Technical Analysis - MACD, RSI

[s2t2]

import talib
import pandas as pd

# Assuming you already have a DataFrame 'df' with a 'Close' column
# RSI
df['RSI'] = talib.RSI(df['Close'], timeperiod=14)

# MACD
df['MACD'], df['MACD_Signal'], df['MACD_Hist'] = talib.MACD(
    df['Close'],
    fastperiod=12,
    slowperiod=26,
    signalperiod=9
)

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def compute_MACD(df, fast=12, slow=26, signal=9, column='Close'):
    """
    Computes the MACD, MACD signal, and MACD histogram for the DataFrame.
    Returns new columns: 'MACD', 'MACD_Signal', and 'MACD_Hist'.
    """
    df = df.copy()  # to avoid modifying the original DataFrame
    
    # Calculate the EMAs
    df['EMA_fast'] = df[column].ewm(span=fast, adjust=False).mean()
    df['EMA_slow'] = df[column].ewm(span=slow, adjust=False).mean()
    
    # MACD line
    df['MACD'] = df['EMA_fast'] - df['EMA_slow']
    
    # MACD Signal line
    df['MACD_Signal'] = df['MACD'].ewm(span=signal, adjust=False).mean()
    
    # MACD Histogram
    df['MACD_Hist'] = df['MACD'] - df['MACD_Signal']
    
    return df

df = compute_MACD(df, fast=12, slow=26, signal=9, column='Close')
print(df[['Close','MACD','MACD_Signal','MACD_Hist']])

def compute_RSI(df, period=14, column='Close'):
    """
    Computes the RSI for a given DataFrame using the specified column for prices.
    Returns a new column 'RSI' in the DataFrame.
    """
    df = df.copy()  # to avoid modifying the original DataFrame
    delta = df[column].diff(1)

    # Separate positive and negative price changes
    gain = delta.clip(lower=0)
    loss = -1 * delta.clip(upper=0)

    # Use exponential moving average for smoothing
    avg_gain = gain.ewm(com=period - 1, min_periods=period).mean()
    avg_loss = loss.ewm(com=period - 1, min_periods=period).mean()

    # Calculate RS and RSI
    rs = avg_gain / avg_loss
    df['RSI'] = 100 - (100 / (1 + rs))
    
    return df

df = compute_RSI(df, period=14, column='Close')
print(df)