
Cette stratégie combine une analyse de séquence temporelle, des prix moyens pondérés en volume de transactions, des bandes de Bryn et des quatre indicateurs techniques delta (OBV-PVT) pour permettre une évaluation multidimensionnelle de la tendance des prix, des surachats et des survente.
Il est possible d’optimiser les stratégies en ajustant la périodicité de la moyenne, l’amplitude de la bande de Brin et le ratio de risque/perte, afin de réduire la fréquence des transactions et d’augmenter le ratio de perte d’une seule transaction.
Cette stratégie utilise une combinaison de plusieurs outils d’analyse, tels que la décomposition de la séquence temporelle, l’indicateur des bandes de Brin et l’indicateur OBV, pour identifier efficacement les principales tendances du marché grâce à une combinaison organique de relations quantitatives, de caractéristiques statistiques et de jugements de tendances. Il existe également un certain risque, qui doit être ajusté par des paramètres pour atteindre l’état optimal.
/*backtest
start: 2023-10-24 00:00:00
end: 2023-11-23 00:00:00
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/
// This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
//// This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © oakwhiz and tathal
//@version=4
strategy("BBPBΔ(OBV-PVT)BB", default_qty_type=strategy.percent_of_equity, default_qty_value=100)
startDate = input(title="Start Date", type=input.integer,
defval=1, minval=1, maxval=31)
startMonth = input(title="Start Month", type=input.integer,
defval=1, minval=1, maxval=12)
startYear = input(title="Start Year", type=input.integer,
defval=2010, minval=1800, maxval=2100)
endDate = input(title="End Date", type=input.integer,
defval=31, minval=1, maxval=31)
endMonth = input(title="End Month", type=input.integer,
defval=12, minval=1, maxval=12)
endYear = input(title="End Year", type=input.integer,
defval=2021, minval=1800, maxval=2100)
// Normalize Function
normalize(_src, _min, _max) =>
// Normalizes series with unknown min/max using historical min/max.
// _src : series to rescale.
// _min, _min: min/max values of rescaled series.
var _historicMin = 10e10
var _historicMax = -10e10
_historicMin := min(nz(_src, _historicMin), _historicMin)
_historicMax := max(nz(_src, _historicMax), _historicMax)
_min + (_max - _min) * (_src - _historicMin) / max(_historicMax - _historicMin, 10e-10)
// STEP 2:
// Look if the close time of the current bar
// falls inside the date range
inDateRange = true
// Stop loss & Take Profit Section
sl_inp = input(2.0, title='Stop Loss %')/100
tp_inp = input(4.0, title='Take Profit %')/100
stop_level = strategy.position_avg_price * (1 - sl_inp)
take_level = strategy.position_avg_price * (1 + tp_inp)
icreturn = false
innercandle = if (high < high[1]) and (low > low[1])
icreturn := true
src = close
float change_src = change(src)
float i_obv = cum(change_src > 0 ? volume : change_src < 0 ? -volume : 0*volume)
float i_pvt = pvt
float result = change(i_obv - i_pvt)
float nresult = ema(normalize(result, -1, 1), 20)
length = input(20, minval=1)
mult = input(2.0, minval=0.001, maxval=50, title="StdDev")
basis = ema(nresult, length)
dev = mult * stdev(nresult, length)
upper = basis + dev
lower = basis - dev
bbr = (nresult - lower)/(upper - lower)
////////////////INPUTS///////////////////
lambda = input(defval = 1000, type = input.float, title = "Smoothing Factor (Lambda)", minval = 1)
leng = input(defval = 100, type = input.integer, title = "Filter Length", minval = 1)
srcc = close
///////////Construct Arrays///////////////
a = array.new_float(leng, 0.0)
b = array.new_float(leng, 0.0)
c = array.new_float(leng, 0.0)
d = array.new_float(leng, 0.0)
e = array.new_float(leng, 0.0)
f = array.new_float(leng, 0.0)
/////////Initialize the Values///////////
//for more details visit:
// https://asmquantmacro.com/2015/06/25/hodrick-prescott-filter-in-excel/
ll1 = leng-1
ll2 = leng-2
for i = 0 to ll1
array.set(a,i, lambda*(-4))
array.set(b,i, src[i])
array.set(c,i, lambda*(-4))
array.set(d,i, lambda*6 + 1)
array.set(e,i, lambda)
array.set(f,i, lambda)
array.set(d, 0, lambda + 1.0)
array.set(d, ll1, lambda + 1.0)
array.set(d, 1, lambda * 5.0 + 1.0)
array.set(d, ll2, lambda * 5.0 + 1.0)
array.set(c, 0 , lambda * (-2.0))
array.set(c, ll2, lambda * (-2.0))
array.set(a, 0 , lambda * (-2.0))
array.set(a, ll2, lambda * (-2.0))
//////////////Solve the optimization issue/////////////////////
float r = array.get(a, 0)
float s = array.get(a, 1)
float t = array.get(e, 0)
float xmult = 0.0
for i = 1 to ll2
xmult := r / array.get(d, i-1)
array.set(d, i, array.get(d, i) - xmult * array.get(c, i-1))
array.set(c, i, array.get(c, i) - xmult * array.get(f, i-1))
array.set(b, i, array.get(b, i) - xmult * array.get(b, i-1))
xmult := t / array.get(d, i-1)
r := s - xmult*array.get(c, i-1)
array.set(d, i+1, array.get(d, i+1) - xmult * array.get(f, i-1))
array.set(b, i+1, array.get(b, i+1) - xmult * array.get(b, i-1))
s := array.get(a, i+1)
t := array.get(e, i)
xmult := r / array.get(d, ll2)
array.set(d, ll1, array.get(d, ll1) - xmult * array.get(c, ll2))
x = array.new_float(leng, 0)
array.set(x, ll1, (array.get(b, ll1) - xmult * array.get(b, ll2)) / array.get(d, ll1))
array.set(x, ll2, (array.get(b, ll2) - array.get(c, ll2) * array.get(x, ll1)) / array.get(d, ll2))
for j = 0 to leng-3
i = leng-3 - j
array.set(x, i, (array.get(b,i) - array.get(f,i)*array.get(x,i+2) - array.get(c,i)*array.get(x,i+1)) / array.get(d, i))
//////////////Construct the output///////////////////
o5 = array.get(x,0)
////////////////////Plottingd///////////////////////
TimeFrame = input('1', type=input.resolution)
start = security(syminfo.tickerid, TimeFrame, time)
//------------------------------------------------
newSession = iff(change(start), 1, 0)
//------------------------------------------------
vwapsum = 0.0
vwapsum := iff(newSession, o5*volume, vwapsum[1]+o5*volume)
volumesum = 0.0
volumesum := iff(newSession, volume, volumesum[1]+volume)
v2sum = 0.0
v2sum := iff(newSession, volume*o5*o5, v2sum[1]+volume*o5*o5)
myvwap = vwapsum/volumesum
dev2 = sqrt(max(v2sum/volumesum - myvwap*myvwap, 0))
Coloring=close>myvwap?color.green:color.red
av=myvwap
showBcol = input(false, type=input.bool, title="Show barcolors")
showPrevVWAP = input(false, type=input.bool, title="Show previous VWAP close")
prevwap = 0.0
prevwap := iff(newSession, myvwap[1], prevwap[1])
nprevwap= normalize(prevwap, 0, 1)
l1= input(20, minval=1)
src2 = close
mult1 = input(2.0, minval=0.001, maxval=50, title="StdDev")
basis1 = sma(src2, l1)
dev1 = mult1 * stdev(src2, l1)
upper1 = basis1 + dev1
lower1 = basis1 - dev1
bbr1 = (src - lower1)/(upper1 - lower1)
az = plot(bbr, "Δ(OBV-PVT)", color.rgb(0,153,0,0), style=plot.style_columns)
bz = plot(bbr1, "BB%B", color.rgb(0,125,125,50), style=plot.style_columns)
fill(az, bz, color=color.white)
deltabbr = bbr1 - bbr
oneline = hline(1)
twoline = hline(1.2)
zline = hline(0)
xx = input(.3)
yy = input(.7)
zz = input(-1)
xxx = hline(xx)
yyy = hline(yy)
zzz = hline(zz)
fill(oneline, twoline, color=color.red, title="Sell Zone")
fill(yyy, oneline, color=color.orange, title="Slightly Overbought")
fill(yyy, zline, color=color.white, title="DO NOTHING ZONE")
fill(zzz, zline, color=color.green, title="GO LONG ZONE")
l20 = crossover(deltabbr, 0)
l30 = crossunder(deltabbr, 0)
l40 = crossover(o5, 0)
l50 = crossunder(o5, 0)
z1 = bbr1 >= 1
z2 = bbr1 < 1 and bbr1 >= .7
z3 = bbr1 < .7 and bbr1 >= .3
z4 = bbr1 < .3 and bbr1 >= 0
z5 = bbr1 < 0
a1 = bbr >= 1
a2 = bbr < 1 and bbr >= .7
a4 = bbr < .3 and bbr >= 0
a5 = bbr < 0
b4 = deltabbr < .3 and deltabbr >= 0
b5 = deltabbr < 0
c4 = o5 < .3 and o5 >= 0
c5 = o5 < 0
b1 = deltabbr >= 1
b2 = deltabbr < 1 and o5 >= .7
c1 = o5 >= 1
c2 = o5 < 1 and o5 >= .7
///
n = input(16,"Period")
H = highest(hl2,n)
L = lowest(hl2,n)
hi = H[1]
lo = L[1]
up = high>hi
dn = low<lo
lowerbbh = lowest(10)[1]
bbh = (low == open ? open < lowerbbh ? open < close ? close > ((high[1] - low[1]) / 2) + low[1] :na : na : na)
plot(normalize(av,-1,1), linewidth=2, title="Trendline", color=color.yellow)
long5 = close < av and av[0] > av[1]
sell5 = close > av
cancel = false
if open >= high[1]
cancel = true
long = (long5 or z5 or a5) and (icreturn or bbh or up)
sell = ((z1 or a1) or (l40 and l20)) and (icreturn or dn) and (c1 or b1)
short = ((z1 or z2 or a1 or sell5) and (l40 or l20)) and icreturn
buy= (z5 or z4 or a5 or long5) and (icreturn or dn)
plotshape(long and not sell ? -0.5 : na, title="Long", location=location.absolute, style=shape.circle, size=size.tiny, color=color.green, transp=0)
plotshape(short and not sell? 1 : na, title="Short", location=location.absolute, style=shape.circle, size=size.tiny, color=color.red, transp=0)
if (inDateRange)
strategy.entry("long", true, when = long )
if (inDateRange) and (strategy.position_size > 0)
strategy.close_all(when = sell or cancel)
if (inDateRange)
strategy.entry("short", false, when = short )
if (inDateRange) and (strategy.position_size < 0)
strategy.close_all(when = buy)