README.md

Bullish Divergence Detector for Binance

This script analyzes cryptocurrency pairs on Binance to detect bullish divergences using MACD and RSI indicators. A bullish divergence occurs when the price of a cryptocurrency makes a lower low, but the indicator makes a higher low, signaling a potential price reversal.

Features

Fetches OHLCV data for multiple symbols from Binance.
Calculates MACD and RSI indicators.
Detects bullish divergences based on MACD and RSI.
Lists symbols that exhibit bullish divergence.

Prerequisites

Python 3.x
pandas library
numpy library
ccxt library
ta library

Installation

Clone the repository:

git clone https://github.com/shidiqmuh0/bullish_divergence_binance.git
cd bullish_divergence_binance

Install the required Python packages:
```
pip install pandas numpy ccxt ta
```

Usage

Run the script to detect symbols with bullish divergence:

python app.py

Result

Script Explanation

1. Initialize the Binance Exchange

exchange = ccxt.binance()

2. Fetch OHLCV Data

The fetch_ohlcv function retrieves OHLCV (Open, High, Low, Close, Volume) data for a given symbol and timeframe from Binance.

def fetch_ohlcv(symbol, timeframe='1h', limit=500):
    ohlcv = exchange.fetch_ohlcv(symbol, timeframe=timeframe, limit=limit)
    df = pd.DataFrame(ohlcv, columns=['timestamp', 'open', 'high', 'low', 'close', 'volume'])
    df['timestamp'] = pd.to_datetime(df['timestamp'], unit='ms')
    return df

3. Calculate MACD

The calculate_macd function computes the MACD (Moving Average Convergence Divergence) indicator.

def calculate_macd(df):
    macd = ta.trend.MACD(df['close'])
    df['macd'] = macd.macd()
    df['signal'] = macd.macd_signal()
    df['macd_hist'] = macd.macd_diff()

4. Calculate RSI

The calculate_rsi function computes the RSI (Relative Strength Index) indicator.

def calculate_rsi(df):
    rsi = ta.momentum.RSIIndicator(df['close'], window=14)
    df['rsi'] = rsi.rsi()

5. Detect Bullish Divergence

The detect_bullish_divergence function checks for bullish divergence based on MACD and RSI indicators.

def detect_bullish_divergence(df):
    bullish_divergence_macd = False
    bullish_divergence_rsi = False
    
    macd_lows = df.loc[df['macd_hist'] < 0, 'macd_hist']
    price_lows = df.loc[df['macd_hist'] < 0, 'close']
    if len(macd_lows) >= 2 and price_lows.iloc[-1] > price_lows.iloc[-2] and macd_lows.iloc[-1] < macd_lows.iloc[-2]:
        bullish_divergence_macd = True
    
    rsi_lows = df.loc[df['rsi'] < 30, 'rsi']
    if len(rsi_lows) >= 2 and df['close'].iloc[-1] > df['close'].iloc[-len(rsi_lows)] and rsi_lows.iloc[-1] < rsi_lows.iloc[-len(rsi_lows)]:
        bullish_divergence_rsi = True
    
    return bullish_divergence_macd and bullish_divergence_rsi

6. Analyze Symbols

The script fetches the list of available symbols from Binance, analyzes each one for bullish divergence, and prints the symbols that exhibit bullish divergence.

markets = exchange.load_markets()
symbols = [symbol for symbol in markets.keys() if '/USDT' in symbol]

bullish_divergence_symbols = []

for symbol in symbols:
    try:
        df = fetch_ohlcv(symbol)
        calculate_macd(df)
        calculate_rsi(df)
        
        if detect_bullish_divergence(df):
            bullish_divergence_symbols.append(symbol)
    except Exception as e:
        print(f"Could not analyze {symbol}: {e}")

print("Symbols with bullish divergence:", bullish_divergence_symbols)

Repository

The code is available at GitHub.

License

This project is licensed under the MIT License.

This README.md provides an overview of the script, its features, prerequisites, installation steps, and a detailed explanation of each part of the script.