forex

Technical Analysis of EURUSD —

Technical Analysis of EURUSD —

EUR/USD Analysis

Technical Analysis of EURUSD —

Technical Analysis EUR/USD Forex Chart Patterns Indicators Support Resistance EMA RSI MACD Fibonacci Bollinger Bands Entry Strategy Risk Management Trading

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IndicatorTypeSettingsSignalTimeframeReliability
EMATrend20 50 200Cross DirectionH4 Dailyสูง
RSIMomentum14OB/OS DivergenceH1 H4ปานกลาง
MACDMomentum12 26 9Cross Zero DivergeH4 Dailyสูง
BollingerVolatility20 2Squeeze BreakoutH1 H4ปานกลาง
FibonacciS/R Level38.2 50 61.8RetracementAllสูง
ATRVolatility14SL DistanceH4 Dailyสูง

Chart Analysis

# === EUR/USD Technical Analysis with Python ===

# pip install yfinance pandas ta matplotlib

# import yfinance as yf
# import pandas as pd
# import ta
#
# # Download EUR/USD data
# df = yf.download("EURUSD=X", start="2024-01-01", period="1y", interval="1d")
#
# # EMA 20, 50, 200
# df["EMA20"] = ta.trend.ema_indicator(df["Close"], window=20)
# df["EMA50"] = ta.trend.ema_indicator(df["Close"], window=50)
# df["EMA200"] = ta.trend.ema_indicator(df["Close"], window=200)
#
# # RSI 14
# df["RSI"] = ta.momentum.rsi(df["Close"], window=14)
#
# # MACD
# macd = ta.trend.MACD(df["Close"])
# df["MACD"] = macd.macd()
# df["MACD_Signal"] = macd.macd_signal()
# df["MACD_Hist"] = macd.macd_diff()
#
# # Bollinger Bands
# bb = ta.volatility.BollingerBands(df["Close"], window=20, window_dev=2)
# df["BB_Upper"] = bb.bollinger_hband()
# df["BB_Lower"] = bb.bollinger_lband()
# df["BB_Middle"] = bb.bollinger_mavg()
#
# # ATR 14
# df["ATR"] = ta.volatility.average_true_range(df["High"], df["Low"], df["Close"], window=14)
#
# # Trend Detection
# latest = df.iloc[-1]
# trend = "Bullish" if latest["EMA20"] > latest["EMA50"] > latest["EMA200"] else \
#         "Bearish" if latest["EMA20"] < latest["EMA50"] < latest["EMA200"] else "Ranging"
#
# print(f"=== EUR/USD Daily Analysis ===")
# print(f"  Price: {latest['Close']:.4f}")
# print(f"  Trend: {trend}")
# print(f"  EMA20: {latest['EMA20']:.4f} | EMA50: {latest['EMA50']:.4f} | EMA200: {latest['EMA200']:.4f}")
# print(f"  RSI: {latest['RSI']:.1f} | ATR: {latest['ATR']:.4f}")

from dataclasses import dataclass

@dataclass
class TechnicalLevel:
    level_type: str
    price: str
    strength: str
    method: str
    action: str

levels = [
    TechnicalLevel("Resistance R3", "1.1050", "Strong", "Monthly High", "TP3 target"),
    TechnicalLevel("Resistance R2", "1.0950", "Medium", "Fibonacci 61.8%", "TP2 target"),
    TechnicalLevel("Resistance R1", "1.0880", "Strong", "EMA200 + Round", "TP1 / Watch"),
    TechnicalLevel("Current Price", "1.0820", "-", "Market", "-"),
    TechnicalLevel("Support S1", "1.0750", "Strong", "Fibonacci 38.2%", "Buy zone"),
    TechnicalLevel("Support S2", "1.0680", "Medium", "Previous low", "Strong buy"),
    TechnicalLevel("Support S3", "1.0600", "Strong", "Psychological", "Last defense"),
]

print("=== Key Levels EUR/USD ===")
for l in levels:
    print(f"  [{l.level_type}] {l.price} | Strength: {l.strength}")
    print(f"    Method: {l.method} | Action: {l.action}")

Trading Strategy

Technical Analysis of EURUSD —
# === EUR/USD Trading Strategies ===

@dataclass
class TradeSetup:
    strategy: str
    timeframe: str
    entry_condition: str
    stop_loss: str
    take_profit: str
    risk_reward: str
    win_rate: str

setups = [
    TradeSetup("EMA Pullback Buy", "H4",
        "Price pulls back to EMA20 in uptrend + bullish candle",
        "Below EMA50 or recent swing low",
        "Previous swing high or 1:2 R:R",
        "1:2", "55-60%"),
    TradeSetup("RSI Divergence", "H4",
        "Price makes lower low but RSI makes higher low at support",
        "Below divergence low + ATR buffer",
        "Next resistance level",
        "1:2.5", "50-55%"),
    TradeSetup("Bollinger Squeeze Breakout", "H1",
        "BB squeeze (narrow bands) + breakout above upper band + volume",
        "Below BB middle band",
        "1.5x BB width from breakout",
        "1:2", "45-50%"),
    TradeSetup("Fibonacci Bounce", "Daily",
        "Price retraces to 50-61.8% Fib + pin bar at level",
        "Below 78.6% Fib level",
        "100% Fib extension",
        "1:3", "50-55%"),
]

print("=== Trade Setups ===")
for s in setups:
    print(f"  [{s.strategy}] TF: {s.timeframe}")
    print(f"    Entry: {s.entry_condition}")
    print(f"    SL: {s.stop_loss}")
    print(f"    TP: {s.take_profit}")
    print(f"    R:R: {s.risk_reward} | Win Rate: {s.win_rate}")

# Economic Calendar Impact
events = {
    "NFP (Non-Farm Payrolls)": "High — 50-100 pips move, first Friday monthly",
    "FOMC Rate Decision": "Very High — 100-200 pips, 8x per year",
    "ECB Rate Decision": "Very High — 80-150 pips, 8x per year",
    "CPI (US)": "High — 50-80 pips, monthly",
    "GDP (US/EU)": "Medium-High — 30-60 pips, quarterly",
    "PMI": "Medium — 20-40 pips, monthly",
}

print(f"\n\nEconomic Calendar:")
for k, v in events.items():
    print(f"  [{k}]: {v}")

Risk Management

# === Risk Management for EUR/USD ===

@dataclass
class RiskCalc:
    balance: float
    risk_pct: float
    entry: float
    stop_loss: float
    take_profit: float

def calculate_position(calc):
    risk_amount = calc.balance * (calc.risk_pct / 100)
    sl_pips = abs(calc.entry - calc.stop_loss) * 10000
    tp_pips = abs(calc.take_profit - calc.entry) * 10000
    lot_size = round(risk_amount / (sl_pips * 10), 2)  # Standard lot pip = $10
    rr_ratio = tp_pips / sl_pips if sl_pips > 0 else 0

    print(f"  Balance:  | Risk: {calc.risk_pct}% = ")
    print(f"  Entry: {calc.entry:.4f} | SL: {calc.stop_loss:.4f} ({sl_pips:.0f} pips)")
    print(f"  TP: {calc.take_profit:.4f} ({tp_pips:.0f} pips) | R:R: 1:{rr_ratio:.1f}")
    print(f"  Lot Size: {lot_size} lots")
    return lot_size

trades = [
    RiskCalc(10000, 1, 1.0750, 1.0710, 1.0830),  # Buy at support
    RiskCalc(10000, 1, 1.0880, 1.0920, 1.0800),  # Sell at resistance
    RiskCalc(25000, 2, 1.0680, 1.0640, 1.0800),  # Larger account buy
]

print("=== Position Sizing ===")
for i, t in enumerate(trades):
    print(f"\n  Trade {i+1}:")
    calculate_position(t)

journal = {
    "Track Every Trade": "Entry Exit SL TP Reason Result Screenshot",
    "Weekly Review": "Win Rate R:R Average P&L Mistakes",
    "Monthly Stats": "Total Trades Profit Factor Max Drawdown",
    "Improve": "ปรับ Strategy ตาม Journal Data",
    "Rules": "ไม่เทรด NFP ไม่ Over-leverage Risk 1% เสมอ",
}

print(f"\n\nTrading Journal:")
for k, v in journal.items():
    print(f"  [{k}]: {v}")

เคล็ดลับ

  • Multi-TF: วิเคราะห์ Weekly Daily ก่อน Entry ที่ H1
  • News: หลีกเลี่ยง Entry ก่อน High Impact News 30 นาที
  • Risk: ไม่เกิน 1% ต่อ Trade ใช้ Position Sizing Calculator
  • Confluence: Entry เมื่อมี 2-3 Signals ยืนยัน ไม่ใช้ตัวเดียว
  • Journal: จด Trade Journal ทุก Trade วิเคราะห์ทุกสัปดาห์

EUR/USD คืออะไร

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