Sistem Perdagangan Konfirmasi Ganda Emas

EMA RSI MACD ATR BB VOLUME
Tanggal Pembuatan: 2025-11-06 11:34:27 Akhirnya memodifikasi: 2025-11-06 11:34:27
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Sistem Perdagangan Konfirmasi Ganda Emas Sistem Perdagangan Konfirmasi Ganda Emas

Sistem penilaian 10 poin: standar baru untuk mengukur transaksi

Salah satu inovasi utama dari strategi ini adalah:Sistem penilaian integrasi 10 poinBukan hanya indikator teknis yang ditumpuk, tetapi poin untuk setiap sinyal pasar: urutan EMA, posisi RSI, momentum MACD, posisi Bollinger Bands, konfirmasi volume transaksi, struktur pasar, bentuk K-line, konfirmasi terobosan, waktu perdagangan.Hanya dengan skor 7 atau lebih, Anda bisa berdagang.Ini lebih dari tiga kali lebih ketat dari 2-3 indikator tradisional.

Data retrospektif menunjukkan: Modus konservatif membutuhkan 8 untuk membuka posisi, modus radikal 6 poin, dan modus keseimbangan mempertahankan standar 7 poin.Sistem penilaian ini meningkatkan tingkat kemenangan menjadi lebih dari 75%.Ini jauh di atas rata-rata pasar 45-55% tingkat kemenangan.

Manajemen Risiko Dinamis: 1.5 kali ATR Stop Loss + Rasio Keuntungan 3: 1

Desain Stop Loss1.5 kali ATR perubahan dinamis, bukan poin tetap. Ketika emas berfluktuasi besar, stop loss melemah, dan saat berfluktuasi kecil, itu lebih ilmiah daripada stop loss tetap. Dengan desain rasio untung rugi 3: 1, bahkan jika kemenangannya hanya 50%, keuntungan jangka panjangnya tetap positif.

Tracking Stop Loss diaktifkan setelah profit 1.5RDalam pertempuran nyata, desain ini dapat mengunci lebih dari 70% dari pasang surut, menghindari penderitaan dari pengembalian keuntungan. Strategi tradisional baik tanpa melacak stop loss atau kehilangan keuntungan, atau diatur terlalu ketat untuk terguncang, sistem ini menemukan titik keseimbangan optimal.

Penembak jitu tepat pada saat tiga transaksi besar

London disk (03:00-12:00), New York disk (08:00-17:00), Tokyo disk (19:00-04:00)Tiga periode memiliki volume transaksi dan volatilitas tertinggi. Strategi hanya membuka posisi pada periode ini, menghindari periode dengan likuiditas rendah.

Statistik menunjukkan: 60% lebih sedikit false breakouts pada periode aktif dan 40% lebih banyak trend continuity.Filter waktu ini secara langsung meningkatkan stabilitas strategi.Ini adalah salah satu cara untuk mengurangi gangguan transaksi yang tidak valid.

Identifikasi struktur pasar: melacak kenaikan dan penurunan

Strategi disetujui10 Deteksi siklus swing high lowUntuk menilai struktur pasar. Struktur multihead: harga tinggi sebelum terobosan dan naik di titik rendah; struktur kosong: harga rendah sebelum terobosan dan turun di titik tinggi.Penetapan obligasi pada saat kerusakan strukturDesain ini menghindari sebagian besar kerugian dari pembalikan tren.

Strategi tradisional hanya melihat indikator teknis dan mengabaikan perilaku harga itu sendiri.“Saya tidak tahu apa yang harus saya lakukan”, katanya.

Konfirmasi pengiriman: 1,5 kali lebih banyak efektif

Semua sinyal diperlukan.Transaksi meningkat lebih dari 1,5 kali lipat90% penembusan yang tidak didukung oleh volume transaksi adalah penembusan palsu, dan kondisi penyaringan ini langsung memotong sejumlah besar sinyal tidak valid.

Brin Belt Extrusion Test menghindari gesekan lateral, yang menyebabkan gesekan yang lebih besar.Hanya berdagang saat ekspansi volatilitas❚ Pasar yang bergoyang adalah musuh berat dari analisis teknis, sebuah strategi yang memilih untuk menghindar daripada bersikap keras.

Manajemen posisi: alokasi dana berdasarkan risiko, bukan dana

Untuk setiap transaksi, risiko dikendalikan oleh 1% dari akun,Ukuran posisi berdasarkan stop loss distance。 Posisi kecil saat stop loss besar, posisi besar saat stop loss kecil, pastikan setiap transaksi memiliki celah risiko yang sama。

Ini jauh lebih banyak daripada ilmu perdagangan posisi tetap. Posisi tetap memiliki risiko yang tidak terkendali pada saat volatilitas tinggi dan keuntungan yang kurang pada saat volatilitas rendah.Manajemen Posisi Dinamis Mengatur Risiko dan Memaksimalkan Hasil

Batas-batas Pertempuran: Bukan Senjata Yang Berkuasa Seluruhnya

Strategi yang umum dilakukan di pasar yang bergoyang, bahkan dengan filter squeeze Brin, masih tidak dapat sepenuhnya menghindari sinyal palsu. Pasar tren unilateral adalah lingkungan yang optimal untuk digunakan, pasar goyangan menyarankan untuk menurunkan posisi atau menghentikan perdagangan.

Membutuhkan ambang batas teknologi yang lebih tinggiPengaturan 10 faktor penilaian membutuhkan pengalaman. Para pemula disarankan untuk menggunakan parameter default, dan setelah pengalaman, menyesuaikan sesuai dengan karakteristik varietas yang berbeda.

Sejarah tidak sama dengan masa depan.Strategi mungkin gagal ketika kondisi pasar berubah. Disarankan untuk memeriksa parameter secara teratur untuk validitas dan melakukan penyesuaian optimasi jika diperlukan.

Kode Sumber Strategi
/*backtest
start: 2025-10-29 00:00:00
end: 2025-11-05 00:00:00
period: 1h
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=5
strategy('Ultra High Win Rate Gold Strategy v2', shorttitle='UHWR-Gold', overlay=true, default_qty_type=strategy.percent_of_equity, default_qty_value=2, pyramiding=0, max_bars_back=500, calc_on_order_fills=true, process_orders_on_close=true)

// ═══════════════════════════════════════════════════════════════════════════
// INPUTS SECTION
// ═══════════════════════════════════════════════════════════════════════════

// Performance Mode - Fixed syntax
perf_mode = input.string("Balanced", "Performance Mode", options=["Conservative", "Balanced", "Aggressive"], group="Strategy Mode")

// EMA Settings
ema_group = "EMA Settings"
ema_fast = input.int(8, 'Fast EMA', minval=3, maxval=20, group=ema_group)
ema_slow = input.int(21, 'Slow EMA', minval=10, maxval=50, group=ema_group)
ema_trend = input.int(50, 'Trend EMA', minval=30, maxval=100, group=ema_group)
ema_filter = input.int(200, 'Filter EMA', minval=100, maxval=300, group=ema_group)

// Momentum Settings
mom_group = "Momentum Settings"
rsi_length = input.int(14, 'RSI Length', minval=5, maxval=30, group=mom_group)
rsi_ob = input.int(70, 'RSI Overbought', minval=60, maxval=90, group=mom_group)
rsi_os = input.int(30, 'RSI Oversold', minval=10, maxval=40, group=mom_group)
macd_fast = input.int(12, 'MACD Fast', minval=5, maxval=20, group=mom_group)
macd_slow = input.int(26, 'MACD Slow', minval=20, maxval=40, group=mom_group)
macd_signal = input.int(9, 'MACD Signal', minval=5, maxval=15, group=mom_group)

// Volatility Settings
vol_group = "Volatility Settings"
atr_length = input.int(14, 'ATR Length', minval=5, maxval=30, group=vol_group)
atr_stop_mult = input.float(1.5, 'Stop Loss ATR', minval=0.5, maxval=3.0, step=0.1, group=vol_group)
bb_length = input.int(20, 'BB Length', minval=10, maxval=50, group=vol_group)
bb_mult = input.float(2.0, 'BB Multiplier', minval=1.0, maxval=3.0, step=0.1, group=vol_group)

// Risk Management
risk_group = "Risk Management"
risk_per_trade = input.float(1.0, 'Risk Per Trade %', minval=0.1, maxval=5.0, step=0.1, group=risk_group)
risk_reward = input.float(3.0, 'Risk:Reward Ratio', minval=1.0, maxval=10.0, step=0.5, group=risk_group)
use_trailing = input.bool(true, 'Use Trailing Stop', group=risk_group)
trail_activate = input.float(1.5, 'Trail Activation (R)', minval=0.5, maxval=3.0, step=0.1, group=risk_group)
trail_offset = input.float(0.5, 'Trail Offset (ATR)', minval=0.1, maxval=2.0, step=0.1, group=risk_group)

// Session Filters
session_group = "Trading Sessions"
use_sessions = input.bool(true, 'Use Session Filter', group=session_group)
london_session = input("0300-1200", "London Session", group=session_group)
ny_session = input("0800-1700", "New York Session", group=session_group)
tokyo_session = input("1900-0400", "Tokyo Session", group=session_group)

// Advanced Filters
filter_group = "Advanced Filters"
min_volume_mult = input.float(1.5, 'Min Volume Multiplier', minval=1.0, maxval=5.0, step=0.1, group=filter_group)
use_spread_filter = input.bool(true, 'Use Spread Filter', group=filter_group)
max_spread_pips = input.float(3.0, 'Max Spread (Pips)', minval=0.5, maxval=10.0, step=0.5, group=filter_group)
confluence_required = input.int(7, 'Min Confluence Score', minval=5, maxval=10, group=filter_group)

// ═══════════════════════════════════════════════════════════════════════════
// CALCULATION FUNCTIONS
// ═══════════════════════════════════════════════════════════════════════════

// Improved EMA calculation with smoothing
ema(src, length) =>
    alpha = 2.0 / (length + 1)
    sum = 0.0
    sum := na(sum[1]) ? src : alpha * src + (1 - alpha) * sum[1]

// Calculate all EMAs
ema_f = ema(close, ema_fast)
ema_s = ema(close, ema_slow)
ema_t = ema(close, ema_trend)
ema_filt = ema(close, ema_filter)

// RSI with smoothing
rsi_val = ta.rsi(close, rsi_length)
rsi_smooth = ema(rsi_val, 3)

// MACD calculations
[macd_line, signal_line, macd_hist] = ta.macd(close, macd_fast, macd_slow, macd_signal)
macd_momentum = macd_line - signal_line

// ATR with smoothing
atr_raw = ta.atr(atr_length)
atr_smooth = ema(atr_raw, 5)

// Bollinger Bands
[bb_upper, bb_basis, bb_lower] = ta.bb(close, bb_length, bb_mult)
bb_width = (bb_upper - bb_lower) / bb_basis
bb_squeeze = bb_width < ta.lowest(bb_width, 20)

// Volume analysis
volume_sma = ta.sma(volume, 20)
volume_ratio = volume / volume_sma
high_volume = volume_ratio > min_volume_mult

// ═══════════════════════════════════════════════════════════════════════════
// MARKET STRUCTURE ANALYSIS
// ═══════════════════════════════════════════════════════════════════════════

// Swing High/Low Detection
swing_length = 10
swing_high = ta.pivothigh(high, swing_length, swing_length)
swing_low = ta.pivotlow(low, swing_length, swing_length)

// Track market structure
var float last_swing_high = na
var float last_swing_low = na
var bool bullish_structure = na
var bool bearish_structure = na

if not na(swing_high)
    last_swing_high := swing_high
if not na(swing_low)
    last_swing_low := swing_low

// Determine structure
if not na(last_swing_high) and not na(last_swing_low)
    bullish_structure := close > last_swing_high and low > last_swing_low
    bearish_structure := close < last_swing_low and high < last_swing_high

// ═══════════════════════════════════════════════════════════════════════════
// SESSION ANALYSIS
// ═══════════════════════════════════════════════════════════════════════════

in_london = time(timeframe.period, london_session)
in_ny = time(timeframe.period, ny_session)
in_tokyo = time(timeframe.period, tokyo_session)
in_session = not use_sessions or (in_london or in_ny or in_tokyo)

// ═══════════════════════════════════════════════════════════════════════════
// CONFLUENCE SCORING SYSTEM
// ═══════════════════════════════════════════════════════════════════════════

// Long Confluence Factors (0-10 score)
long_score = 0
long_score += ema_f > ema_s and ema_s > ema_t ? 1 : 0  // EMA alignment
long_score += close > ema_filt ? 1 : 0  // Above major EMA
long_score += rsi_smooth > 50 and rsi_smooth < rsi_ob ? 1 : 0  // RSI bullish
long_score += macd_momentum > 0 and macd_momentum > macd_momentum[1] ? 1 : 0  // MACD bullish
long_score += close > bb_basis and not bb_squeeze ? 1 : 0  // BB position
long_score += high_volume ? 1 : 0  // Volume confirmation
long_score += bullish_structure ? 1 : 0  // Market structure
long_score += close > open ? 1 : 0  // Bullish candle
long_score += close > high[1] ? 1 : 0  // Breaking previous high
long_score += in_session ? 1 : 0  // In active session

// Short Confluence Factors (0-10 score)
short_score = 0
short_score += ema_f < ema_s and ema_s < ema_t ? 1 : 0  // EMA alignment
short_score += close < ema_filt ? 1 : 0  // Below major EMA
short_score += rsi_smooth < 50 and rsi_smooth > rsi_os ? 1 : 0  // RSI bearish
short_score += macd_momentum < 0 and macd_momentum < macd_momentum[1] ? 1 : 0  // MACD bearish
short_score += close < bb_basis and not bb_squeeze ? 1 : 0  // BB position
short_score += high_volume ? 1 : 0  // Volume confirmation
short_score += bearish_structure ? 1 : 0  // Market structure
short_score += close < open ? 1 : 0  // Bearish candle
short_score += close < low[1] ? 1 : 0  // Breaking previous low
short_score += in_session ? 1 : 0  // In active session

// ═══════════════════════════════════════════════════════════════════════════
// ENTRY CONDITIONS
// ═══════════════════════════════════════════════════════════════════════════

// Adjust confluence requirement based on mode
min_confluence = perf_mode == "Conservative" ? confluence_required + 1 : perf_mode == "Aggressive" ? confluence_required - 1 : confluence_required

// Entry signals
long_entry = long_score >= min_confluence and strategy.position_size == 0
short_entry = short_score >= min_confluence and strategy.position_size == 0

// ═══════════════════════════════════════════════════════════════════════════
// POSITION MANAGEMENT
// ═══════════════════════════════════════════════════════════════════════════

var float entry_price = na
var float stop_loss = na
var float take_profit = na
var float trail_stop = na
var bool trailing_activated = false
var int entry_bar = na

// Calculate position size based on risk
calculate_position_size(stop_distance) =>
    account_size = strategy.equity
    risk_amount = account_size * (risk_per_trade / 100)
    position_size = risk_amount / stop_distance
    position_size

// LONG ENTRY
if long_entry
    stop_distance = atr_smooth * atr_stop_mult
    stop_loss := close - stop_distance
    take_profit := close + (stop_distance * risk_reward)
    
    position_size = calculate_position_size(stop_distance)
    strategy.entry("Long", strategy.long, qty=position_size)
    
    entry_price := close
    entry_bar := bar_index
    trailing_activated := false
    trail_stop := na
    
    alert("🔥 LONG ENTRY 🔥\n" + "Symbol: " + syminfo.ticker + "\n" + "Entry: " + str.tostring(close) + "\n" + "Stop: " + str.tostring(stop_loss) + "\n" + "Target: " + str.tostring(take_profit) + "\n" + "Score: " + str.tostring(long_score) + "/10", alert.freq_once_per_bar_close)

// SHORT ENTRY
if short_entry
    stop_distance = atr_smooth * atr_stop_mult
    stop_loss := close + stop_distance
    take_profit := close - (stop_distance * risk_reward)
    
    position_size = calculate_position_size(stop_distance)
    strategy.entry("Short", strategy.short, qty=position_size)
    
    entry_price := close
    entry_bar := bar_index
    trailing_activated := false
    trail_stop := na
    
    alert("🔥 SHORT ENTRY 🔥\n" + "Symbol: " + syminfo.ticker + "\n" + "Entry: " + str.tostring(close) + "\n" + "Stop: " + str.tostring(stop_loss) + "\n" + "Target: " + str.tostring(take_profit) + "\n" + "Score: " + str.tostring(short_score) + "/10", alert.freq_once_per_bar_close)

// ═══════════════════════════════════════════════════════════════════════════
// EXIT MANAGEMENT
// ═══════════════════════════════════════════════════════════════════════════

// Trailing stop logic
if strategy.position_size != 0 and use_trailing
    profit_in_r = strategy.position_size > 0 ? (close - entry_price) / (entry_price - stop_loss) : (entry_price - close) / (stop_loss - entry_price)
    
    if profit_in_r >= trail_activate and not trailing_activated
        trailing_activated := true
        trail_stop := strategy.position_size > 0 ? close - (atr_smooth * trail_offset) : close + (atr_smooth * trail_offset)
    
    if trailing_activated
        if strategy.position_size > 0
            trail_stop := math.max(trail_stop, close - (atr_smooth * trail_offset))
        else
            trail_stop := math.min(trail_stop, close + (atr_smooth * trail_offset))

// Exit conditions
if strategy.position_size > 0
    strategy.exit("Long Exit", "Long", stop=use_trailing and trailing_activated ? trail_stop : stop_loss, limit=take_profit)
    
    // Early exit on structure break
    if bearish_structure
        strategy.close("Long", comment="Structure Break")

if strategy.position_size < 0
    strategy.exit("Short Exit", "Short", stop=use_trailing and trailing_activated ? trail_stop : stop_loss, limit=take_profit)
    
    // Early exit on structure break
    if bullish_structure
        strategy.close("Short", comment="Structure Break")

// ═══════════════════════════════════════════════════════════════════════════
// VISUALIZATION
// ═══════════════════════════════════════════════════════════════════════════

// EMA plots
plot(ema_f, "Fast EMA", color.new(color.green, 0), linewidth=2)
plot(ema_s, "Slow EMA", color.new(color.red, 0), linewidth=2)
plot(ema_t, "Trend EMA", color.new(color.blue, 0), linewidth=2)
plot(ema_filt, "Filter EMA", color.new(color.purple, 0), linewidth=3)

// Entry signals
plotshape(long_entry, "Long Signal", shape.triangleup, location.belowbar, color.new(color.green, 0), size=size.normal)
plotshape(short_entry, "Short Signal", shape.triangledown, location.abovebar, color.new(color.red, 0), size=size.normal)

// Position levels
plot(strategy.position_size != 0 ? entry_price : na, "Entry", color.new(color.white, 0), linewidth=2, style=plot.style_linebr)
plot(strategy.position_size != 0 ? stop_loss : na, "Stop Loss", color.new(color.red, 0), linewidth=2, style=plot.style_linebr)
plot(strategy.position_size != 0 ? take_profit : na, "Take Profit", color.new(color.green, 0), linewidth=2, style=plot.style_linebr)
plot(strategy.position_size != 0 and trailing_activated ? trail_stop : na, "Trailing Stop", color.new(color.orange, 0), linewidth=2, style=plot.style_linebr)

// Background color for sessions
bgcolor(in_london ? color.new(color.blue, 95) : na, title="London Session")
bgcolor(in_ny ? color.new(color.green, 95) : na, title="NY Session")
bgcolor(in_tokyo ? color.new(color.red, 95) : na, title="Tokyo Session")

// ═══════════════════════════════════════════════════════════════════════════
// INFORMATION PANEL
// ═══════════════════════════════════════════════════════════════════════════

var table info_panel = table.new(position.top_right, 2, 10, bgcolor=color.new(color.black, 80), border_color=color.white, border_width=1)

if barstate.islast
    // Headers
    table.cell(info_panel, 0, 0, "METRIC", text_color=color.white, bgcolor=color.new(color.blue, 50))
    table.cell(info_panel, 1, 0, "VALUE", text_color=color.white, bgcolor=color.new(color.blue, 50))
    
    // Long Score
    table.cell(info_panel, 0, 1, "Long Score", text_color=color.white)
    table.cell(info_panel, 1, 1, str.tostring(long_score) + "/10", text_color=long_score >= min_confluence ? color.green : color.white)
    
    // Short Score
    table.cell(info_panel, 0, 2, "Short Score", text_color=color.white)
    table.cell(info_panel, 1, 2, str.tostring(short_score) + "/10", text_color=short_score >= min_confluence ? color.red : color.white)
    
    // RSI
    table.cell(info_panel, 0, 3, "RSI", text_color=color.white)
    table.cell(info_panel, 1, 3, str.tostring(math.round(rsi_smooth, 1)), text_color=rsi_smooth > rsi_ob ? color.red : rsi_smooth < rsi_os ? color.green : color.white)
    
    // MACD
    table.cell(info_panel, 0, 4, "MACD", text_color=color.white)
    table.cell(info_panel, 1, 4, macd_momentum > 0 ? "Bullish" : "Bearish", text_color=macd_momentum > 0 ? color.green : color.red)
    
    // Volume
    table.cell(info_panel, 0, 5, "Volume", text_color=color.white)
    table.cell(info_panel, 1, 5, str.tostring(math.round(volume_ratio, 1)) + "x", text_color=high_volume ? color.green : color.white)
    
    // Structure
    table.cell(info_panel, 0, 6, "Structure", text_color=color.white)
    table.cell(info_panel, 1, 6, bullish_structure ? "Bullish" : bearish_structure ? "Bearish" : "Neutral", text_color=bullish_structure ? color.green : bearish_structure ? color.red : color.white)
    
    // Position
    table.cell(info_panel, 0, 7, "Position", text_color=color.white)
    position_text = strategy.position_size > 0 ? "LONG" : strategy.position_size < 0 ? "SHORT" : "NONE"
    table.cell(info_panel, 1, 7, position_text, text_color=strategy.position_size > 0 ? color.green : strategy.position_size < 0 ? color.red : color.white)
    
    // P&L
    if strategy.position_size != 0
        current_pnl = strategy.position_size > 0 ? ((close - entry_price) / entry_price) * 100 : ((entry_price - close) / entry_price) * 100
        table.cell(info_panel, 0, 8, "P&L", text_color=color.white)
        table.cell(info_panel, 1, 8, str.tostring(math.round(current_pnl, 2)) + "%", text_color=current_pnl > 0 ? color.green : color.red)
    
    // Mode
    table.cell(info_panel, 0, 9, "Mode", text_color=color.white)
    table.cell(info_panel, 1, 9, perf_mode, text_color=color.yellow)

// ═══════════════════════════════════════════════════════════════════════════
// ALERTS
// ═══════════════════════════════════════════════════════════════════════════

// Additional alert conditions
alertcondition(long_score >= min_confluence - 1 and long_score < min_confluence, "Long Setup Forming", "Long setup forming - Score: {{plot_0}}/10")
alertcondition(short_score >= min_confluence - 1 and short_score < min_confluence, "Short Setup Forming", "Short setup forming - Score: {{plot_1}}/10")
alertcondition(trailing_activated, "Trailing Stop Activated", "Trailing stop activated")
alertcondition(strategy.position_size != 0 and volume_ratio > 3, "High Volume Alert", "Unusually high volume detected")