inverse head and shoulders

Inverse Head and Shoulders

Inverse Head and Shoulders Chart Pattern Reversal Downtrend Uptrend Neckline Breakout Volume Left Shoulder Head Right Shoulder Target Price Technical Analysis

Pattern Detection

# ihs_detector.py — Inverse Head & Shoulders Detection
from dataclasses import dataclass
from typing import List, Optional, Tuple

@dataclass
class PricePoint:
    date: str
    price: float
    volume: int

@dataclass
class IHSPattern:
    left_shoulder: PricePoint
    head: PricePoint
    right_shoulder: PricePoint
    neckline: float
    target_price: float
    pattern_height: float
    confirmed: bool

def find_ihs(lows: List[PricePoint], highs: List[PricePoint]) -> Optional[IHSPattern]:
    """ค้นหา Inverse Head and Shoulders Pattern"""
    if len(lows) < 3 or len(highs) < 2:
        return None

    left_shoulder = lows[0]
    head = lows[1]
    right_shoulder = lows[2]

    # Head ต้องต่ำกว่า Shoulders
    if head.price >= left_shoulder.price or head.price >= right_shoulder.price:
        return None

    # Shoulders ควรอยู่ระดับใกล้เคียงกัน (±5%)
    shoulder_diff = abs(left_shoulder.price - right_shoulder.price)
    avg_shoulder = (left_shoulder.price + right_shoulder.price) / 2
    if shoulder_diff / avg_shoulder > 0.05:
        return None

    # Neckline = เฉลี่ยจุดสูงระหว่าง Shoulders
    neckline = (highs[0].price + highs[1].price) / 2

    # Target
    pattern_height = neckline - head.price
    target = neckline + pattern_height

    # Volume confirmation
    confirmed = right_shoulder.volume > left_shoulder.volume

    return IHSPattern(
        left_shoulder, head, right_shoulder,
        neckline, target, pattern_height, confirmed
    )

# Example
lows = [
    PricePoint("2024-01-15", 85, 500000),
    PricePoint("2024-02-10", 75, 600000),
    PricePoint("2024-03-05", 83, 700000),
]
highs = [
    PricePoint("2024-01-28", 95, 400000),
    PricePoint("2024-02-25", 93, 450000),
]

pattern = find_ihs(lows, highs)
if pattern:
    print("=== Inverse Head & Shoulders Detected ===")
    print(f"  Left Shoulder: {pattern.left_shoulder.price} ({pattern.left_shoulder.date})")
    print(f"  Head: {pattern.head.price} ({pattern.head.date})")
    print(f"  Right Shoulder: {pattern.right_shoulder.price} ({pattern.right_shoulder.date})")
    print(f"  Neckline: {pattern.neckline}")
    print(f"  Pattern Height: {pattern.pattern_height}")
    print(f"  Target Price: {pattern.target_price}")
    print(f"  Confirmed: {pattern.confirmed}")

Trading Strategy

# ihs_strategy.py — Trading Strategy with IHS
from dataclasses import dataclass
from typing import List

@dataclass
class TradeSetup:
    entry: float
    stop_loss: float
    target_1: float
    target_2: float
    risk_reward: float
    position_size: int

def calculate_trade(neckline: float, head: float, right_shoulder: float,
                    account: float, risk_pct: float) -> TradeSetup:
    entry = neckline * 1.005  # Entry เหนือ Neckline 0.5%
    stop_loss = right_shoulder * 0.99  # SL ใต้ Right Shoulder 1%
    pattern_height = neckline - head
    target_1 = neckline + pattern_height  # 1x Height
    target_2 = neckline + pattern_height * 1.5  # 1.5x Height

    risk_per_share = entry - stop_loss
    risk_amount = account * (risk_pct / 100)
    position_size = int(risk_amount / risk_per_share)
    reward = target_1 - entry
    rr = reward / risk_per_share if risk_per_share > 0 else 0

    return TradeSetup(entry, stop_loss, target_1, target_2, rr, position_size)

trade = calculate_trade(
    neckline=94, head=75, right_shoulder=83,
    account=1000000, risk_pct=2
)

print("\n=== Trade Setup ===")
print(f"  Entry: {trade.entry}")
print(f"  Stop Loss: {trade.stop_loss}")
print(f"  Target 1: {trade.target_1} (1x)")
print(f"  Target 2: {trade.target_2} (1.5x)")
print(f"  Risk:Reward: 1:{trade.risk_reward:.1f}")
print(f"  Position Size: {trade.position_size} shares")

# Backtest Results
results = [
    {"pattern": "IHS #1", "entry": 95, "target": 113, "result": "+18.9%", "win": True},
    {"pattern": "IHS #2", "entry": 52, "target": 64, "result": "+23.1%", "win": True},
    {"pattern": "IHS #3", "entry": 180, "target": 210, "result": "-5.2%", "win": False},
    {"pattern": "IHS #4", "entry": 45, "target": 55, "result": "+22.2%", "win": True},
    {"pattern": "IHS #5", "entry": 120, "target": 145, "result": "+20.8%", "win": True},
]

wins = sum(1 for r in results if r["win"])
print(f"\n  Backtest: {wins}/{len(results)} wins ({wins/len(results)*100:.0f}%)")
for r in results:
    icon = "WIN" if r["win"] else "LOSS"
    print(f"    [{icon}] {r['pattern']}: Entry {r['entry']} -> {r['result']}")

Advanced Analysis

# advanced.py — Multi-timeframe & Volume Analysis
from dataclasses import dataclass

@dataclass
class VolumeProfile:
    phase: str
    avg_volume: int
    trend: str
    signal: str

volume_phases = [
    VolumeProfile("Downtrend (Before)", 500000, "สูง", "ขาลงแรง"),
    VolumeProfile("Left Shoulder", 450000, "ลดลง", "แรงขายลด"),
    VolumeProfile("Head (จุดต่ำสุด)", 350000, "ต่ำสุด", "Capitulation"),
    VolumeProfile("Right Shoulder", 400000, "เพิ่มขึ้น", "สะสม"),
    VolumeProfile("Neckline Break", 800000, "สูงมาก", "ยืนยัน Breakout"),
    VolumeProfile("After Breakout", 600000, "สูง", "Trend ใหม่"),
]

print("=== Volume Profile ===")
for v in volume_phases:
    bar = "█" * (v.avg_volume // 100000)
    print(f"  [{v.phase}]")
    print(f"    Volume: {v.avg_volume:,} ({v.trend}) — {v.signal}")
    print(f"    {bar}")

# Common Mistakes
mistakes = {
    "ไม่รอ Breakout": "เข้าก่อน Neckline Break อาจเป็น False Pattern",
    "ไม่ดู Volume": "Breakout ต้องมี Volume สูง ถ้า Volume ต่ำ = อ่อน",
    "Timeframe เล็ก": "H1 หรือต่ำกว่า False Signal มาก ใช้ Daily ขึ้นไป",
    "ไม่ตั้ง Stop Loss": "ตั้ง SL ใต้ Right Shoulder เสมอ",
    "Target ไกลเกิน": "ใช้ 1x Pattern Height เป็น Target แรก",
    "ไม่ Retest": "Retest Neckline เป็นจุด Entry ที่ดีกว่า Breakout",
}

print(f"\n\nCommon Mistakes:")
for mistake, fix in mistakes.items():
    print(f"  [{mistake}]: {fix}")

เคล็ดลับ

• Volume: Breakout ต้องมี Volume สูงกว่าค่าเฉลี่ย 2x
• Retest: รอ Retest Neckline เป็น Entry ที่ดีกว่า
• Timeframe: Daily/Weekly น่าเชื่อถือกว่า Intraday
• Symmetry: Shoulders ที่สมมาตร น่าเชื่อถือกว่า
• Stop Loss: ตั้งใต้ Right Shoulder เสมอ

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สรุป

Inverse Head and Shoulders Chart Pattern Reversal Neckline Breakout Volume Target Price Left Shoulder Head Right Shoulder Backtest Position Sizing Risk Management Stop Loss Retest Daily Weekly