AAPL_Triple_SMA_Crossover.py

# 1) IMPORT LIBRARIES
import yfinance as yf               # to fetch historical market data
import pandas as pd                # for DataFrame operations
import matplotlib.pyplot as plt    # for plotting

# 2) DOWNLOAD Apple DATA AND BUILD INITIAL DF
#    We directly assign the downloaded DataFrame to `df`
df = yf.download(
    tickers='AAPL',
    start='2020-01-01',
    end='2025-04-01',
    progress=False
)

# 3) KEEP ONLY CLOSE PRICE
df = df[['Close']].rename(columns={'Close':'close'})  
#    Now df has one column: 'close'

# 4) CALCULATE MOVING AVERAGES IN-PLACE
df['sma5'] = df['close'].rolling(window=5).mean()   # fast
df['sma10'] = df['close'].rolling(window=10).mean()   # medium
df['sma15'] = df['close'].rolling(window=15).mean()   # slow
df = df.dropna()

# GENERATE ENTRY/EXIT SIGNALS
df['signal'] = 0
#  fast > med & fast > slow → potential buy zone
long_zone  = (df['sma5'] > df['sma10']) & (df['sma5'] > df['sma15']) & (df['sma10'] > df['sma15'])
#  fast < med & fast < slow → potential sell zone
short_zone = (df['sma5'] < df['sma10']) & (df['sma5'] < df['sma15']) & (df['sma10'] < df['sma15'])
#  when zone turns True from False → signal
df.loc[ long_zone & ~long_zone.shift(1).fillna(False), 'signal'] =  1
df.loc[short_zone & ~short_zone.shift(1).fillna(False), 'signal'] = -1

# CALCULATE RETURNS
df['market_ret']   = df['close'].pct_change()                # daily market return
df['strategy_ret'] = df['signal'].shift(1) * df['market_ret']  # apply yesterday’s signal today

# CUMULATIVE RETURNS
df['cum_market']   = (1 + df['market_ret']).cumprod()
df['cum_strategy'] = (1 + df['strategy_ret']).cumprod()

# PLOT PRICE & SMAs
plt.figure(figsize=(14, 6))
plt.plot(df.index, df['close'],   label='Close', color='black', linewidth=1)
plt.plot(df.index, df['sma5'],   label='5-day SMA', color='red',   linewidth=1)
plt.plot(df.index, df['sma10'],   label='10-day SMA', color='green', linewidth=1)
plt.plot(df.index, df['sma15'],   label='15-day SMA', color='purple',linewidth=1)
plt.title('AAPL Price & Triple SMA Crossover (5/10/15)')
plt.xlabel('Date'); plt.ylabel('Price (USD)')
plt.legend(); plt.grid(True); plt.tight_layout()
plt.show()