ChaoZhang
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Pengikut
Ringkasan
Strategi ini adalah sistem pelacakan tren yang menggabungkan indikator indeks variabel rata-rata dinamis (VIDYA) dengan pita Bollinger (Bollinger Bands) dan mengintegrasikan mekanisme stop-loss multi-lapisan. Berbeda dengan strategi tren tradisional, sistem ini menggunakan metode pengembalian yang lebih adaptif untuk membedakan posisi kosong dengan basis ATR dan target persentase yang unik. Inovasi dalam strategi ini adalah penggunaan metode stop-loss multi-lapisan dinamis, terutama untuk perdagangan kosong dengan perkalian persentase yang lebih radikal, yang memberikan fleksibilitas untuk mengoptimalkan manajemen perdagangan dan distribusi keuntungan berdasarkan volatilitas pasar dan kekuatan tren.
Prinsip Strategi
Inti dari strategi ini adalah dengan menggunakan dua indikator VIDYA cepat dan lambat untuk menganalisis tren harga, dengan mempertimbangkan volatilitas pasar. Rumus perhitungan indikator VIDYA adalah: Faktor kelancaran (α) = 2/ (periode + 1) VIDYA (t) = α * k * harga (t) + (1 - α * k) * VIDYA (t-1) di mana k = Chand dinamika osilator MO 100
Blinking Band sebagai Filter Tingkat Fluktuasi: Jalur atas = MA + (K * standard deviasi) Jalur bawah = MA - (K * standar deviasi)
Syarat masuk:
- Multi Head: Harga menembus slow Vidia dan fast Vidia naik, sementara harga menembus Brin berbaris
- Blank: Harga turun di bawah slowVIDYA dan fastVIDYA turun ke bawah, sementara harga turun di bawah Brin Belt
Sistem multi-layer suspensi meliputi:
- ATR-based stop
- Penutupan berdasarkan persentase
- Perdagangan kosong menggunakan perkalian untuk meningkatkan rasio stop loss
Keunggulan Strategis
- Adaptasi dinamis: Indeks VIDA dapat menyesuaikan diri secara otomatis dengan fluktuasi pasar, lebih sensitif daripada garis rata-rata tradisional
- Manajemen risiko yang sempurna: mekanisme multi-layer yang dapat mengunci keuntungan pada tingkat harga yang berbeda
- Proses diferensiasi: Strategi penghentian yang berbeda untuk posisi kosong, lebih sesuai dengan karakteristik pasar
- Filter tingkat fluktuasi: penggunaan pita Brin dapat memfilter sinyal bocor palsu
- Fleksibilitas parameter: dapat disesuaikan dengan kondisi pasar yang berbeda
Risiko Strategis
- Risiko pasar yang bergoyang: sinyal palsu bisa muncul di pasar horizontal
- Efek slippage: beberapa stop-loss dapat menyebabkan deviasi harga eksekusi karena slippage
- Parameter ketergantungan: parameter mungkin perlu sering disesuaikan untuk kondisi pasar yang berbeda
- Kompleksitas sistem: mekanisme hambatan berlapis meningkatkan kompleksitas strategi
- Tekanan pengelolaan dana: beberapa posisi terhenti dapat meningkatkan kesulitan pengelolaan posisi
Arah optimasi strategi
- Penyesuaian parameter dinamis: sistem parameter adaptif dapat dikembangkan, menyesuaikan secara otomatis sesuai dengan kondisi pasar
- Identifikasi lingkungan pasar: menambahkan modul penilaian lingkungan pasar, menggunakan parameter yang berbeda dalam kondisi pasar yang berbeda
- Optimasi Stop Loss: meningkatkan mekanisme stop loss dinamis dan meningkatkan kemampuan pengendalian risiko
- Filter sinyal: meningkatkan indikator tambahan seperti volume lalu lintas, meningkatkan keandalan sinyal
- Manajemen Posisi: Mengembangkan Algoritma Pembagian Posisi yang Lebih Cerdas
Meringkaskan
Strategi ini menciptakan sistem pelacakan tren yang komprehensif dengan menggabungkan adaptasi dinamis dari indikator VIDYA dan fungsi penyaringan tingkat fluktuasi dari Brin Belt. Mekanisme hambatan bertingkat dan pengolahan multivariate yang diferensiasi membuatnya memiliki kemampuan pengembalian dan pengendalian risiko yang baik. Namun, pengguna perlu memperhatikan perubahan lingkungan pasar, menyesuaikan parameter sesuai kebutuhan, dan membangun sistem manajemen dana yang baik.
Kode Sumber Strategi
/*backtest
start: 2019-12-23 08:00:00
end: 2024-12-10 08:00:00
period: 1d
basePeriod: 1d
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/
// © PresentTrading
// This strategy, "VIDYA ProTrend Multi-Tier Profit," is a trend-following system that utilizes fast and slow VIDYA indicators
// to identify entry and exit points based on the direction and strength of the trend.
// It incorporates Bollinger Bands as a volatility filter and features a multi-step take profit mechanism,
// with adjustable ATR-based and percentage-based profit targets for both long and short positions.
// The strategy allows for more aggressive take profit settings for short trades, making it adaptable to varying market conditions.
//@version=5
strategy("VIDYA ProTrend Multi-Tier Profit", overlay=true, precision=3, commission_value= 0.1, commission_type=strategy.commission.percent, slippage= 1, currency=currency.USD, default_qty_type = strategy.percent_of_equity, default_qty_value = 10, initial_capital=10000)
// User-defined inputs
tradeDirection = input.string(title="Trading Direction", defval="Both", options=["Long", "Short", "Both"])
fastVidyaLength = input.int(10, title="Fast VIDYA Length", minval=1)
slowVidyaLength = input.int(30, title="Slow VIDYA Length", minval=1)
minSlopeThreshold = input.float(0.05, title="Minimum VIDYA Slope Threshold", step=0.01)
// Bollinger Bands Inputs
bbLength = input.int(20, title="Bollinger Bands Length", minval=1)
bbMultiplier = input.float(1.0, title="Bollinger Bands Multiplier", step=0.1)
// Multi-Step Take Profit Settings
group_tp = "Multi-Step Take Profit"
useMultiStepTP = input.bool(true, title="Enable Multi-Step Take Profit", group=group_tp)
tp_direction = input.string(title="Take Profit Direction", defval="Both", options=["Long", "Short", "Both"], group=group_tp)
atrLengthTP = input.int(14, title="ATR Length", group=group_tp)
// ATR-based Take Profit Steps
atrMultiplierTP1 = input.float(2.618, title="ATR Multiplier for TP 1", group=group_tp)
atrMultiplierTP2 = input.float(5.0, title="ATR Multiplier for TP 2", group=group_tp)
atrMultiplierTP3 = input.float(10.0, title="ATR Multiplier for TP 3", group=group_tp)
// Short Position Multiplier for Take Profit Percentages
shortTPPercentMultiplier = input.float(1.5, title="Short TP Percent Multiplier", group=group_tp)
// Percentage-based Take Profit Steps (Long)
tp_level_percent1 = input.float(title="Take Profit Level 1 (%)", defval=3.0, group=group_tp)
tp_level_percent2 = input.float(title="Take Profit Level 2 (%)", defval=8.0, group=group_tp)
tp_level_percent3 = input.float(title="Take Profit Level 3 (%)", defval=17.0, group=group_tp)
// Percentage-based Take Profit Allocation (Long)
tp_percent1 = input.float(title="Take Profit Percent 1 (%)", defval=12.0, group=group_tp)
tp_percent2 = input.float(title="Take Profit Percent 2 (%)", defval=8.0, group=group_tp)
tp_percent3 = input.float(title="Take Profit Percent 3 (%)", defval=10.0, group=group_tp)
// ATR-based Take Profit Percent Allocation (Long)
tp_percentATR1 = input.float(title="ATR TP Percent 1 (%)", defval=10.0, group=group_tp)
tp_percentATR2 = input.float(title="ATR TP Percent 2 (%)", defval=10.0, group=group_tp)
tp_percentATR3 = input.float(title="ATR TP Percent 3 (%)", defval=10.0, group=group_tp)
// Short position percentage allocations using the multiplier
tp_percent1_short = tp_percent1 * shortTPPercentMultiplier
tp_percent2_short = tp_percent2 * shortTPPercentMultiplier
tp_percent3_short = tp_percent3 * shortTPPercentMultiplier
tp_percentATR1_short = tp_percentATR1 * shortTPPercentMultiplier
tp_percentATR2_short = tp_percentATR2 * shortTPPercentMultiplier
tp_percentATR3_short = tp_percentATR3 * shortTPPercentMultiplier
// VIDYA Calculation Function
calcVIDYA(src, length) =>
alpha = 2 / (length + 1)
momm = ta.change(src)
m1 = momm >= 0.0 ? momm : 0.0
m2 = momm < 0.0 ? -momm : 0.0
sm1 = math.sum(m1, length)
sm2 = math.sum(m2, length)
chandeMO = nz(100 * (sm1 - sm2) / (sm1 + sm2))
k = math.abs(chandeMO) / 100
var float vidya = na
vidya := na(vidya[1]) ? src : (alpha * k * src + (1 - alpha * k) * vidya[1])
vidya
// Calculate VIDYAs
fastVIDYA = calcVIDYA(close, fastVidyaLength)
slowVIDYA = calcVIDYA(close, slowVidyaLength)
// Bollinger Bands Calculation
[bbUpper, bbBasis, bbLower] = ta.bb(close, bbLength, bbMultiplier)
// Manual Slope Calculation (price difference over time)
calcSlope(current, previous, length) =>
(current - previous) / length
// Slope of fast and slow VIDYA (comparing current value with value 'length' bars ago)
fastSlope = calcSlope(fastVIDYA, fastVIDYA[fastVidyaLength], fastVidyaLength)
slowSlope = calcSlope(slowVIDYA, slowVIDYA[slowVidyaLength], slowVidyaLength)
// Conditions for long entry with Bollinger Bands filter
longCondition = close > slowVIDYA and fastVIDYA > slowSlope and fastSlope > minSlopeThreshold and slowSlope > 1/2*minSlopeThreshold and close > bbUpper
// Conditions for short entry with Bollinger Bands filter
shortCondition = close < slowVIDYA and fastSlope < slowSlope and fastSlope < -minSlopeThreshold and slowSlope < -1/2*minSlopeThreshold and close < bbLower
// Exit conditions (opposite crossovers or flat slopes)
exitLongCondition = fastSlope < -minSlopeThreshold and slowSlope < -1/2*minSlopeThreshold or shortCondition
exitShortCondition = fastSlope > minSlopeThreshold and slowSlope > 1/2*minSlopeThreshold or longCondition
// Entry and Exit logic with trading direction
if (longCondition) and (strategy.position_size == 0) and (tradeDirection == "Long" or tradeDirection == "Both")
strategy.entry("Long", strategy.long)
if (exitLongCondition) and strategy.position_size > 0 and (tradeDirection == "Long" or tradeDirection == "Both")
strategy.close("Long")
if (shortCondition) and (strategy.position_size == 0) and (tradeDirection == "Short" or tradeDirection == "Both")
strategy.entry("Short", strategy.short)
if (exitShortCondition) and strategy.position_size < 0 and (tradeDirection == "Short" or tradeDirection == "Both")
strategy.close("Short")
if useMultiStepTP
if strategy.position_size > 0 and (tp_direction == "Long" or tp_direction == "Both")
// ATR-based Take Profit (Long)
tp_priceATR1_long = strategy.position_avg_price + atrMultiplierTP1 * ta.atr(atrLengthTP)
tp_priceATR2_long = strategy.position_avg_price + atrMultiplierTP2 * ta.atr(atrLengthTP)
tp_priceATR3_long = strategy.position_avg_price + atrMultiplierTP3 * ta.atr(atrLengthTP)
// Percentage-based Take Profit (Long)
tp_pricePercent1_long = strategy.position_avg_price * (1 + tp_level_percent1 / 100)
tp_pricePercent2_long = strategy.position_avg_price * (1 + tp_level_percent2 / 100)
tp_pricePercent3_long = strategy.position_avg_price * (1 + tp_level_percent3 / 100)
// Execute ATR-based exits for Long
strategy.exit("TP ATR 1 Long", from_entry="Long", qty_percent=tp_percentATR1, limit=tp_priceATR1_long)
strategy.exit("TP ATR 2 Long", from_entry="Long", qty_percent=tp_percentATR2, limit=tp_priceATR2_long)
strategy.exit("TP ATR 3 Long", from_entry="Long", qty_percent=tp_percentATR3, limit=tp_priceATR3_long)
// Execute Percentage-based exits for Long
strategy.exit("TP Percent 1 Long", from_entry="Long", qty_percent=tp_percent1, limit=tp_pricePercent1_long)
strategy.exit("TP Percent 2 Long", from_entry="Long", qty_percent=tp_percent2, limit=tp_pricePercent2_long)
strategy.exit("TP Percent 3 Long", from_entry="Long", qty_percent=tp_percent3, limit=tp_pricePercent3_long)
if strategy.position_size < 0 and (tp_direction == "Short" or tp_direction == "Both")
// ATR-based Take Profit (Short) - using the same ATR levels as long
tp_priceATR1_short = strategy.position_avg_price - atrMultiplierTP1 * ta.atr(atrLengthTP)
tp_priceATR2_short = strategy.position_avg_price - atrMultiplierTP2 * ta.atr(atrLengthTP)
tp_priceATR3_short = strategy.position_avg_price - atrMultiplierTP3 * ta.atr(atrLengthTP)
// Percentage-based Take Profit (Short) - using the same levels, but more aggressive percentages
tp_pricePercent1_short = strategy.position_avg_price * (1 - tp_level_percent1 / 100)
tp_pricePercent2_short = strategy.position_avg_price * (1 - tp_level_percent2 / 100)
tp_pricePercent3_short = strategy.position_avg_price * (1 - tp_level_percent3 / 100)
// Execute ATR-based exits for Short (using the percentage multiplier for short)
strategy.exit("TP ATR 1 Short", from_entry="Short", qty_percent=tp_percentATR1_short, limit=tp_priceATR1_short)
strategy.exit("TP ATR 2 Short", from_entry="Short", qty_percent=tp_percentATR2_short, limit=tp_priceATR2_short)
strategy.exit("TP ATR 3 Short", from_entry="Short", qty_percent=tp_percentATR3_short, limit=tp_priceATR3_short)
// Execute Percentage-based exits for Short
strategy.exit("TP Percent 1 Short", from_entry="Short", qty_percent=tp_percent1_short, limit=tp_pricePercent1_short)
strategy.exit("TP Percent 2 Short", from_entry="Short", qty_percent=tp_percent2_short, limit=tp_pricePercent2_short)
strategy.exit("TP Percent 3 Short", from_entry="Short", qty_percent=tp_percent3_short, limit=tp_pricePercent3_short)
// Plot VIDYAs
plot(fastVIDYA, color=color.green, title="Fast VIDYA")
plot(slowVIDYA, color=color.red, title="Slow VIDYA")