Revolutionize Trading with Mean Reversion Channel and Multi-Timeframe Analysis in Pine Script

//@version=5
indicator('Mean Revg', shorttitle='MgggRC', overlay=true, format=format.inherit, max_bars_back = 4800, precision = 5)

//************************************************************************************************************
// Parameter
//************************************************************************************************************

indiSet = input(false, '═════════ MRC Parameter ════════')
source = input(hlc3, title='Price Source')
type = input.string('SuperSmoother', title='Filter Type', options=['SuperSmoother', 'Ehlers EMA', 'Gaussian', 'Butterworth', 'BandStop', 'SMA', 'EMA', 'RMA'])
length = input.int(200, title='Lookback Period', minval=1)
innermult = input.float(1.0, title='Inner Channel Size Multiplier', minval=0.1)
outermult = input.float(2.415, title='Outer Channel Size Multiplier', minval=0.1)

ChartSet = input(false, '═════════ Chart Setting ════════')
drawchannel = input(true, title='Draw Channel')
displayzone = input(true, title='Draw Zone (With Channel)')
zonetransp = input.int(60, title='Zone Transparency', minval=0, maxval=100)
displayline = input(true, title='Display Line Extension')

MTFSet = input(false, '═════════ MTF Setting ════════')
enable_mtf = input(true, title='Enable Multiple TimeFrame Analysis')
mtf_disp_typ = input.string('On Hover', title='MTF Display Type', options=['Always Display', 'On Hover'])
mtf_typ = input.string('Auto', title='Multiple TimeFrame Type', options=['Auto', 'Custom'])
mtf_lvl1 = input.timeframe('D', title='Custom MTF Level 1')
mtf_lvl2 = input.timeframe('W', title='Custom MTF Level 2')

//************************************************************************************************************
// Functions Start {
//************************************************************************************************************
var pi = 2 * math.asin(1)
var mult = pi * innermult
var mult2 = pi * outermult
var gradsize = 0.5
var gradtransp = zonetransp

//-----------------------
// Ehler SwissArmyKnife Function
//-----------------------
SAK_smoothing(_type, _src, _length) =>
    c0 = 1.0
    c1 = 0.0
    b0 = 1.0
    b1 = 0.0
    b2 = 0.0
    a1 = 0.0
    a2 = 0.0
    alpha = 0.0
    beta = 0.0
    gamma = 0.0
    cycle = 2 * pi / _length

    if _type == 'Ehlers EMA'
        alpha := (math.cos(cycle) + math.sin(cycle) - 1) / math.cos(cycle)
        b0 := alpha
        a1 := 1 - alpha
        a1
    if _type == 'Gaussian'
        beta := 2.415 * (1 - math.cos(cycle))
        alpha := -beta + math.sqrt(beta * beta + 2 * beta)
        c0 := alpha * alpha
        a1 := 2 * (1 - alpha)
        a2 := -(1 - alpha) * (1 - alpha)
        a2
    if _type == 'Butterworth'
        beta := 2.415 * (1 - math.cos(cycle))
        alpha := -beta + math.sqrt(beta * beta + 2 * beta)
        c0 := alpha * alpha / 4
        b1 := 2
        b2 := 1
        a1 := 2 * (1 - alpha)
        a2 := -(1 - alpha) * (1 - alpha)
        a2
    if _type == 'BandStop'
        beta := math.cos(cycle)
        gamma := 1 / math.cos(cycle * 2 * 0.1)  // delta default to 0.1. Acceptable delta -- 0.05<d<0.5
        alpha := gamma - math.sqrt(gamma * gamma - 1)
        c0 := (1 + alpha) / 2
        b1 := -2 * beta
        b2 := 1
        a1 := beta * (1 + alpha)
        a2 := -alpha
        a2
    if _type == 'SMA'
        c1 := 1 / _length
        b0 := 1 / _length
        a1 := 1
        a1
    if _type == 'EMA'
        alpha := 2 / (_length + 1)
        b0 := alpha
        a1 := 1 - alpha
        a1
    if _type == 'RMA'
        alpha := 1 / _length
        b0 := alpha
        a1 := 1 - alpha
        a1

    _Input = _src
    _Output = 0.0
    _Output := c0 * (b0 * _Input + b1 * nz(_Input[1]) + b2 * nz(_Input[2])) + a1 * nz(_Output[1]) + a2 * nz(_Output[2]) - c1 * nz(_Input[_length])
    _Output

//-----------------------
// SuperSmoother Function
//-----------------------
supersmoother(_src, _length) =>
    s_a1 = math.exp(-math.sqrt(2) * pi / _length)
    s_b1 = 2 * s_a1 * math.cos(math.sqrt(2) * pi / _length)
    s_c3 = -math.pow(s_a1, 2)
    s_c2 = s_b1
    s_c1 = 1 - s_c2 - s_c3
    ss = 0.0
    ss := s_c1 * _src + s_c2 * nz(ss[1], _src[1]) + s_c3 * nz(ss[2], _src[2])
    ss

//-----------------------
// Auto TimeFrame Function
//-----------------------
// ————— Converts current chart resolution into a float minutes value.
f_resInMinutes() =>
    _resInMinutes = timeframe.multiplier * (timeframe.isseconds ? 1. / 60 : timeframe.isminutes ? 1. : timeframe.isdaily ? 60. * 24 : timeframe.isweekly ? 60. * 24 * 7 : timeframe.ismonthly ? 60. * 24 * 30.4375 : na)
    _resInMinutes

get_tf(_lvl) =>
    y = f_resInMinutes()
    z = timeframe.period
    if mtf_typ == 'Auto'
        if y < 1
            z := _lvl == 1 ? '1' : _lvl == 2 ? '5' : z
            z
        else if y <= 3
            z := _lvl == 1 ? '5' : _lvl == 2 ? '15' : z
            z
        else if y <= 10
            z := _lvl == 1 ? '15' : _lvl == 2 ? '60' : z
            z
        else if y <= 30
            z := _lvl == 1 ? '60' : _lvl == 2 ? '240' : z
            z
        else if y <= 120
            z := _lvl == 1 ? '240' : _lvl == 2 ? 'D' : z
            z
        else if y <= 240
            z := _lvl == 1 ? 'D' : _lvl == 2 ? 'W' : z
            z
        else if y <= 1440
            z := _lvl == 1 ? 'W' : _lvl == 2 ? 'M' : z
            z
        else if y <= 10080
            z := _lvl == 1 ? 'M' : z
            z
        else
            z := z
            z
    else
        z := _lvl == 1 ? mtf_lvl1 : _lvl == 2 ? mtf_lvl2 : z
        z

    z

//-----------------------
// Mean Reversion Channel Function
//-----------------------
get_mrc() =>
    v_condition = 0
    v_meanline = source
    v_meanrange = supersmoother(ta.tr, length)

    //-- Get Line value
    if type == 'SuperSmoother'
        v_meanline := supersmoother(source, length)
        v_meanline

    if type != 'SuperSmoother'
        v_meanline := SAK_smoothing(type, source, length)
        v_meanline

    v_upband1 = v_meanline + v_meanrange * mult
    v_loband1 = v_meanline - v_meanrange * mult
    v_upband2 = v_meanline + v_meanrange * mult2
    v_loband2 = v_meanline - v_meanrange * mult2

    //-- Check Condition
    if close > v_meanline
        v_upband2_1 = v_upband2 + v_meanrange * gradsize * 4
        v_upband2_9 = v_upband2 + v_meanrange * gradsize * -4
        if high >= v_upband2_9 and high < v_upband2
            v_condition := 1
            v_condition
        else if high >= v_upband2 and high < v_upband2_1
            v_condition := 2
            v_condition
        else if high >= v_upband2_1
            v_condition := 3
            v_condition
        else if close <= v_meanline + v_meanrange
            v_condition := 4
            v_condition
        else
            v_condition := 5
            v_condition

    if close < v_meanline
        v_loband2_1 = v_loband2 - v_meanrange * gradsize * 4
        v_loband2_9 = v_loband2 - v_meanrange * gradsize * -4
        if low <= v_loband2_9 and low > v_loband2
            v_condition := -1
            v_condition
        else if low <= v_loband2 and low > v_loband2_1
            v_condition := -2
            v_condition
        else if low <= v_loband2_1
            v_condition := -3
            v_condition
        else if close >= v_meanline + v_meanrange
            v_condition := -4
            v_condition
        else
            v_condition := -5
            v_condition

    [v_meanline, v_meanrange, v_upband1, v_loband1, v_upband2, v_loband2, v_condition]

//-----------------------
// MTF Analysis
//-----------------------

get_stat(_cond) =>
    ret = 'Price at Mean Line\n'
    if _cond == 1
        ret := 'Overbought (Weak)\n'
        ret
    else if _cond == 2
        ret := 'Overbought\n'
        ret
    else if _cond == 3
        ret := 'Overbought (Strong)\n'
        ret
    else if _cond == 4
        ret := 'Price Near Mean\n'
        ret
    else if _cond == 5
        ret := 'Price Above Mean\n'
        ret
    else if _cond == -1
        ret := 'Oversold (Weak)\n'
        ret
    else if _cond == -2
        ret := 'Oversold\n'
        ret
    else if _cond == -3
        ret := 'Oversold (Strong)\n'
        ret
    else if _cond == -4
        ret := 'Price Near Mean\n'
        ret
    else if _cond == -5
        ret := 'Price Below Mean\n'
        ret
    ret

//-----------------------
// Chart Drawing Function
//-----------------------
format_price(x) =>
    y = str.tostring(x, '0.00000')
    if x > 10
        y := str.tostring(x, '0.000')
        y
    if x > 1000
        y := str.tostring(x, '0.00')
        y
    y

f_PriceLine(_ref, linecol) =>
    line.new(x1=bar_index, x2=bar_index - 1, y1=_ref, y2=_ref, extend=extend.left, color=linecol)

f_MTFLabel(_txt, _yloc) =>
    label.new(x=time + math.round(ta.change(time) * 20), y=_yloc, xloc=xloc.bar_time, text=mtf_disp_typ == 'Always Display' ? _txt : 'Check MTF', tooltip=mtf_disp_typ == 'Always Display' ? '' : _txt, color=color.black, textcolor=color.white, size=size.normal, style=mtf_disp_typ == 'On Hover' and displayline ? label.style_label_lower_left : label.style_label_left, textalign=text.align_left)

//} Function End

//************************************************************************************************************
// Calculate Channel
//************************************************************************************************************
var tf_0 = timeframe.period
var tf_1 = get_tf(1)
var tf_2 = get_tf(2)

[meanline, meanrange, upband1, loband1, upband2, loband2, condition] = get_mrc()
[mtf1_meanline, mtf1_meanrange, mtf1_upband1, mtf1_loband1, mtf1_upband2, mtf1_loband2, mtf1_condition] = request.security(syminfo.tickerid, tf_1, get_mrc())
[mtf2_meanline, mtf2_meanrange, mtf2_upband1, mtf2_loband1, mtf2_upband2, mtf2_loband2, mtf2_condition] = request.security(syminfo.tickerid, tf_2, get_mrc())

//************************************************************************************************************
// Drawing Start {
//************************************************************************************************************
float p_meanline = drawchannel ? meanline : na
float p_upband1 = drawchannel ? upband1 : na
float p_loband1 = drawchannel ? loband1 : na
float p_upband2 = drawchannel ? upband2 : na
float p_loband2 = drawchannel ? loband2 : na

z = plot(p_meanline, color=color.new(#FFCD00, 0), style=plot.style_line, title=' Mean', linewidth=2)
x1 = plot(p_upband1, color=color.new(color.green, 50), style=plot.style_circles, title=' R1', linewidth=1)
x2 = plot(p_loband1, color=color.new(color.green, 50), style=plot.style_circles, title=' S1', linewidth=1)
y1 = plot(p_upband2, color=color.new(color.red, 50), style=plot.style_line, title=' R2', linewidth=1)
y2 = plot(p_loband2, color=color.new(color.red, 50), style=plot.style_line, title=' S2', linewidth=1)

//-----------------------
// Draw zone
//-----------------------
//---
var color1 = #FF0000
var color2 = #FF4200
var color3 = #FF5D00
var color4 = #FF7400
var color5 = #FF9700
var color6 = #FFAE00
var color7 = #FFC500
var color8 = #FFCD00
//---
float upband2_1 = drawchannel and displayzone ? upband2 + meanrange * gradsize * 4 : na
float loband2_1 = drawchannel and displayzone ? loband2 - meanrange * gradsize * 4 : na
float upband2_2 = drawchannel and displayzone ? upband2 + meanrange * gradsize * 3 : na
float loband2_2 = drawchannel and displayzone ? loband2 - meanrange * gradsize * 3 : na
float upband2_3 = drawchannel and displayzone ? upband2 + meanrange * gradsize * 2 : na
float loband2_3 = drawchannel and displayzone ? loband2 - meanrange * gradsize * 2 : na
float upband2_4 = drawchannel and displayzone ? upband2 + meanrange * gradsize * 1 : na
float loband2_4 = drawchannel and displayzone ? loband2 - meanrange * gradsize * 1 : na
float upband2_5 = drawchannel and displayzone ? upband2 + meanrange * gradsize * 0 : na
float loband2_5 = drawchannel and displayzone ? loband2 - meanrange * gradsize * 0 : na
float upband2_6 = drawchannel and displayzone ? upband2 + meanrange * gradsize * -1 : na
float loband2_6 = drawchannel and displayzone ? loband2 - meanrange * gradsize * -1 : na
float upband2_7 = drawchannel and displayzone ? upband2 + meanrange * gradsize * -2 : na
float loband2_7 = drawchannel and displayzone ? loband2 - meanrange * gradsize * -2 : na
float upband2_8 = drawchannel and displayzone ? upband2 + meanrange * gradsize * -3 : na
float loband2_8 = drawchannel and displayzone ? loband2 - meanrange * gradsize * -3 : na
float upband2_9 = drawchannel and displayzone ? upband2 + meanrange * gradsize * -4 : na
float loband2_9 = drawchannel and displayzone ? loband2 - meanrange * gradsize * -4 : na

//---
plot_upband2_1 = plot(upband2_1, color=na, display=display.none, transp=100)
plot_loband2_1 = plot(loband2_1, color=na, display=display.none, transp=100)
plot_upband2_2 = plot(upband2_2, color=na, display=display.none, transp=100)
plot_loband2_2 = plot(loband2_2, color=na, display=display.none, transp=100)
plot_upband2_3 = plot(upband2_3, color=na, display=display.none, transp=100)
plot_loband2_3 = plot(loband2_3, color=na, display=display.none, transp=100)
plot_upband2_4 = plot(upband2_4, color=na, display=display.none, transp=100)
plot_loband2_4 = plot(loband2_4, color=na, display=display.none, transp=100)
plot_upband2_5 = plot(upband2_5, color=na, display=display.none, transp=100)
plot_loband2_5 = plot(loband2_5, color=na, display=display.none, transp=100)
plot_upband2_6 = plot(upband2_6, color=na, display=display.none, transp=100)
plot_loband2_6 = plot(loband2_6, color=na, display=display.none, transp=100)
plot_upband2_7 = plot(upband2_7, color=na, display=display.none, transp=100)
plot_loband2_7 = plot(loband2_7, color=na, display=display.none, transp=100)
plot_upband2_8 = plot(upband2_8, color=na, display=display.none, transp=100)
plot_loband2_8 = plot(loband2_8, color=na, display=display.none, transp=100)
plot_upband2_9 = plot(upband2_9, color=na, display=display.none, transp=100)
plot_loband2_9 = plot(loband2_9, color=na, display=display.none, transp=100)

//---
fill(plot_upband2_1, plot_upband2_2, color=color1, transp=gradtransp)
fill(plot_loband2_1, plot_loband2_2, color=color1, transp=gradtransp)
fill(plot_upband2_2, plot_upband2_3, color=color2, transp=gradtransp)
fill(plot_loband2_2, plot_loband2_3, color=color2, transp=gradtransp)
fill(plot_upband2_3, plot_upband2_4, color=color3, transp=gradtransp)
fill(plot_loband2_3, plot_loband2_4, color=color3, transp=gradtransp)
fill(plot_upband2_4, plot_upband2_5, color=color4, transp=gradtransp)
fill(plot_loband2_4, plot_loband2_5, color=color4, transp=gradtransp)
fill(plot_upband2_5, plot_upband2_6, color=color5, transp=gradtransp)
fill(plot_loband2_5, plot_loband2_6, color=color5, transp=gradtransp)
fill(plot_upband2_6, plot_upband2_7, color=color6, transp=gradtransp)
fill(plot_loband2_6, plot_loband2_7, color=color6, transp=gradtransp)
fill(plot_upband2_7, plot_upband2_8, color=color7, transp=gradtransp)
fill(plot_loband2_7, plot_loband2_8, color=color7, transp=gradtransp)
fill(plot_upband2_8, plot_upband2_9, color=color8, transp=gradtransp)
fill(plot_loband2_8, plot_loband2_9, color=color8, transp=gradtransp)

//-----------------------
// Plot Extension
//-----------------------
if displayline and enable_mtf and mtf_disp_typ == 'Always Display'
    displayline := false
    displayline

var line mean = na
line.delete(mean)
mean := displayline ? f_PriceLine(meanline, #FFCD00) : na
var line res1 = na
line.delete(res1)
res1 := displayline ? f_PriceLine(upband1, color.green) : na
var line sup1 = na
line.delete(sup1)
sup1 := displayline ? f_PriceLine(loband1, color.green) : na
var line res2 = na
line.delete(res2)
res2 := displayline ? f_PriceLine(upband2, color.red) : na
var line sup2 = na
line.delete(sup2)
sup2 := displayline ? f_PriceLine(loband2, color.red) : na

//--------------
// Prep MTF Label
//--------------
var brl = '\n--------------------------------------'
dist_0 = 'Distance from Mean: ' + str.tostring((close - meanline) / close * 100, '#.##') + ' %'
dist_1 = 'Distance from Mean: ' + str.tostring((close - mtf1_meanline) / close * 100, '#.##') + ' %'
dist_2 = 'Distance from Mean: ' + str.tostring((close - mtf2_meanline) / close * 100, '#.##') + ' %'

var title = 'Mean Reversion Channel\nMultiple TimeFrame Analysis' + brl
tf0 = '\n\nTimeframe: ' + tf_0 + ' (Current)\n\nStatus: ' + get_stat(condition) + dist_0 + brl

tf1 = not timeframe.ismonthly ? '\n\nTimeframe: ' + tf_1 + '\n\nStatus: ' + get_stat(mtf1_condition) + dist_1 + brl : ''

tf2 = not timeframe.isweekly and not timeframe.ismonthly ? '\n\nTimeframe: ' + tf_2 + '\n\nStatus: ' + get_stat(mtf2_condition) + dist_2 + brl : ''

mtf_lbl = title + tf0 + tf1 + tf2
var label label_mtf = na
label.delete(label_mtf)
label_mtf := enable_mtf ? f_MTFLabel(mtf_lbl, meanline) : na

//} Drawing End






//22222222222222222222222222222

emaFast = 12
emaSlow = 26
sc = 55
int maxLoopCycles = 300
float closeFastSlowEmaPercentDiffSeries = na
int pivotLowSeries = na
int pivotHighSeries = na
int diffBetweenEmasIsGrowingSeries = na
int diffBetweenEmasIsFallingSeries = na
float g = na
float oe = na
float K = na
float Se = na
float ce = na
float ye = na
float me = na
float Ee = na
float We = na
float ut = na
float et = na
float _t = na
float Rt  = na
float rn  = na
float Qt  = na
float Wt  = na
float cn  = na
float Xt  = na 
float gt  = na
float un = na
bool bn = na
bool z_condition = na
bool J = na
bool fe = na
bool Oe = na
bool le = na
bool _e = na
bool Fe = na
bool ve = na
bool we = na
bool Ae = na
bool Be = na
float closeFastSlowEmaPercentDiffSeriesSmaSeries = na
float closeFastEmaSeries = na
float closeSlowEmaSeries = na
float Klowest = na
float Sehighest = na
 
 
currentBarIndex = bar_index
fi(e, n, i, r, a) =>
    u = array.new_float(0)
    int maxLoop = maxLoopCycles
    if a < maxLoopCycles
        maxLoop := a
    for h = 0 to maxLoop + 1
        if e[h] == 1
            array.unshift(u, math.abs(h+r))
    array.reverse(u)
    if array.size(u) > i
        idx = array.get(u,i)
        n[idx]
    else
        n[0]
 
 
rc(e, n) =>
    int maxLoop = maxLoopCycles
    if n < maxLoopCycles
        maxLoop := n
    int i = 0
    for r = 0 to maxLoop + 1
        if e[r] == 1
            i := math.abs(r+1)
            break
    i            
 
//if bar_index > bar_index - 3000
closeFastEmaSeries := ta.ema(close, emaFast)
closeSlowEmaSeries := ta.ema(close, emaSlow)
closeFastSlowEmaPercentDiffSeries := (closeFastEmaSeries - closeSlowEmaSeries) / closeSlowEmaSeries * 100
closeFastSlowEmaPercentDiffSeriesSmaSeries := ta.sma(closeFastSlowEmaPercentDiffSeries,2)
 
pivotLowSeries := low[0] > low[1] and low[1] < low[2] or low[1] == low[2] and low[1] < low[0] and low[1] < low[3] or low[1] == low[2] and low[1] == low[3] and low[1] < low[0] and (low[1] < low[4] or low[1] == low[2] and low[1] == low[3]) and low[1] and low[1] == low[4] and low[1] < low[0] and low[1] < low[5] ? 1 : 0
pivotHighSeries := high[0] < high[1] and high[1] > high[2] or high[1] == high[2] and high[1] > high[0] and high[1] > high[3] or high[1] == high[2] and high[1] == high[3] and high[1] > high[0] and (high[1] > high[4] or high[1] == high[2] and high[1] == high[3]) and high[1] and high[1] == high[4] and high[1] > high[0] and high[1] > high[5] ? 1 : 0
 
diffBetweenEmasIsGrowingSeries := closeFastSlowEmaPercentDiffSeriesSmaSeries[0] > closeFastSlowEmaPercentDiffSeriesSmaSeries[1] and closeFastSlowEmaPercentDiffSeriesSmaSeries[1] < closeFastSlowEmaPercentDiffSeriesSmaSeries[2] ? 1 : 0
diffBetweenEmasIsFallingSeries := closeFastSlowEmaPercentDiffSeriesSmaSeries[0] < closeFastSlowEmaPercentDiffSeriesSmaSeries[1] and closeFastSlowEmaPercentDiffSeriesSmaSeries[1] > closeFastSlowEmaPercentDiffSeriesSmaSeries[2] ? 1 : 0
g := fi(diffBetweenEmasIsGrowingSeries, closeFastSlowEmaPercentDiffSeriesSmaSeries, 0, 1, currentBarIndex - 1)
oe := fi(diffBetweenEmasIsFallingSeries, closeFastSlowEmaPercentDiffSeriesSmaSeries, 0, 1, currentBarIndex - 1)
K :=  fi(pivotLowSeries, low, 0, 1, currentBarIndex - 1)
Se := fi(pivotHighSeries, high, 0, 1, currentBarIndex - 1)
ce := pivotLowSeries and rc(diffBetweenEmasIsGrowingSeries, currentBarIndex) < 3 ? low[1] : na
ye := pivotHighSeries and rc(diffBetweenEmasIsFallingSeries, currentBarIndex) < 3 ? high[1] : na
Klowest := ta.lowest(K, 4)
Sehighest := ta.highest(Se, 4)
me := rc(pivotLowSeries, currentBarIndex) < 5 ? Klowest : na
Ee := rc(pivotHighSeries, currentBarIndex) < 5 ? Sehighest : na
We := fi(diffBetweenEmasIsFallingSeries, Ee, 1, 0, currentBarIndex - 1)
ut := fi(diffBetweenEmasIsGrowingSeries, me, 1, 0, currentBarIndex - 1)
et := ta.lowest(low, sc)
_t := ta.highest(high, sc)
Rt := fi(pivotLowSeries, et, 1, 0, currentBarIndex - 1)
rn := fi(pivotHighSeries, _t, 1, 0, currentBarIndex - 1)
Qt := fi(diffBetweenEmasIsGrowingSeries, oe, 0, 0, currentBarIndex - 1)
Wt := fi(diffBetweenEmasIsFallingSeries, oe, 1, 0, currentBarIndex - 1)
cn := fi(diffBetweenEmasIsGrowingSeries, g, 0, 0, currentBarIndex - 1)
Xt := fi(diffBetweenEmasIsGrowingSeries, g, 1, 0, currentBarIndex - 1)
gt := fi(diffBetweenEmasIsGrowingSeries, K, 0, 0, currentBarIndex - 1)
un := fi(diffBetweenEmasIsFallingSeries, Se, 0, 0, currentBarIndex - 1)
bn := oe < ta.highest(closeFastSlowEmaPercentDiffSeriesSmaSeries, sc)
z_condition := un > rn
J := ye > rn
fe := g > ta.lowest(closeFastSlowEmaPercentDiffSeriesSmaSeries, sc)
Oe := gt < Rt
le := ce < Rt
 
_e := (gt < ut and diffBetweenEmasIsGrowingSeries and cn > Xt) or (ce < ut and cn > Xt) or (diffBetweenEmasIsGrowingSeries and fe and Oe) or (fe and le)
Fe := (un > We and diffBetweenEmasIsFallingSeries and Qt < Wt) or (ye > We and Qt < Wt) or (diffBetweenEmasIsFallingSeries and bn and z_condition) or (bn and J)
 
ve := not _e
we := not Fe
Ae := _e and ve[1] and ve[2] and ve[3] and ve[4] and ve[5] and ve[6] and ve[7] and ve[8] and ve[9] and ve[10] and ve[11] and ve[12] and ve[13] and ve[14] and ve[15] and ve[16] and ve[17] and ve[18] and ve[19] and ve[20] and ve[21] and ve[22] and ve[23] and ve[24] and ve[25] and ve[26] and ve[27] and ve[28] and ve[29] and ve[30] and ve[31] and ve[32] and ve[33] and ve[34] and ve[35] and ve[36] and ve[37] and ve[38] and ve[39] and ve[40] and ve[41] and ve[42] and ve[43] and ve[44] and ve[45] and ve[46] and ve[47] and ve[48] and ve[49] and ve[50] ? 1 : 0
Be := Fe and we[1] and we[2] and we[3] and we[4] and we[5] and we[6] and we[7] and we[8] and we[9] and we[10] and we[11] and we[12] and we[13] and we[14] and we[15] and we[16] and we[17] and we[18] and we[19] and we[20] and we[21] and we[22] and we[23] and we[24] and we[25] and we[26] and we[27] and we[28] and we[29] and we[30] and we[31] and we[32] and we[33] and we[34] and we[35] and we[36] and we[37] and we[38] and we[39] and we[40] and we[41] and we[42] and we[43] and we[44] and we[45] and we[46] and we[47] and we[48] and we[49] and we[50] ? 1 : 0
 
plotshape(Ae , title="Bull", text="Bull", location=location.belowbar, color = color.green,  style=shape.circle, size=size.small, textcolor = color.green)
plotshape(Be , title="Bear", text="Bear", location=location.abovebar,color =  color.red, style=shape.circle, size=size.small,textcolor = color.red)
plot(Ae ? 1 : Be ? -1 : 0, "Signal", linewidth = 0, display = display.none)

How to Apply Pine Script in TradingView:

1. Open TradingView and log in to your account.
2. Navigate to the Pine Script Editor at the bottom of the screen.
3. Copy the provided Pine Script code.
4. Paste it into the editor.
5. Click Save and provide a descriptive name, such as “Mean Reversion Channel.”
6. Click Add to Chart to apply the indicator to your selected chart.
7. Customize the input settings in the indicator panel to suit your trading style.

Key Features of the Script:

1. Dynamic Mean Reversion Channel:
   • Creates adaptive mean and channel bands using advanced smoothing techniques like Super Smoother, Gaussian, and Butterworth filters.
   • Displays inner and outer bands to highlight overbought and oversold conditions.
2. Multi-Timeframe (MTF) Analysis:
   • Incorporates customizable MTF levels for in-depth analysis of price movements across different timeframes.
   • Displays MTF conditions dynamically based on the current chart resolution.
3. Visual Indicators:
   • Overlays zones with varying transparency to emphasize price proximity to key levels.
   • Highlights overbought and oversold areas with gradient-filled zones and distinct colors for easy identification.
4. Custom Alerts and Conditions:
   • Identifies and signals pivotal market conditions, such as when prices approach or deviate from the mean.
   • Includes automated alerts for bullish and bearish reversals.
5. Additional Analysis Features:
   • Includes pivot detection for highs and lows.
   • Tracks exponential moving averages (EMA) and calculates their percentage differences to identify trends.
6. Flexibility and Customization:
   • Offers full customization of input parameters such as lookback periods, multipliers, and zone transparency.
   • Supports detailed annotations for actionable insights.

Recommended Usage:

1. Trend and Reversal Trading:
   • Utilize the mean reversion channel to identify entry and exit points when the price is overbought or oversold.
   • Leverage multi-timeframe analysis to validate trends and avoid false signals.
2. Day Trading:
   • Use the dynamic channels to identify short-term trading opportunities.
   • Enable MTF analysis for precise decision-making on intraday charts.
3. Risk Management:
   • Monitor channel boundaries to set stop-loss and take-profit levels based on key support and resistance zones.
4. Algorithmic Integration:
   • The script’s alerts can be integrated into automated trading systems for executing trades based on predefined conditions.