Strategi Mengikuti Tren yang Jelas


Tanggal Pembuatan: 2023-09-28 16:07:12 Akhirnya memodifikasi: 2023-09-28 16:07:12
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Ringkasan

Strategi ini menggabungkan berbagai indikator teknis untuk melacak tren dengan jelas. Strategi ini terdiri dari beberapa bagian:

  1. Penghakiman tren berdasarkan rata-rata
  2. Penilaian overbought dan oversold berdasarkan indikator acak
  3. Perhitungan aliran dana berdasarkan indikator harga
  4. Penilaian kualitas tren berdasarkan indikator fluktuasi
  5. Pengadilan deviasi berdasarkan RSI

Prinsip

Strategi ini pertama-tama menilai arah tren harga melalui garis rata-rata. Secara khusus, menghitung rata-rata harga dalam periode tertentu, dan saluran pita dari rata-rata ini. Saluran harga yang pecah menunjukkan kemungkinan pembalikan tren.

Kemudian digabungkan dengan indikator KD dalam indikator acak untuk menentukan apakah harga berada dalam kondisi overbought atau oversold.

Kemudian, informasi volume transaksi digunakan untuk menentukan arus masuk dan arus keluar dana dengan membangun indikator volume harga. Kenaikan volume menunjukkan arus masuk dana dan perkembangan tren, sedangkan penurunan volume berarti arus keluar dana dan pembalikan tren.

Untuk menilai kualitas tren, gunakan rentang fluktuasi harga rata-rata untuk membangun indeks data pasar, kemudian hitung EMA untuk menilai kekuatan tren. Dengan demikian, beberapa tren palsu dapat disaring.

Akhirnya, indikator RSI dapat digunakan untuk mendeteksi harga dan defisit fluktuasi, yang juga sering menandakan pembalikan tren yang akan datang.

Informasi dari indikator-indikator ini dapat digunakan untuk menilai tren harga dengan lebih jelas. Strategi ini akan membangun posisi multihead ketika terjadi persilangan emas di garis rata dan posisi kosong ketika terjadi persilangan mati.

Keunggulan

  • Pengadilan Komprehensif Multi-Indikator, memfilter kebisingan, membuat penilaian tren lebih jelas dan lebih dapat diandalkan
  • Jika Anda bergabung dengan penilaian overbought dan oversold, Anda dapat menentukan titik waktu untuk berbalik.
  • Indikator kuantitatif untuk mengevaluasi aliran dana dan menghindari terobosan palsu
  • Indikator oscillasi mengukur kualitas tren, mencegah tertipu oleh getaran skala kecil
  • RSI bergeser untuk memberikan sinyal reversal tren tambahan
  • Struktur kode yang jelas, mudah dipahami dan dimodifikasi

Risiko

  • Pertimbangan yang digabungkan dengan indikator-indikator dapat menyebabkan konflik sinyal, dan perlu diperhatikan.
  • Kecanduan juga bisa disebabkan oleh permainan uang, hati-hati
  • Beberapa indikator seperti RSI perlu disesuaikan dengan parameter yang berbeda
  • Guncangan kecil dapat menyebabkan sinyal yang salah
  • Efek dari indikator pasar yang tidak efisien akan dikurangi

Tindakan pencegahan risiko:

  • Meningkatkan penyesuaian parameter untuk memastikan indikator bekerja dengan baik
  • Menambahkan berat indeks, menangani konflik sinyal
  • Parameter disesuaikan dengan karakteristik varietas yang berbeda
  • Meningkatkan persentase kepemilikan, mengurangi frekuensi transaksi
  • Menggunakan efek validasi simulasi disk nyata

Arah optimasi

Strategi ini dapat dioptimalkan dalam beberapa hal:

  1. Mengoptimalkan parameter secara otomatis menggunakan metode pembelajaran mesin untuk membuat indikator lebih sesuai dengan karakteristik varietas yang berbeda

  2. Menambahkan modul penilaian model, menyesuaikan bobot masing-masing indikator sesuai dengan dinamika fase pasar yang berbeda

  3. Menambahkan strategi stop loss adaptif yang memungkinkan penyesuaian stop loss sesuai dengan volatilitas pasar

  4. Menggunakan Deep Learning untuk mengekstrak lebih banyak karakteristik dan memberikan penilaian tren yang lebih akurat

  5. Mengembangkan modul penyesuaian sinyal otomatis untuk menangani konflik indikator dan situasi yang mudah menimbulkan sinyal yang salah

  6. Menambahkan model terpadu, mengintegrasikan lebih banyak penilaian indikator teknis, dan menghasilkan hasil prediksi yang sistematis

  7. Menjelajahi indikator tanpa parameter, mengurangi ketergantungan indikator pada parameter

Meringkaskan

Strategi ini dengan mengintegrasikan kekuatan berbagai indikator teknis, menilai tren harga secara komprehensif, memiliki keunggulan dan prospek aplikasi di bidang strategi penilaian tren. Namun, masih perlu terus dioptimalkan untuk meningkatkan akurasi penilaian dan mengurangi risiko kesalahan penilaian, agar dapat beroperasi secara stabil di dunia nyata. Di masa depan, teknologi seperti pembelajaran mesin dapat diperkenalkan lebih lanjut untuk peningkatan kecerdasan.

Kode Sumber Strategi
/*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)