Strategi Pelacakan Tren yang Jelas

Penulis:ChaoZhang, Tanggal: 2023-09-28 16:07:12
Tag:

Gambaran umum

Strategi ini menggabungkan beberapa indikator teknis untuk mencapai pelacakan tren yang jelas.

  1. Penilaian tren berdasarkan rata-rata bergerak
  2. Analisis oversold/overbought menggunakan osilator stokastik
  3. Analisis arus dana dengan indikator harga dan volume
  4. Pengukuran kualitas tren menggunakan indeks volatilitas
  5. Deteksi divergensi dengan RSI

Dengan mensintesis sinyal dari indikator-indikator ini, strategi dapat mengidentifikasi tren dengan lebih tepat.

Prinsip

Pertama, rata-rata bergerak dan amplopnya digunakan untuk menentukan arah tren.

Kedua, garis KD dari osilator stokastik digunakan untuk mendeteksi kondisi oversold/overbought, yang biasanya menyiratkan peluang untuk pembalikan.

Kemudian, indikator harga-volume dibangun untuk menganalisis arus dana. Volume yang meningkat mewakili arus masuk modal dan kelanjutan tren, sementara volume yang menurun menunjukkan arus keluar modal dan pembalikan tren.

Untuk mengukur kualitas tren, indeks volatilitas dibangun dari kisaran harga rata-rata, dan EMAnya mengukur kekuatan tren.

Akhirnya, perbedaan antara harga dan RSI juga dapat menunjukkan pembalikan tren yang akan datang.

Dengan menggabungkan semua sinyal ini, tren dapat diidentifikasi dengan lebih tepat. strategi akan pergi panjang ketika golden cross antara MAs muncul, dan pergi pendek ketika mati cross terjadi.

Keuntungan

  • Pengurangan kebisingan dan sinyal yang lebih jelas menggunakan beberapa indikator
  • Analisis oversold/overbought memberikan waktu pembalikan yang baik
  • Analisis volume mencegah pecah palsu
  • Indeks volatilitas mengukur kualitas tren untuk menghindari ketegangan
  • Perbedaan RSI menawarkan sinyal pembalikan tambahan
  • Struktur kode yang bersih, mudah dimengerti dan dimodifikasi

Risiko

  • Konflik sinyal dapat terjadi ketika menggabungkan beberapa indikator, yang membutuhkan penyesuaian parameter yang cermat
  • Volume yang meningkat juga bisa dimanipulasi, penilaian yang bijaksana diperlukan
  • Parameter RSI mungkin perlu disesuaikan untuk produk yang berbeda
  • Whipsaws dan sinyal yang salah sering terjadi selama pasar berkisar
  • Kinerja indikator dapat memburuk di pasar yang tidak efisien

Manajemen risiko:

  • Meningkatkan optimasi parameter untuk perilaku indikator yang tepat
  • Mengkonfigurasi bobot indikator untuk menyelesaikan konflik
  • Sesuaikan parameter berdasarkan karakteristik produk
  • Meningkatkan ukuran posisi untuk mengurangi perdagangan yang berlebihan
  • Memverifikasi kinerja melalui backtesting dan perdagangan kertas

Optimisasi

Strategi ini dapat ditingkatkan dalam hal berikut:

  1. Menggunakan pembelajaran mesin untuk menyesuaikan parameter otomatis untuk produk yang berbeda

  2. Tambahkan evaluasi model untuk menyesuaikan secara dinamis bobot indikator berdasarkan kondisi pasar

  3. Mengimplementasikan stop loss adaptif berdasarkan volatilitas pasar

  4. Masukkan pembelajaran mendalam untuk prediksi tren yang lebih akurat

  5. Membangun rekonsiliasi sinyal otomatis untuk menyelesaikan konflik dan mengurangi sinyal palsu

  6. Mengintegrasikan lebih banyak indikator untuk prediksi sistem ensemble

  7. Jelajahi indikator tanpa parameter untuk mengurangi ketergantungan parameter

Kesimpulan

Strategi ini memanfaatkan beberapa indikator teknis untuk mencapai identifikasi tren yang relatif kuat, dengan potensi aplikasi yang menjanjikan. Namun, akurasi dan manajemen risiko membutuhkan perbaikan terus-menerus sebelum perdagangan langsung yang stabil. Optimasi di masa depan dapat menggabungkan pembelajaran mesin dan teknik lain untuk memungkinkan otomatisasi cerdas.


/*backtest
start: 2022-09-21 00:00:00
end: 2023-09-27 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=3
//Market Cipher Update 2 - updated 8th Oct 2019

//Momentum Curves with green and red dots
strategy(title="MarketCipher B", shorttitle="MarketCipher B")
n1 = input(9, "Channel Length")
n2 = input(12, "Average Length")
obLevel1 = input(60, "Over Bought Level 1")
obLevel2 = input(53, "Over Bought Level 2")
osLevel1 = input(-60, "Over Sold Level 1")
osLevel2 = input(-53, "Over Sold Level 2")
osLevel3 = input(-100, "Over Sold Level 2")

 
ap = hlc3 
esa = ema(ap, n1)
d = ema(abs(ap - esa), n1)
ci = (ap - esa) / (0.015 * d)
tci = ema(ci, n2)
 
wt1 = tci
wt2 = sma(wt1,3)

plot(0, color=gray, title="Zero Line")
plot(obLevel1, color=red, style=3, title="Bottom")
plot(osLevel1, color=green, style=3, title="Top")
plot(wt1, color=#BFE4FF, style=4, title= "Lt Blue Wave")
plot(wt2, color=#673ab7, style=4, title="Blue Wave", transp=40)
plot(wt1-wt2, color=yellow, style=4, transp=40, title="wave1-wave2")

//green dots and crosses
plotshape(crossover(wt1, wt2) and osLevel1 ? wt2 : na, title="Pos Crossover", location=location.absolute, style=shape.cross, size=size.tiny, color=#3FFF00, transp=20)
plotshape(crossover(wt2, wt1) and osLevel1 ? wt1 : na, title="Neg Crossover", location=location.absolute, style=shape.cross, size=size.tiny, color=red, transp=20)
plotshape(crossover(wt1, wt2) and wt2 < -59 ? wt2 : na, title="Pos Crossover", location=location.bottom, style=shape.circle, size=size.tiny, color=#3FFF00, transp=20)
plotshape(crossover(wt2, wt1) and wt1 > 59 ? wt2 : na, title="Neg Crossover", location=location.top, style=shape.circle, size=size.tiny, color=red, transp=20)

buy= crossover(wt1,wt2) // Define our buy/sell conditions, using pine inbuilt functions.
sell= crossover(wt2,wt1)
ordersize=floor(strategy.equity/close) // To dynamically calculate the order size as the account equity increases or decreases.
strategy.entry("long",strategy.long,ordersize,when=buy) // Buys when buy condition met
strategy.close("long", when = sell ) // Closes position when sell condition met
strategy.entry("short",strategy.short,ordersize,when=sell)
strategy.close("short",when = buy )

//soch RSI with divergences
smoothKw = input(3, minval=1)
smoothDw = input(3, minval=1)
lengthRSIw = input(14, minval=1)
lengthStochw = input(14, minval=1)
uselogw = input(true, title="Log")
srcInw = input(close,  title="Source")
showdivsw = input(true, title="Show Divergences")
showhiddenw = input(false, title="Show Hidden Divergences")
showchanw = input(false, title="Show Divergences Channel")


srcw = uselogw ? log(srcInw) : srcInw
rsi1w = rsi(srcw, lengthRSIw)
kkw = sma(stoch(rsi1w, rsi1w, rsi1w, lengthStochw), smoothKw)
dw = sma(kkw, smoothDw)
hmw = input(false, title="Use Average of both K & D")
kw = hmw ? avg(kkw, dw) : kkw

aw = plot(kkw, color=blue, linewidth=1, transp=0, title="K")
bw = plot(dw, color=orange, linewidth=1, transp=0, title="D")
fw = kkw >= dw ? blue : orange
fill(aw, bw, title="KD Fill", color=white)


//------------------------------
//@RicardoSantos' Divergence Script

f_top_fractal(_src)=>_src[4] < _src[2] and _src[3] < _src[2] and _src[2] > _src[1] and _src[2] > _src[0]
f_bot_fractal(_src)=>_src[4] > _src[2] and _src[3] > _src[2] and _src[2] < _src[1] and _src[2] < _src[0]
f_fractalize(_src)=>f_top_fractal(_src) ? 1 : f_bot_fractal(_src) ? -1 : 0
//-------------------------
fractal_top = f_fractalize(kw) > 0 ? kw[2] : na
fractal_bot = f_fractalize(kw) < 0 ? kw[2] : na

high_prev = valuewhen(fractal_top, kw[2], 0)[2]
high_price = valuewhen(fractal_top, high[2], 0)[2]
low_prev = valuewhen(fractal_bot, kw[2], 0)[2]
low_price = valuewhen(fractal_bot, low[2], 0)[2]

regular_bearish_diva = fractal_top and high[2] > high_price and kw[2] < high_prev
hidden_bearish_diva = fractal_top and high[2] < high_price and kw[2] > high_prev
regular_bullish_diva = fractal_bot and low[2] < low_price and kw[2] > low_prev
hidden_bullish_diva = fractal_bot and low[2] > low_price and kw[2] < low_prev
//-------------------------
plot(showchanw?fractal_top:na, title="Top Div Channel", offset=-2, color=gray)
plot(showchanw?fractal_bot:na, title="Bottom Div Channel", offset=-2, color=gray)

col1 = regular_bearish_diva ? red : hidden_bearish_diva and showhiddenw ? red : na
col2 = regular_bullish_diva ? green : hidden_bullish_diva and showhiddenw ? green : na
col3 = regular_bearish_diva ? red : hidden_bearish_diva and showhiddenw ? red : showchanw ? gray : na
col4 = regular_bullish_diva ? green : hidden_bullish_diva and showhiddenw ? green : showchanw ? gray : na

plot(title='H F', series=showdivsw and fractal_top ? kw[2] : na, color=col1, linewidth=2, offset=-2)
plot(title='L F', series=showdivsw and fractal_bot ? kw[2] : na, color=col2, linewidth=2, offset=-2)
plot(title='H D', series=showdivsw and fractal_top ? kw[2] : na, style=circles, color=col3, linewidth=3, offset=-2)
plot(title='L D', series=showdivsw and fractal_bot ? kw[2] : na, style=circles, color=col4, linewidth=3, offset=-2)

plotshape(title='+RBD', series=showdivsw and regular_bearish_diva ? kw[2] : na, text='R', style=shape.labeldown, location=location.absolute, color=red, textcolor=white, offset=-2)
plotshape(title='+HBD', series=showdivsw and hidden_bearish_diva and showhiddenw ? kw[2] : na, text='H', style=shape.labeldown, location=location.absolute, color=red, textcolor=white, offset=-2)
plotshape(title='-RBD', series=showdivsw and regular_bullish_diva ? kw[2] : na, text='R', style=shape.labelup, location=location.absolute, color=green, textcolor=white, offset=-2)
plotshape(title='-HBD', series=showdivsw and hidden_bullish_diva  and showhiddenw ? kw[2] : na, text='H', style=shape.labelup, location=location.absolute, color=green, textcolor=white, offset=-2)


//money flow
colorRed = #ff0000
colorGreen = #03ff00

ma(matype, src, length) =>
    if matype == "RMA"
        rma(src, length)
    else
        if matype == "SMA"
            sma(src, length)
        else
            if matype == "EMA"
                ema(src, length)
            else
                if matype == "WMA"
                    wma(src, length)
                else
                    if matype == "VWMA"
                        vwma(src, length)
                    else
                        src

rsiMFIperiod = input(60, "RSI+MFI Period")
rsiMFIMultiplier = input(190, "RSI+MFI Area multiplier")
MFRSIMA = input(defval="SMA", title="MFRSIMA", options=["RMA", "SMA", "EMA", "WMA", "VWMA"])

candleValue = (close - open) / (high - low)
MVC = ma(MFRSIMA, candleValue, rsiMFIperiod)
color_area = MVC > 0 ? green : red

RSIMFIplot = plot(MVC * rsiMFIMultiplier, title="RSI+MFI Area", color=color_area, transp=35)
fill(RSIMFIplot, plot(0), color_area, transp=50)

//rsi
//Bullish Divergence (green triangle)
//Hidden Bullish Divergence (green circle)
//Bearish Divergence (red triangle)
//Hidden Bearish Divergence (red circle)

lend = 14
bearish_div_rsi = input(60, "Min Bearish RSI",  minval=50, maxval=100)
bullish_div_rsi = input(40, "Max Bullish RSI",  minval=0, maxval=50)

// RSI code
rsi = rsi(close, lend)
plot(rsi,  color=#6DFFE1, linewidth=2, transp=0, title="RSI")

// DIVS code
xbars = 60
hb = abs(highestbars(rsi, xbars)) // Finds bar with highest value in last X bars
lb = abs(lowestbars(rsi, xbars)) // Finds bar with lowest value in last X bars

// Defining variable values, mandatory in Pine 3
max = na
max_rsi = na
min = na
min_rsi = na
bearish_div = na
bullish_div = na
hidden_bearish_div = na
hidden_bullish_div = na
div_alert = na
hidden_div_alert = na

// If bar with lowest / highest is current bar, use it's value
max := hb == 0 ? close : na(max[1]) ? close : max[1]
max_rsi := hb == 0 ? rsi : na(max_rsi[1]) ? rsi : max_rsi[1]
min := lb == 0 ? close : na(min[1]) ? close : min[1]
min_rsi := lb == 0 ? rsi : na(min_rsi[1]) ? rsi : min_rsi[1]

// Compare high of current bar being examined with previous bar's high
// If curr bar high is higher than the max bar high in the lookback window range
if close > max // we have a new high
    max := close // change variable "max" to use current bar's high value
if rsi > max_rsi // we have a new high
    max_rsi := rsi // change variable "max_rsi" to use current bar's RSI value
if close < min // we have a new low
    min := close // change variable "min" to use current bar's low value
if rsi < min_rsi // we have a new low
    min_rsi := rsi // change variable "min_rsi" to use current bar's RSI value

// Detects divergences between price and indicator with 1 candle delay so it filters out repeating divergences
if (max[1] > max[2]) and (rsi[1] < max_rsi) and (rsi <= rsi[1]) and (rsi[1] >= bearish_div_rsi)
    bearish_div := true
	div_alert := true
if (min[1] < min[2]) and (rsi[1] > min_rsi) and (rsi >= rsi[1]) and (rsi[1] <= bullish_div_rsi)
    bullish_div := true
	div_alert := true
// Hidden divergences
if (max[1] < max[2]) and (rsi[1] < max_rsi)
	hidden_bearish_div := true
	hidden_div_alert := true
if (min[1] > min[2]) and (rsi[1] > min_rsi)
	hidden_bullish_div := true
	hidden_div_alert := true
// Alerts
alertcondition(div_alert, title='RSI Divergence', message='RSI Divergence')
alertcondition(hidden_div_alert, title='Hidden RSI Divergence', message='Hidden RSI Divergence')

// Plots divergences with offest
plotshape((bearish_div ? rsi[1] + 3 : na), location=location.absolute, style=shape.diamond, color=#ff0000, size=size.tiny, transp=0, offset=0, title="RSI Bear Div")
plotshape((bullish_div ? rsi[1] - 3 : na), location=location.absolute, style=shape.diamond, color=#00ff01, size=size.tiny, transp=0, offset=0, title="RSI Bull Div")
plotshape((hidden_bearish_div ? rsi[1] + 3 : na), location=location.absolute, style=shape.circle, color=#ff0000, size=size.tiny, transp=0, offset=0, title="RSI Bear hDiv")
plotshape((hidden_bullish_div ? rsi[1] - 3 : na), location=location.absolute, style=shape.circle, color=#00ff01, size=size.tiny, transp=0, offset=0, title="RSI Bull hDiv")


//wave divergences
WTCross = cross(wt1, wt2)
WTCrossUp = wt2 - wt1 <= 0
WTCrossDown = wt2 - wt1 >= 0
WTFractal_top = f_fractalize(wt1) > 0 and wt1[2] ? wt1[2] : na
WTFractal_bot = f_fractalize(wt1) < 0 and wt1[2] ? wt1[2] : na

WTHigh_prev  = valuewhen(WTFractal_top, wt1[2], 0)[2]
WTHigh_price = valuewhen(WTFractal_top, high[2], 0)[2]
WTLow_prev  = valuewhen(WTFractal_bot, wt1, 0)[2]
WTLow_price  = valuewhen(WTFractal_bot, low[2], 0)[2]

WTRegular_bearish_div = WTFractal_top and high[2] > WTHigh_price and wt1[2] < WTHigh_prev
WTRegular_bullish_div = WTFractal_bot and low[2] < WTLow_price and wt1[2] > WTLow_prev

bearWTSignal = WTRegular_bearish_div and WTCrossDown
bullWTSignal = WTRegular_bullish_div and WTCrossUp

WTCol1 = bearWTSignal ? #ff0000 : na
WTCol2 = bullWTSignal ? #00FF00EB : na

plot(series = WTFractal_top ? wt1[2] : na, title='Bearish Divergence', color=WTCol1, linewidth=5, transp=60)
plot(series = WTFractal_bot ? wt1[2] : na, title='Bullish Divergence', color=WTCol2, linewidth=5, transp=60)


//2nd wave
WTFractal_topa = f_fractalize(wt2) > 0 and wt2[2] ? wt2[2] : na
WTFractal_bota = f_fractalize(wt2) < 0 and wt2[2] ? wt2[2] : na

WTHigh_preva  = valuewhen(WTFractal_topa, wt2[2], 0)[2]
WTHigh_pricea = valuewhen(WTFractal_topa, high[2], 0)[2]
WTLow_preva  = valuewhen(WTFractal_bota, wt2, 0)[2]
WTLow_pricea  = valuewhen(WTFractal_bota, low[2], 0)[2]


WTRegular_bearish_diva = WTFractal_topa and high[2] > WTHigh_pricea and wt2[2] < WTHigh_preva
WTRegular_bullish_diva = WTFractal_bota and low[2] < WTLow_pricea and wt2[2] > WTLow_preva

bearWTSignala = WTRegular_bearish_diva and WTCrossDown
bullWTSignala = WTRegular_bullish_diva and WTCrossUp

WTCol1a = bearWTSignala ? #ff0000 : na
WTCol2a = bullWTSignala ? #00FF00EB : na

plot(series = WTFractal_topa ? wt2[2] : na, title='Bearish Divergence', color=WTCol1a, linewidth=5, transp=60)
plot(series = WTFractal_bota ? wt2[2] : na, title='Bullish Divergence', color=WTCol2a, linewidth=5, transp=60)


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