trades accounting for a low percent profitable and a big average winning trade. Most mean-reversion successful strategies have a percent profitability of 40-80% but are profitable due to risk management control.
BE Trades: Number of break-even trades, excluding commission/slippage.
Losing Trades: The total number of losing trades generated by the strategy.
Winning Trades: The total number of winning trades generated by the strategy.
Total Trades: Total number of taken traders visible your charts.
Net Profit: The overall profit or loss (in the selected currency) achieved by the trading strategy in the test period. The value is the sum of all values from the Profit column (on the List of Trades tab), taking into account the sign.
- Monthly: Displays performance data on a month-by-month basis, allowing users to analyze performance trends over each month and year.
- Weekly: Displays performance data on a week-by-week basis, helping users to understand weekly performance variations.
- UI Table: A user-friendly table that allows users to view and save the selected strategy parameters from user inputs. This table enables easy access to key settings and configurations, providing a straightforward solution for saving strategy parameters by simply taking a screenshot with Alt + S or ⌥ + S.
User-input styles and customizations:
Please note that all background colors in the style are disabled by default to enhance visualization.
How to Use This Strategy to Create a Profitable Edge and Systems?
Choose Your Strategy mode:
- Decide whether you are creating an investing strategy or a trading strategy.
Select a Market:
- Choose a one-sided market such as stocks, indices, or cryptocurrencies.
Historical Data:
- Ensure the historical data covers at least 10 years of price action for robust backtesting.
Timeframe Selection:
- Choose the timeframe you are comfortable trading with. It is strongly recommended to use a timeframe above 15 minutes to minimize the impact of commissions/slippage on your profits.
Set Commission and Slippage:
- Properly set the commission and slippage in the strategy properties according to your broker/prop firm specifications.
Parameter Optimization:
- Use trial and error to test different parameters until you find the performance results you are looking for in the summary table or, preferably, through deep backtesting using the strategy tester.
Trade Count:
- Ensure the number of trades is 200 or more; the higher, the better for statistical significance.
Positive Average Trade:
- Make sure the average trade is above zero.
(An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.)
Performance Metrics:
- Look for a high profit factor, and net profit with minimum drawdown.
- Ideally, aim for a drawdown under 20-30%, depending on your risk tolerance.
Refinement and Optimization:
- Try out different markets and timeframes.
- Continue working on refining your edge using the available filters and components to further optimize your strategy.
What Makes This Strategy Unique?
This strategy combines flexibility, smart risk management, and momentum focus in a way that’s rare and practical:
1. Adapts to Any Market Rhythm
Works on daily, weekly, or intraday charts without code changes.
Uses two entry types: classic breakouts (like trending stocks) or fractal patterns (to avoid false starts).
2. Smarter Stop-Loss System
No rigid rules: Stops adjust based on price structure (e.g., new “higher lows”), not fixed percentages.
Avoids whipsaws: Tightens stops only when the trend strengthens, not in choppy markets.
3. Safe Profit-Boosting Pyramiding
Adds new positions only after prior trades are risk-free (stops moved above breakeven).
Scales up using locked-in profits, not new capital, to grow gains safely.
4. Built-In Momentum Check
Tracks 1/3/6-month price growth to spotlight stocks with strong, lasting momentum.
Terms and Conditions | Disclaimer
Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data.
Built-in components, features, and functionalities of our charting tools are the intellectual property of @Fractalyst Unauthorized use, reproduction, or distribution of these proprietary elements is prohibited.
- By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer and agrees to respect our intellectual property rights and comply with all applicable laws and regulations.
Relative Strength Index//@version=6
indicator(title="Relative Strength Index", shorttitle="RSI", format=format.price, precision=2, timeframe="", timeframe_gaps=true)
// RSI Settings
rsiLengthInput = input.int(14, minval=1, title="RSI Length", group="RSI Settings")
rsiSourceInput = input.source(close, "Source", group="RSI Settings")
calculateDivergence = input.bool(false, title="Calculate Divergence", group="RSI Settings", display = display.data_window, tooltip = "Calculating divergences is needed in order for divergence alerts to fire.")
// RSI Calculation
change = ta.change(rsiSourceInput)
up = ta.rma(math.max(change, 0), rsiLengthInput)
down = ta.rma(-math.min(change, 0), rsiLengthInput)
rsi = down == 0 ? 100 : up == 0 ? 0 : 100 - (100 / (1 + up / down))
// Smoothing MA inputs
GRP = "Smoothing"
TT_BB = "Only applies when 'SMA + Bollinger Bands' is selected. Determines the distance between the SMA and the bands."
maTypeInput = input.string("SMA", "Type", options = , group = GRP, display = display.data_window)
maLengthInput = input.int(14, "Length", group = GRP, display = display.data_window)
bbMultInput = input.float(2.0, "BB StdDev", minval = 0.001, maxval = 50, step = 0.5, tooltip = TT_BB, group = GRP, display = display.data_window)
var enableMA = maTypeInput != "None"
var isBB = maTypeInput == "SMA + Bollinger Bands"
// Smoothing MA Calculation
ma(source, length, MAtype) =>
switch MAtype
"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)
// Calculate MA
smoothingMA = enableMA ? ma(rsi, maLengthInput, maTypeInput) : na
// Define RSI color based on position relative to MA
rsiColor = enableMA ? (rsi > smoothingMA ? color.green : color.red) : (rsi > rsi ? color.green : color.red)
// Plot RSI with dynamic color
rsiPlot = plot(rsi, "RSI", color = rsiColor)
// Horizontal lines
rsiUpperBand = hline(70, "RSI Upper Band (70)", color=#787B86, linestyle=hline.style_solid)
rsiUpperMidBand = hline(60, "RSI Upper Mid Band (60)", color=color.new(#787B86, 30), linestyle=hline.style_dashed)
midline = hline(50, "RSI Middle Band (50)", color=color.new(#787B86, 50))
rsiLowerMidBand = hline(40, "RSI Lower Mid Band (40)", color=color.new(#787B86, 30), linestyle=hline.style_dashed)
rsiLowerBand = hline(30, "RSI Lower Band (30)", color=#787B86, linestyle=hline.style_solid)
// Fills
fill(rsiUpperBand, rsiUpperMidBand, color=color.new(color.green, 90), title="Extreme Overbought Zone")
fill(rsiUpperMidBand, midline, color=color.new(color.green, 95), title="Overbought Zone")
fill(midline, rsiLowerMidBand, color=color.new(color.red, 95), title="Oversold Zone")
fill(rsiLowerMidBand, rsiLowerBand, color=color.new(color.red, 90), title="Extreme Oversold Zone")
midLinePlot = plot(50, color = na, editable = false, display = display.none)
fill(rsiPlot, midLinePlot, 100, 70, top_color = color.new(color.green, 0), bottom_color = color.new(color.green, 100), title = "Overbought Gradient Fill")
fill(rsiPlot, midLinePlot, 30, 0, top_color = color.new(color.red, 100), bottom_color = color.new(color.red, 0), title = "Oversold Gradient Fill")
// Smoothing MA plots
smoothingStDev = isBB ? ta.stdev(rsi, maLengthInput) * bbMultInput : na
plot(smoothingMA, "RSI-based MA", color=color.yellow, display = enableMA ? display.all : display.none, editable = enableMA)
bbUpperBand = plot(smoothingMA + smoothingStDev, title = "Upper Bollinger Band", color=color.green, display = isBB ? display.all : display.none, editable = isBB)
bbLowerBand = plot(smoothingMA - smoothingStDev, title = "Lower Bollinger Band", color=color.green, display = isBB ? display.all : display.none, editable = isBB)
fill(bbUpperBand, bbLowerBand, color= isBB ? color.new(color.green, 90) : na, title="Bollinger Bands Background Fill", display = isBB ? display.all : display.none, editable = isBB)
// Divergence (unchanged)
lookbackRight = 5
lookbackLeft = 5
rangeUpper = 60
rangeLower = 5
bearColor = color.red
bullColor = color.green
textColor = color.white
noneColor = color.new(color.white, 100)
_inRange(cond) =>
bars = ta.barssince(cond)
rangeLower <= bars and bars <= rangeUpper
plFound = false
phFound = false
bullCond = false
bearCond = false
rsiLBR = rsi
if calculateDivergence
plFound := not na(ta.pivotlow(rsi, lookbackLeft, lookbackRight))
plFoundPrev = plFound
inRangeBull = _inRange(plFoundPrev)
rsiHL = rsiLBR > ta.valuewhen(plFound, rsiLBR, 1) and inRangeBull
lowLBR = low
priceLL = lowLBR < ta.valuewhen(plFound, lowLBR, 1)
bullCond := priceLL and rsiHL and plFound
phFound := not na(ta.pivothigh(rsi, lookbackLeft, lookbackRight))
phFoundPrev = phFound
inRangeBear = _inRange(phFoundPrev)
rsiLH = rsiLBR < ta.valuewhen(phFound, rsiLBR, 1) and inRangeBear
highLBR = high
priceHH = highLBR > ta.valuewhen(phFound, highLBR, 1)
bearCond := priceHH and rsiLH and phFound
plot(plFound ? rsiLBR : na, offset = -lookbackRight, title = "Regular Bullish", linewidth = 2, color = (bullCond ? bullColor : noneColor), display = display.pane, editable = calculateDivergence)
plotshape(bullCond ? rsiLBR : na, offset = -lookbackRight, title = "Regular Bullish Label", text = " Bull ", style = shape.labelup, location = location.absolute, color = bullColor, textcolor = textColor, display = display.pane, editable = calculateDivergence)
plot(phFound ? rsiLBR : na, offset = -lookbackRight, title = "Regular Bearish", linewidth = 2, color = (bearCond ? bearColor : noneColor), display = display.pane, editable = calculateDivergence)
plotshape(bearCond ? rsiLBR : na, offset = -lookbackRight, title = "Regular Bearish Label", text = " Bear ", style = shape.labeldown, location = location.absolute, color = bearColor, textcolor = textColor, display = display.pane, editable = calculateDivergence)
alertcondition(bullCond, title='Regular Bullish Divergence', message="Found a new Regular Bullish Divergence, `Pivot Lookback Right` number of bars to the left of the current bar.")
alertcondition(bearCond, title='Regular Bearish Divergence', message='Found a new Regular Bearish Divergence, `Pivot Lookback Right` number of bars to the left of the current bar.')
Pinbar DetectorFinding a pinbars on m5 timeframe. In order for the indicator to search for pinbars specifically on the M5 timeframe (5 minutes), you need to set this value in the tf parameter by default. In the current code, the timeframe is set via input.timeframe, and you can either change it manually in the indicator settings after adding it to the chart, or set M5 directly in the code.
Here's how to do it:
Change in code: In the line with input.timeframe, replace the default value "D" with "5" (in Pine Script, timeframes are designated as follows: "5" for 5 minutes, "15" for 15 minutes, "60" for 1 hour, etc.).
Volume Box PressureThis is a liquidity analysis to determine support and resistance from large volumes that are automatically detected. Its use is if the candle breakout upwards from the box, then the candle would fly high. Conversely, if the candle breakdown downwards from the box, then the candle would fall deep.
avgPrice v2 - VF20Here I create my own indicator on Tradingview to detect whale movements in stocks, crypto, & forex, which is suitable for all trading instruments.
By using the whale approach and technical analysis, it is useful for detecting increases based on whale/market maker buying actions and detecting decreases based on whale/market maker selling actions.
There is also an automatic analysis of "Long" and "Short" so it is easy to use, with 3 line features with different colors and different functions as explained below:
If the gray line is below the yellow line, then there is accumulation by whales, conversely if the gray line is above the yellow line, then there is distribution by whales.
I created this indicator, dedicated specifically to friends who have difficulty trading and want to keep it simple, "Buy" is enough "Buy" and "Sell" is enough "Sell". I have summarized all whale detection analysis in one simple indicator.
I like to share and I love the world of trading, for me this is like a second life. Hopefully this description is useful and motivates friends to get consistent profits from trading.
Greetings,
TREND FINDER BY MRS (SSL Hybrid + Delta Candles)Perfect for identifying trend direction, continuation signals, and exit points while visualizing real-time buying/selling pressure.
A sophisticated multi-timeframe trading system combining:
SSL Hybrid Trend Analysis (HMA/JMA/EMA baseline)
Volume Delta Visualization (colored candles)
ATR Volatility Bands (optional)
Key Features:
1. Smart Trend Detection
Custom Baseline MA: Choose between HMA, JMA (Jurik), or EMA with adjustable length
Trend-Colored Baseline:
🟢 Green = Uptrend (price above & baseline rising)
🔴 Red = Downtrend (price below & baseline falling)
🟠 Orange = Neutral/Transition phase
2. Volume Delta Candles
Colors candles based on lower timeframe volume imbalance:
🟢 Dark Green: Strong buying pressure (delta > 20%)
🌱 Light Green: Moderate buying (delta 5-20%)
🔴 Dark Red: Strong selling pressure (delta < -20%)
🌸 Light Red: Moderate selling (delta -5% to -20%)
⚪ Gray: Balanced volume
3. Professional Tools
ATR Bands: Visualize volatility with adjustable multiplier
Multi-Timeframe Analysis: Delta calculated from lower timeframe (default: 1min)
Alerts: Baseline crosses and extreme delta conditions
Recommended Settings:
Chart Type: Daily (for NNFX method)
Baseline: HMA/JMA (60 periods)
Delta TF: 1-5min for intraday volume accuracy
How Traders Use It:
Trend Traders: Follow colored baseline for direction
Swing Traders: Use delta extremes for reversals
Breakout Traders: Watch ATR band expansions
Published Notes:
TREND FINDER BY MRS (SSL Hybrid with Delta Candles)
By: Rajasekhar Muvvala
*"See the trend, read the volume, trade with confidence"*
Installation:
1. Add to TradingView via Pine Editor
2. Customize colors/thresholds in settings
3. Apply to daily charts for best results
Pro Tip:
Combine with:
- 200EMA for long-term bias
- Horizontal S/R levels
- Price action confirmation
This description highlights the indicator's unique value while making it accessible for both beginners and advanced traders. The markdown formatting ensures clean presentation when published on trading forums or journals. Would you like me to adjust any technical aspects or emphasize different features?
RSI + MFI Momentum Mapper - CoffeeKillerRSI + MFI Momentum Mapper - CoffeeKiller Indicator Guide
Welcome traders! This guide will walk you through the RSI + MFI Momentum Mapper indicator, an innovative market analysis tool developed by CoffeeKiller that combines two powerful oscillators to create a comprehensive momentum visualization system.
🔔 **Warning: This Is Not a Standard RSI or MFI Indicator** 🔔 This indicator combines and normalizes RSI and MFI data to create a unified momentum representation with boundary detection and peak signaling features.
Core Concept: Combined Momentum Analysis
The foundation of this indicator lies in merging the strengths of two complementary oscillators - Relative Strength Index (RSI) and Money Flow Index (MFI) - to provide a more robust momentum signal that accounts for both price action and volume.
Directional Columns: Momentum Strength
- Positive Green Columns: Bullish momentum
- Negative Red Columns: Bearish momentum
- Color intensity varies based on momentum strength
- Special coloring for new high/low boundaries
Marker Lines: Dynamic Support/Resistance
- High Marker Line (Magenta): Tracks the highest point reached during a bullish phase
- Low Marker Line (Cyan): Tracks the lowest point reached during a bearish phase
- Creates visual boundaries showing momentum extremes
Peak Detection System:
- Triangular markers identify significant local maxima and minima
- Background highlighting shows important momentum peaks
- Helps identify potential reversal points and momentum exhaustion
Reference Lines:
- Zero Line (Gray): Divides bullish from bearish momentum
- High Line (+1): Upper threshold for extremely bullish conditions
- Low Line (-1): Lower threshold for extremely bearish conditions
Core Components
1. Oscillator Normalization
- RSI and MFI values centered around zero
- Values scaled to create consistent visualization
- Normalized range typically between -1 and +1
- Combination of indicators for signal reliability
2. Boundary Tracking System
- Automatic detection of highest values in bullish phases
- Automatic detection of lowest values in bearish phases
- Step-line visualization of boundaries
- Color-coded for easy identification
3. Peak Detection System
- Identification of local maxima and minima
- Background highlighting of significant peaks
- Triangle markers for peak visualization
- Zero-line cross detection for trend changes
4. Signal Smoothing
- Signal line calculation via SMA
- Helps filter noise and identify trends
- Provides confirmation of momentum direction
Main Features
Oscillator Settings
- Customizable RSI length for sensitivity control
- Customizable MFI length for sensitivity control
- Normalized display for consistent visualization
- Signal smoothing for clearer readings
Visual Elements
- Color-coded columns showing momentum direction and strength
- Dynamic marker lines for momentum boundaries
- Peak triangles for significant turning points
- Background highlighting for peak identification
- Reference lines for momentum threshold levels
Signal Generation
- Zero-line crosses for trend change signals
- Boundary breaks for momentum strength
- Peak formation for potential reversals
- Color changes for momentum direction and acceleration
Customization Options
- RSI and MFI length parameters
- Marker line visibility and colors
- Peak marker color selection
- Peak background display options
Trading Applications
1. Trend Identification
- Directional line crossing above zero: bullish trend beginning
- Directional line crossing below zero: bearish trend beginning
- Column color: indicates momentum direction
- Column height: indicates momentum strength
2. Reversal Detection
- Peak triangles after extended trend: potential exhaustion
- Background highlighting: significant reversal points
- Directional line approaching marker lines: potential trend change
- Color shifts from bright to muted: decreasing momentum
3. Momentum Analysis
- Breaking above previous high boundary: accelerating bullish momentum
- Breaking below previous low boundary: accelerating bearish momentum
- Special coloring (magenta/cyan): boundary breaks indicating strength
- Approaching +1/-1 lines: extreme momentum conditions
4. Market Structure Assessment
- Consecutive higher peaks: strengthening bullish structure
- Consecutive lower troughs: strengthening bearish structure
- Peak comparisons: relative strength of momentum phases
- Boundary line steps: market structure levels
Optimization Guide
1. Oscillator Settings
- RSI Length: Default 14 provides balanced signals
- Lower values (7-10): More responsive, potentially noisier
- Higher values (20-30): Smoother, fewer false signals
- MFI Length: Default 14 provides balanced signals
- Lower values: More responsive to volume changes
- Higher values: Less sensitive to short-term volume spikes
2. Visual Customization
- Marker Line Colors: Adjust for visibility on your chart
- Peak Marker Color: Default yellow provides good contrast
- Enable/disable background highlights based on preference
- Consider chart background when selecting colors
3. Signal Interpretation
- Stronger signals: When directional line approaches +1/-1
- Confirmation: When peaks form after extended momentum
- Early warnings: When color intensity changes before direction
- Trend strength: Distance between zero line and current reading
4. Reference Line Usage
- Zero line: Primary trend divider
- +1/-1 lines: Extreme momentum thresholds
- Marker lines: Dynamic support/resistance levels
- Distance from reference: Momentum strength measure
Best Practices
1. Signal Confirmation
- Wait for zero-line crosses to confirm trend changes
- Look for peak formations to identify potential reversals
- Check for boundary breaks to confirm strong momentum
- Use with price action for entry/exit precision
2. Timeframe Selection
- Lower timeframes: more signals, potential noise
- Higher timeframes: cleaner signals, less frequent
- Multiple timeframes: confirm signals across time horizons
- Match to your trading style and holding period
3. Market Context
- Strong bullish phase: positive columns breaking above marker line
- Strong bearish phase: negative columns breaking below marker line
- Columns approaching zero: potential trend change
- Columns approaching +1/-1: extreme conditions, potential reversal
4. Combining with Other Indicators
- Use with trend indicators for confirmation
- Pair with other oscillators for divergence detection
- Combine with volume analysis for validation
- Consider support/resistance levels with boundary lines
Advanced Trading Strategies
1. Boundary Break Strategy
- Enter long when directional line breaks above previous high marker line
- Enter short when directional line breaks below previous low marker line
- Use zero-line as initial stop-loss reference
- Take profits at formation of opposing peaks
2. Peak Trading Strategy
- Identify significant peaks with triangular markers
- Look for consecutive lower peaks in bullish phases for shorting opportunities
- Look for consecutive higher troughs in bearish phases for buying opportunities
- Use zero-line crosses as confirmation
3. Extreme Reading Strategy
- Look for directional line approaching +1/-1 lines
- Watch for color changes and peak formations
- Enter counter-trend positions after confirmed peaks
- Use tight stops due to extreme momentum conditions
4. Column Color Strategy
- Enter long when columns turn bright green (increasing momentum)
- Enter short when columns turn bright red (increasing momentum)
- Exit when color intensity fades (decreasing momentum)
- Use marker lines as dynamic support/resistance
Practical Analysis Examples
Bullish Market Scenario
- Directional line crosses above zero line
- Green columns grow in height and intensity
- High marker line forms steps upward
- Peak triangles appear at local maxima
- Background highlights appear at significant momentum peaks
Bearish Market Scenario
- Directional line crosses below zero line
- Red columns grow in depth and intensity
- Low marker line forms steps downward
- Peak triangles appear at local minima
- Background highlights appear at significant momentum troughs
Consolidation Scenario
- Directional line oscillates around zero line
- Column colors alternate frequently
- Marker lines remain relatively flat
- Few or no new peak highlights appear
- Directional values remain small
Understanding Market Dynamics Through RSI + MFI Momentum Mapper
At its core, this indicator provides a unique lens to visualize market momentum by combining two complementary oscillators:
1. Combined Strength: By averaging RSI (price-based) and MFI (volume-based), the indicator provides a more comprehensive view of market momentum that considers both price action and buying/selling pressure.
2. Normalized Scale: The indicator normalizes values around zero, making it easier to identify bullish vs bearish conditions and the relative strength of momentum in either direction.
3. Dynamic Boundaries: The marker lines create a visual representation of the "high water marks" of momentum in both directions, helping to identify when markets are making new momentum extremes.
4. Exhaustion Signals: The peak detection system highlights moments where momentum has reached a local maximum or minimum, often precursors to reversals or consolidations.
Remember:
- Combine signals from directional line, marker lines, and peak formations
- Use appropriate timeframe settings for your trading style
- Customize the indicator to match your visual preferences
- Consider market conditions and correlate with price action
This indicator works best when:
- Used as part of a comprehensive trading system
- Combined with proper risk management
- Applied with an understanding of current market conditions
- Signals are confirmed by price action and other indicators
DISCLAIMER: This indicator and its signals are intended solely for educational and informational purposes. They do not constitute financial advice. Trading involves significant risk of loss. Always conduct your own analysis and consult with financial professionals before making trading decisions.
Fibonacci BB Strategy with RSI + 2% Exit📈 Fibonacci BB Strategy with RSI + 2% Profit Exit
This strategy combines a VWMA-based Bollinger Band system with RSI confirmation and a 2% profit-taking mechanism, offering a balanced blend of trend and momentum trading.
🔍 Key Features:
✅ VWMA-Based Bands: Uses a 200-period Volume Weighted Moving Average (VWMA) to create dynamic support and resistance bands with standard deviation. Helps capture trend direction with volume-weighted precision.
✅ Entry Signals:
Long Entry: When price crosses above the upper VWMA band.
Short Entry: When price crosses below the lower VWMA band.
✅ Exit Conditions:
Profit Target: Positions close automatically at a 2% profit (customizable).
RSI-Based Exit:
Longs close when RSI < 30 (oversold).
Shorts close when RSI > 70 (overbought).
✅ Built-in Risk Management: Avoids greed-based exits by locking in profits early or exiting on reversal signals.
⚙️ User Inputs:
VWMA length (default: 200)
Deviation multiplier for bands (default: 3.0)
RSI length (default: 14)
Profit target in % (default: 2%)
🧠 How to Use:
Works best in strong trending markets.
Can be combined with higher-timeframe trend filters or volume analysis.
Suitable for both swing trading and intraday strategies.
Volume Delta Divergence + Bollinger Bands (Filtered)📌 Volume Delta Divergence with Bollinger Bands (Filtered)
This script combines Volume Delta Divergence detection with Bollinger Bands to help identify high-probability buy and sell signals based on volume behavior and price action.
🔍 Key Features:
✅ Divergence Detection: Identifies when price moves in one direction (green/red candle), but the delta volume (buy vs sell volume) moves in the opposite direction — a common sign of hidden weakness or strength.
✅ Volume Strength Filter: Filters out weak divergence signals by checking if the delta volume is significantly larger than its historical average (user-defined lookback).
✅ Breakout Confirmation: A signal is only triggered when the next candle breaks the high or low of the divergence candle.
✅ Bollinger Bands Overlay: Adds standard Bollinger Bands (20-period SMA ± 2 standard deviations by default) for trend and volatility analysis.
✅ Clean Signal Display: Plots "BUY" and "SELL" labels only when strong divergences occur, reducing noise and false signals.
⚙️ User Inputs:
Custom timeframe for volume delta analysis
Delta volume average lookback period
Bollinger Band settings (length & deviation)
🧠 How to Use:
Use the divergence signals in conjunction with Bollinger Band positioning.
Consider SELL signals stronger when they occur near the upper Bollinger Band, and BUY signals near the lower band.
Combine with price action or RSI for added confluence.
Stock Buy SignalThis is for daily purchase strategy, buying at crosses of super trend followed by exit at 3%
Initiative Analysis CoreInitiative Analysis (IA) Indicator
Initiative Analysis (IA) is an innovative technical analysis tool based on a unique concept of visualizing and analyzing the real battle between buyers and sellers.
🔍 What is IA and how does it work?
IA identifies initiatives on the chart — directional price moves caused by the actions of buyers or sellers. These initiatives form the three key phases of the market:
• Sideways range (consolidation)
• Trend
• Transitional period
Each initiative has a time limit and a price range. This helps traders clearly see:
• Who currently controls the market;
• What key levels and activity zones are forming;
• Where the price is likely to meet support or resistance.
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Main Features and How to Read the Chart:
✅ Identifying Buyer and Seller Initiatives (Dominant Zones)
• A blue background shows a buyer’s initiative — buyers control the market and price is expected to rise (colors can be customized).
• A red background shows a seller’s initiative — sellers control the market and price is expected to fall.
✅ Key Price Levels
• The bottom edge of the blue zone = potential demand/support level.
• The top edge of the red zone = potential supply/resistance level.
• The blue line = potential target level during bullish phases.
• The red line = potential target level during bearish phases.
✅ Levels Inside Initiatives
• The indicator can show up to 5 levels inside each initiative (like Fibonacci levels), which you can set manually in the settings.
✅ Multi-Timeframe Analysis
• Visual elements (initiatives, levels, targets) are shown for two timeframes at once: the current chart timeframe and a higher timeframe of your choice.
• This helps to do full analysis without switching charts.
✅ Key Candles in Initiative Analysis
• KC (Key Candle): the candle with the highest volume within an Initiative.
• tKC (Temporary Key Candle): a temporary high-volume candle that forms after the KC. It may become the new KC if the Initiative extends beyond the previous range.
• IKC (Internal Key Candle): the candle with the highest volume among Initiatives that form inside a sideways range. If KC/tKC and IKC appear in opposite directions within the same Initiative, IKC takes priority.
• One possible approach for finding long setups: look for a buyer-side KC, tKC, or IKC within the lower 50% of the Initiative, or a seller-side KC/tKC/IKC on the lower boundary that has been absorbed by buyers. The reverse applies when looking for short setups.
✅ Customization
• All colors and elements can be easily adjusted to fit your trading style.
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💡 Why is IA useful for traders and investors?
• Color-coded zones make market context easy to understand: who’s in control, key levels, possible initiative change;
• Saves a lot of time on market analysis;
• Helps find return zones and high-potential entry points;
• Helps forecast potential price targets;
• Makes reading market structure simple and clear.
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The public version of the IA Indicator (IA Core) provides the following features:
• Full real-time functionality for BTC/USDT (Spot). Access to other instruments or contract types requires the IA Advanced version.
• Real-time visualization of initiatives and target levels, as well as simultaneous display of key elements (initiatives, levels, and targets) on the 15-minute and weekly timeframes for all other assets.
• Historical data analysis across all timeframes for all assets. Explore past price movements and evaluate the effectiveness of the IA concept. (Note: the most recent historical segments may be unavailable depending on the selected timeframe.)
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📖 Soon-to-be Published Articles
We will soon publish articles explaining:
• What Initiative Analysis is,
• How it helps traders and investors,
• How it saves time,
• How it helps identify return zones and entry points,
• How it differs from other methods.
Below is a short excerpt from the first article to help you understand the basics of chart reading:
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🖼️ Look at this chart:
When one side controls the market strongly, we see a single background color in price ranges. In this case, it makes sense to look for trades in the direction of the move. But it’s important to check the higher timeframe for confirmation (!).
In the chart:
• A blue target line means a bullish target (thin line = 1H, thick = 1D).
• A black target line means a bearish target (same logic for thickness).
• Targets are calculated using a custom method that includes the initiative range, candle structure inside the initiative, and traded volumes.
• Once a candle crosses the target line, the target is considered reached.
• If a new target appears, it will be shown.
• If the price leaves the buyer zone, the blue target disappears until the price returns. Same rule for seller zones.
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📉 Sideways Market (Range)
If the chart background changes between red and blue in one price range, it means the market is in consolidation (sideways) — temporary balance between buyers and sellers. In this case, targets also switch: blue = buy target, red = sell target.
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🔀 Transitional Phase
Sometimes, two price zones may appear at the same time — one above (buyers), one below (sellers). This is a transition period. It may turn into a sideways range or develop into a trend.
During transitions:
• It’s better to avoid trading.
• Check who controlled the price before, and who is in control on the higher timeframe (this is always important).
• For example, if sellers were in control before, and the higher timeframe confirms it, sellers are likely to stay dominant. However, a short-term bounce or trend reversal is possible.
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💰 Wishing you profitable trades!
Bi Trend signalauto bot MT5 for XAU, BTC ETH, liên hệ tôi để biết thêm chi tiết cho các hạng mục coppy trade
RSI Intraday High AccuracyThis is a high-accuracy RSI-based intraday trading indicator written in TradingView Pine Script. It identifies overbought and oversold zones to generate buy/sell signals while also providing EMA confirmation to enhance signal accuracy.
02 SMC + BB Breakout (Improved)This strategy combines Smart Money Concepts (SMC) with Bollinger Band breakouts to identify potential trading opportunities. SMC focuses on identifying key price levels and market structure shifts, while Bollinger Bands help pinpoint overbought/oversold conditions and potential breakout points. The strategy also incorporates higher timeframe trend confirmation to filter out trades that go against the prevailing trend.
Key Components:
Bollinger Bands:
Calculated using a Simple Moving Average (SMA) of the closing price and a standard deviation multiplier.
The strategy uses the upper and lower bands to identify potential breakout points.
The SMA (basis) acts as a centerline and potential support/resistance level.
The fill between the upper and lower bands can be toggled by the user.
Higher Timeframe Trend Confirmation:
The strategy allows for optional confirmation of the current trend using a higher timeframe (e.g., daily).
It calculates the SMA of the higher timeframe's closing prices.
A bullish trend is confirmed if the higher timeframe's closing price is above its SMA.
This helps filter out trades that go against the prevailing long-term trend.
Smart Money Concepts (SMC):
Order Blocks:
Simplified as recent price clusters, identified by the highest high and lowest low over a specified lookback period.
These levels are considered potential areas of support or resistance.
Liquidity Zones (Swing Highs/Lows):
Identified by recent swing highs and lows, indicating areas where liquidity may be present.
The Swing highs and lows are calculated based on user defined lookback periods.
Market Structure Shift (MSS):
Identifies potential changes in market structure.
A bullish MSS occurs when the closing price breaks above a previous swing high.
A bearish MSS occurs when the closing price breaks below a previous swing low.
The swing high and low values used for the MSS are calculated based on the user defined swing length.
Entry Conditions:
Long Entry:
The closing price crosses above the upper Bollinger Band.
If higher timeframe confirmation is enabled, the higher timeframe trend must be bullish.
A bullish MSS must have occurred.
Short Entry:
The closing price crosses below the lower Bollinger Band.
If higher timeframe confirmation is enabled, the higher timeframe trend must be bearish.
A bearish MSS must have occurred.
Exit Conditions:
Long Exit:
The closing price crosses below the Bollinger Band basis.
Or the Closing price falls below 99% of the order block low.
Short Exit:
The closing price crosses above the Bollinger Band basis.
Or the closing price rises above 101% of the order block high.
Position Sizing:
The strategy calculates the position size based on a fixed percentage (5%) of the strategy's equity.
This helps manage risk by limiting the potential loss per trade.
Visualizations:
Bollinger Bands (upper, lower, and basis) are plotted on the chart.
SMC elements (order blocks, swing highs/lows) are plotted as lines, with user-adjustable visibility.
Entry and exit signals are plotted as shapes on the chart.
The Bollinger band fill opacity is adjustable by the user.
Trading Logic:
The strategy aims to capitalize on Bollinger Band breakouts that are confirmed by SMC signals and higher timeframe trend. It looks for breakouts that align with potential market structure shifts and key price levels (order blocks, swing highs/lows). The higher timeframe filter helps avoid trades that go against the overall trend.
In essence, the strategy attempts to identify high-probability breakout trades by combining momentum (Bollinger Bands) with structural analysis (SMC) and trend confirmation.
Key User-Adjustable Parameters:
Bollinger Bands Length
Standard Deviation Multiplier
Higher Timeframe
Higher Timeframe Confirmation (on/off)
SMC Elements Visibility (on/off)
Order block lookback length.
Swing lookback length.
Bollinger band fill opacity.
This detailed description should provide a comprehensive understanding of the strategy's logic and components.
***DISCLAIMER: This strategy is for educational purposes only. It is not financial advice. Past performance is not indicative of future results. Use at your own risk. Always perform thorough backtesting and forward testing before using any strategy in live trading.***
TW SMAa Simple Moving Average (SMA) with a glowing effect. The logic behind this script can be broken down into the following key components:
The result is an SMA with a smooth glowing effect, making it easier to visualize trend direction.
The color change in the SMA itself provides clear bullish and bearish indications.
The glow layers create an appealing and intuitive representation of price movement relative to the SMA.
