Chande Momentum Oscillator (MO)
Bollinger Bands như bộ lọc biến động: Phạm vi trên = MA + (K * StdDev) Phạm vi dưới = MA - (K * StdDev)
Điều kiện nhập cảnh:
Cơ chế thu lợi nhuận đa cấp bao gồm:
Chiến lược này tạo ra một hệ thống theo dõi xu hướng toàn diện bằng cách kết hợp khả năng thích nghi năng động của chỉ số VIDYA với lọc biến động Bollinger Bands. Cơ chế lấy lợi nhuận đa cấp và xử lý dài / ngắn phân biệt cung cấp tiềm năng lợi nhuận và kiểm soát rủi ro mạnh mẽ. Tuy nhiên, người dùng cần theo dõi những thay đổi môi trường thị trường, điều chỉnh các tham số phù hợp và thiết lập các hệ thống quản lý tiền mạnh mẽ.
/*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")