Price Action Quasimodo pattern Trading Strategy Meaning and Trading Rules

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The Quasimodo trading strategy is a chart pattern that consists of a series of swing highs and lows that breaks the characteristics of an existing trend.

What Does Quasimodo Mean in Trading? In trading, the Quasimodo definition refers to a reversal pattern that signals a potential change in the trend direction. It indicates a shift from an uptrend to a downtrend (bearish Quasimodo) or a downtrend to an uptrend (bullish Quasimodo).

Note* Some technicians might call this reversal pattern the “Over and Under” chart pattern.

Quasimodo Pattern Trading Strategy 🔥

The Quasimodo pattern is a reversal price action pattern that helps traders identify potential trend reversals. It is also known as the Over and Under Pattern and is used in both forex and stock trading.

📌 What is the Quasimodo Pattern?

The Quasimodo pattern consists of higher highs (HH), lower lows (LL), and an imbalance in structure that signals a potential trend reversal.

🔹 Bullish Quasimodo Pattern (Buy Signal)

  • The market is in a downtrend (Lower Highs & Lower Lows).
  • Price creates a Higher High (HH), breaking previous structure.
  • Then, a Lower Low (LL) is formed.
  • Entry: When price retraces to a key support zone after breaking the structure.

🔹 Confirmation: Look for bullish candlestick patterns like a pin bar, engulfing candle, or doji.

🔻 Bearish Quasimodo Pattern (Sell Signal)

  • The market is in an uptrend (Higher Highs & Higher Lows).
  • Price creates a Lower Low (LL), breaking previous structure.
  • Then, a Higher High (HH) is formed.
  • Entry: When price retraces to a key resistance level after breaking structure.

🔻 Confirmation: Look for bearish candlestick patterns like a bearish engulfing, pin bar, or shooting star.

📈 How to Trade the Quasimodo Pattern

1️⃣ Identify Market Structure

  • Look for a strong trend reversal with a break of structure.
  • Confirm a shift from higher highs to lower lows (or vice versa).

2️⃣ Mark Key Levels

  • Identify support & resistance zones for possible retracements.
  • Use Fibonacci retracements (50% – 78.6%) for extra confluence.

3️⃣ Wait for Price Confirmation

  • Price should return to the Quasimodo level (previous broken structure).
  • Look for candlestick confirmation before entering.

4️⃣ Set Stop-Loss & Take-Profit

✅ Stop-Loss (SL): Above/below the Quasimodo level (5-10 pips buffer).
✅ Take-Profit (TP): Near the next support/resistance zone.
✅ Risk-to-Reward Ratio: Aim for at least 1:2 or 1:3 RR.

🔍 Example of Quasimodo Strategy

📊 Bullish Quasimodo Example

  1. Downtrend creates Lower Highs & Lower Lows.
  2. Price breaks a key resistance and makes a Higher High (HH).
  3. Price retraces to a previous structure zone (support).
  4. Look for bullish reversal candles and enter a BUY trade.

📊 Bearish Quasimodo Example

  1. Uptrend creates Higher Highs & Higher Lows.
  2. Price breaks a key support and forms a Lower Low (LL).
  3. Price retraces to a resistance zone.
  4. Look for bearish reversal candles and enter a SELL trade.

🛠 Tools to Improve Accuracy

🔹 Fibonacci Levels – Look for retracements to 50% – 78.6% for confluence.
🔹 RSI Indicator – Check for overbought (70) or oversold (30) conditions.
🔹 Volume Analysis – Strong volume confirms breakout and Quasimodo validity.

🚀 Pro Tips for Quasimodo Trading

✅ Combine with Support & Resistance, RSI, and Fibonacci levels.
✅ Trade only on higher timeframes (H1, H4, Daily) for higher accuracy.
✅ Wait for confirmation before entering a trade.
✅ Avoid trading in ranging markets (low volatility).

Python script to detect Quasimodo patterns in live market data? 🚀📊

Here’s a Python script to detect Quasimodo patterns in historical market data using pandas, numpy, and TA-Lib (for technical analysis). This script fetches forex/stock data from Yahoo Finance, identifies potential Quasimodo patterns, and plots them for visualization.

A “Quasimodo” pattern in trading, also called an “Over and Under” pattern, is a price action reversal structure with a series of higher highs and higher lows (for bearish reversals) or lower lows and lower highs (for bullish reversals).

Here’s a Python script to detect Quasimodo patterns in live market data using TA-Lib and ccxt (for live exchange data). It checks for a series of higher highs (HH) and higher lows (HL) followed by a break of structure.

Features of the script:

✅ Fetches live market data from Binance
✅ Identifies Quasimodo pattern based on price structure
✅ Uses pandas & TA-Lib for analysis
✅ Can be modified for different timeframes & assets

Python Code:

You’ll need to install dependencies first:

bashCopyEditpip install ccxt pandas numpy ta-lib

Now, here’s the script:

pythonCopyEditimport ccxt
import pandas as pd
import numpy as np

# Initialize Binance API (No API Key needed for public data)
exchange = ccxt.binance()

# Parameters
symbol = "BTC/USDT"
timeframe = "5m"  # Change to "1h", "15m", etc.
lookback = 50  # Number of candles to analyze

def fetch_market_data(symbol, timeframe, limit=100):
    """Fetch OHLCV market data from Binance"""
    ohlcv = exchange.fetch_ohlcv(symbol, timeframe, limit=limit)
    df = pd.DataFrame(ohlcv, columns=['timestamp', 'open', 'high', 'low', 'close', 'volume'])
    df['timestamp'] = pd.to_datetime(df['timestamp'], unit='ms')  # Convert timestamp
    return df

def identify_quasimodo(df):
    """Detect Quasimodo Pattern"""
    highs = df['high'].values
    lows = df['low'].values
    closes = df['close'].values

    for i in range(4, len(df)):
        HH1 = highs[i-4]
        HL1 = lows[i-3]
        HH2 = highs[i-2]
        HL2 = lows[i-1]
        BOS = lows[i]  # Break of structure level

        if HH2 > HH1 and HL2 > HL1 and BOS < HL1:  # Bearish Quasimodo
            print(f"Bearish Quasimodo detected at {df['timestamp'][i]}")

        if HH2 < HH1 and HL2 < HL1 and BOS > HH1:  # Bullish Quasimodo
            print(f"Bullish Quasimodo detected at {df['timestamp'][i]}")

# Run the detection
df = fetch_market_data(symbol, timeframe, lookback)
identify_quasimodo(df)

How It Works:

  • It fetches recent candlestick data (OHLCV) from Binance
  • It checks for the Quasimodo structure:
    • Bearish QM: Higher highs (HH), higher lows (HL), then a break of structure (BOS) downward
    • Bullish QM: Lower highs (LH), lower lows (LL), then a BOS upward
  • Prints detected patterns with timestamps

Next Steps & Improvements:

🔹 Add alerts (Telegram, email, etc.)
🔹 Store detected patterns in a database
🔹 Visualize with matplotlib or plotly
🔹 Use machine learning for more accurate detection

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