Code Editor for analytics.py

import pandas as pd
import numpy as np

def calculate_moving_averages(data, period):
    """
    Calculate simple moving average
    """
    return data['Close'].rolling(window=period).mean()

def calculate_volatility(prices, period=30):
    """
    Calculate historical volatility (annualized)
    """
    returns = prices.pct_change().dropna()
    volatility = returns.tail(period).std() * np.sqrt(252) * 100  # Annualized
    return volatility

def calculate_rsi(prices, period=14):
    """
    Calculate Relative Strength Index
    """
    delta = prices.diff()
    gain = (delta.where(delta > 0, 0)).rolling(window=period).mean()
    loss = (-delta.where(delta < 0, 0)).rolling(window=period).mean()
    
    rs = gain / loss
    rsi = 100 - (100 / (1 + rs))
    
    return rsi

def calculate_bollinger_bands(prices, period=20, std_dev=2):
    """
    Calculate Bollinger Bands
    """
    ma = prices.rolling(window=period).mean()
    std = prices.rolling(window=period).std()
    
    upper_band = ma + (std * std_dev)
    lower_band = ma - (std * std_dev)
    
    return upper_band, ma, lower_band

def calculate_macd(prices, fast=12, slow=26, signal=9):
    """
    Calculate MACD (Moving Average Convergence Divergence)
    """
    ema_fast = prices.ewm(span=fast).mean()
    ema_slow = prices.ewm(span=slow).mean()
    
    macd_line = ema_fast - ema_slow
    signal_line = macd_line.ewm(span=signal).mean()
    histogram = macd_line - signal_line
    
    return macd_line, signal_line, histogram

def calculate_support_resistance(data, window=20):
    """
    Calculate basic support and resistance levels
    """
    highs = data['High'].rolling(window=window).max()
    lows = data['Low'].rolling(window=window).min()
    
    return highs, lows