SMA_TMA.py

# 1) IMPORT LIBRARIES
import yfinance as yf               # to fetch historical stock data
import pandas as pd                # for DataFrame & rolling calculations
import matplotlib.pyplot as plt    # for plotting

# 2) DOWNLOAD TESLA (TSLA) DATA
#    - 'start' is inclusive, 'end' is exclusive
tesla = yf.download(
    tickers='TSLA',
    start='2023-01-01',
    end='2025-04-25',
    progress=False
)

# 3) EXTRACT CLOSE PRICE SERIES
close = tesla['Close']

# 4) CALCULATE 30-DAY SIMPLE MOVING AVERAGE (SMA)
sma30 = close.rolling(window=30).mean()

# 5) CALCULATE 30-DAY TRIANGULAR MOVING AVERAGE (TMA)
#    TMA = SMA of the SMA
tma30 = sma30.rolling(window=30).mean()

# 6) PLOT CLOSE, SMA AND TMA
plt.figure(figsize=(12, 6))

# raw close price
plt.plot(close.index, close, label='Close Price', linewidth=1)

# 30-day SMA
plt.plot(sma30.index, sma30, label='30-Day SMA', linewidth=1)

# 30-day TMA
plt.plot(tma30.index, tma30, label='30-Day TMA', linewidth=1)

# 7) FORMAT THE PLOT
plt.title('Tesla Close Price with 30-Day SMA & TMA\n2023–2025')
plt.xlabel('Date')
plt.ylabel('Price (USD)')
plt.legend()
plt.grid(True)
plt.tight_layout()

# 8) DISPLAY THE PLOT
plt.show()