বুলিশ এনগুলফিং কেনা এবং বিক্রয় কৌশলটি মোমবাতি প্যাটার্নের উপর ভিত্তি করে একটি পরিমাণগত ট্রেডিং কৌশল। এটি
এই কৌশলটি
যখন একটি স্টক একটি ডাউনট্রেন্ডে থাকে, যদি একটি ছোট বাস্তব শরীরের সাথে একটি মোমবাতি অনুসরণ করে যার বাস্তব শরীর সম্পূর্ণরূপে পূর্ববর্তী বাস্তব শরীরকে গ্রাস করে, এবং বন্ধের মূল্য পূর্ববর্তী উচ্চ মূল্যের চেয়ে বেশি হয়, এটি একটি বুলিশ গ্রাস প্যাটার্ন গঠন করে, একটি আসন্ন প্রবণতা বিপরীত সংকেত দেয়, যেখানে মূল্য বৃদ্ধি শুরু হবে।
এই কৌশলটি একটি দীর্ঘ পজিশন খুলবে যখন একটি বুলিশ এনগলফিং প্যাটার্ন চিহ্নিত করা হবে, লাভের লক্ষ্যমাত্রা 1% এবং 1% এর স্টপ লস সহ লাভের লক করার জন্য।
এই কৌশলটির সুবিধাগুলো হল:
এই কৌশলটির কিছু ঝুঁকি রয়েছেঃ
এই ঝুঁকিগুলি মোকাবেলা করার জন্য, আমরা করতে পারিঃ
এই কৌশল আরও উন্নত করা যেতে পারেঃ
বুলিশ এনগুলফিং কেনা বিক্রয় কৌশলটি প্রযুক্তিগত বিশ্লেষণের উপর ভিত্তি করে একটি পরিপক্ক পরিমাণগত ট্রেডিং কৌশল, সহজ এবং পরিষ্কার ট্রেডিং সংকেতগুলির সুবিধা সহ যা বাস্তবায়ন করা সহজ। অনুকূলিত পরামিতি এবং ভাল ঝুঁকি নিয়ন্ত্রণ ব্যবস্থাগুলির সাথে এটি স্থিতিশীল মুনাফা অর্জন করতে পারে এবং এটি অত্যন্ত প্রস্তাবিত।
/*backtest start: 2022-12-20 00:00:00 end: 2023-12-26 00:00:00 period: 1d basePeriod: 1h 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/ // © thequantscience // ██████╗ ██╗ ██╗██╗ ██╗ ██╗███████╗██╗ ██╗ ███████╗███╗ ██╗ ██████╗ ██╗ ██╗██╗ ███████╗██╗███╗ ██╗ ██████╗ // ██╔══██╗██║ ██║██║ ██║ ██║██╔════╝██║ ██║ ██╔════╝████╗ ██║██╔════╝ ██║ ██║██║ ██╔════╝██║████╗ ██║██╔════╝ // ██████╔╝██║ ██║██║ ██║ ██║███████╗███████║ █████╗ ██╔██╗ ██║██║ ███╗██║ ██║██║ █████╗ ██║██╔██╗ ██║██║ ███╗ // ██╔══██╗██║ ██║██║ ██║ ██║╚════██║██╔══██║ ██╔══╝ ██║╚██╗██║██║ ██║██║ ██║██║ ██╔══╝ ██║██║╚██╗██║██║ ██║ // ██████╔╝╚██████╔╝███████╗███████╗██║███████║██║ ██║ ███████╗██║ ╚████║╚██████╔╝╚██████╔╝███████╗██║ ██║██║ ╚████║╚██████╔╝ // ╚═════╝ ╚═════╝ ╚══════╝╚══════╝╚═╝╚══════╝╚═╝ ╚═╝ ╚══════╝╚═╝ ╚═══╝ ╚═════╝ ╚═════╝ ╚══════╝╚═╝ ╚═╝╚═╝ ╚═══╝ ╚═════╝ //@version=5 strategy( "Buy&Sell Bullish Engulfing - The Quant Science", overlay = true, default_qty_type = strategy.percent_of_equity, default_qty_value = 100, pyramiding = 1, currency = currency.EUR, initial_capital = 10000, commission_type = strategy.commission.percent, commission_value = 0.07, process_orders_on_close = true, close_entries_rule = "ANY" ) startDate = input.int(title="D: ", defval=1, minval=1, maxval=31, inline = 'Start', group = "START DATE BACKTESTING", tooltip = "D is Day, M is Month, Y is Year.") startMonth = input.int(title="M: ", defval=1, minval=1, maxval=12, inline = 'Start', group = "START DATE BACKTESTING", tooltip = "D is Day, M is Month, Y is Year.") startYear = input.int(title="Y: ", defval=2022, minval=1800, maxval=2100, inline = 'Start', group = "START DATE BACKTESTING", tooltip = "D is Day, M is Month, Y is Year.") endDate = input.int(title="D: ", defval=31, minval=1, maxval=31, inline = 'End', group = "END DATE BACKTESTING", tooltip = "D is Day, M is Month, Y is Year.") endMonth = input.int(title="M: ", defval=12, minval=1, maxval=12, inline = 'End', group = "END DATE BACKTESTING", tooltip = "D is Day, M is Month, Y is Year.") endYear = input.int(title="Y: ", defval=2023, minval=1800, maxval=2100, inline = 'End', group = "END DATE BACKTESTING", tooltip = "D is Day, M is Month, Y is Year.") inDateRange = (time >= timestamp(syminfo.timezone, startYear, startMonth, startDate, 0, 0)) and (time < timestamp(syminfo.timezone, endYear, endMonth, endDate, 0, 0)) PROFIT = input.float(defval = 1, minval = 0, title = "Target profit (%): ", step = 0.10, group = "TAKE PROFIT-STOP LOSS") STOPLOSS = input.float(defval = 1, minval = 0, title = "Stop Loss (%): ", step = 0.10, group = "TAKE PROFIT-STOP LOSS") var float equity_trades = 0 strategy.initial_capital = 50000 equity_trades := strategy.initial_capital var float equity = 0 var float qty_order = 0 t_ordersize = "Percentage size of each new order. With 'Reinvestment Profit' activate, the size will be calculate on the equity, with 'Reinvestment Profit' deactivate the size will be calculate on the initial capital." orders_size = input.float(defval = 2, title = "Orders size (%): ", minval = 0.10, step = 0.10, maxval = 100, group = "RISK MANAGEMENT", tooltip = t_ordersize) qty_order := ((equity_trades * orders_size) / 100 ) / close C_DownTrend = true C_UpTrend = true var trendRule1 = "SMA50" var trendRule2 = "SMA50, SMA200" var trendRule = input.string(trendRule1, "Detect Trend Based On", options=[trendRule1, trendRule2, "No detection"], group = "BULLISH ENGULFING") if trendRule == trendRule1 priceAvg = ta.sma(close, 50) C_DownTrend := close < priceAvg C_UpTrend := close > priceAvg if trendRule == trendRule2 sma200 = ta.sma(close, 200) sma50 = ta.sma(close, 50) C_DownTrend := close < sma50 and sma50 < sma200 C_UpTrend := close > sma50 and sma50 > sma200 C_Len = 14 C_ShadowPercent = 5.0 C_ShadowEqualsPercent = 100.0 C_DojiBodyPercent = 5.0 C_Factor = 2.0 C_BodyHi = math.max(close, open) C_BodyLo = math.min(close, open) C_Body = C_BodyHi - C_BodyLo C_BodyAvg = ta.ema(C_Body, C_Len) C_SmallBody = C_Body < C_BodyAvg C_LongBody = C_Body > C_BodyAvg C_UpShadow = high - C_BodyHi C_DnShadow = C_BodyLo - low C_HasUpShadow = C_UpShadow > C_ShadowPercent / 100 * C_Body C_HasDnShadow = C_DnShadow > C_ShadowPercent / 100 * C_Body C_WhiteBody = open < close C_BlackBody = open > close C_Range = high-low C_IsInsideBar = C_BodyHi[1] > C_BodyHi and C_BodyLo[1] < C_BodyLo C_BodyMiddle = C_Body / 2 + C_BodyLo C_ShadowEquals = C_UpShadow == C_DnShadow or (math.abs(C_UpShadow - C_DnShadow) / C_DnShadow * 100) < C_ShadowEqualsPercent and (math.abs(C_DnShadow - C_UpShadow) / C_UpShadow * 100) < C_ShadowEqualsPercent C_IsDojiBody = C_Range > 0 and C_Body <= C_Range * C_DojiBodyPercent / 100 C_Doji = C_IsDojiBody and C_ShadowEquals patternLabelPosLow = low - (ta.atr(30) * 0.6) patternLabelPosHigh = high + (ta.atr(30) * 0.6) label_color_bullish = input.color(color.rgb(43, 255, 0), title = "Label Color Bullish", group = "BULLISH ENGULFING") C_EngulfingBullishNumberOfCandles = 2 C_EngulfingBullish = C_DownTrend and C_WhiteBody and C_LongBody and C_BlackBody[1] and C_SmallBody[1] and close >= open[1] and open <= close[1] and ( close > open[1] or open < close[1] ) if C_EngulfingBullish var ttBullishEngulfing = "Engulfing\nAt the end of a given downward trend, there will most likely be a reversal pattern. To distinguish the first day, this candlestick pattern uses a small body, followed by a day where the candle body fully overtakes the body from the day before, and closes in the trend’s opposite direction. Although similar to the outside reversal chart pattern, it is not essential for this pattern to completely overtake the range (high to low), rather only the open and the close." label.new(bar_index, patternLabelPosLow, text="BE", style=label.style_label_up, color = label_color_bullish, textcolor=color.white, tooltip = ttBullishEngulfing) bgcolor(ta.highest(C_EngulfingBullish?1:0, C_EngulfingBullishNumberOfCandles)!=0 ? color.new(#21f321, 90) : na, offset=-(C_EngulfingBullishNumberOfCandles-1)) var float c = 0 var float o = 0 var float c_exit = 0 var float c_stopl = 0 if C_EngulfingBullish and strategy.opentrades==0 and inDateRange c := strategy.equity o := close c_exit := c + (c * PROFIT / 100) c_stopl := c - (c * STOPLOSS / 100) strategy.entry(id = "LONG", direction = strategy.long, qty = qty_order, limit = o) if ta.crossover(strategy.equity, c_exit) strategy.exit(id = "CLOSE-LONG", from_entry = "LONG", limit = close) if ta.crossunder(strategy.equity, c_stopl) strategy.exit(id = "CLOSE-LONG", from_entry = "LONG", limit = close)