import yfinance as yf


def download_stock_data(
    ticker, start_date, end_date, granularity
):
    # Download daily OHLC, volume, dividends, stock splits, and other data
    stock_data = yf.download(
        ticker, start=start_date, end=end_date, actions=True,
        interval=granularity
    )

    # Calculate the 5-day moving average
    stock_data['MA5'] = stock_data['Close'].rolling(window=5).mean()

    # Keep the relevant columns
    stock_data = stock_data[[
        'Open', 'High', 'Low', 'Close',
        'Volume', 'Dividends', 'Stock Splits', 'MA5'
    ]]

    # Extract ex-dividend date from the dividends column
    stock_data['Ex-Dividend'] = stock_data['Dividends'].shift(1)

    # Extract split ratio from the stock splits column
    stock_data['Split Ratio'] = stock_data['Stock Splits'].apply(
        lambda x: 1 / x if x != 0 else 1
    )

    # Drop rows with NaN values
    stock_data = stock_data.dropna()

    # Add a column for the asset (use the ticker symbol as an example)
    stock_data['Asset'] = ticker

    # rename columns to lowercase
    stock_data.columns = stock_data.columns.str.lower()
    # rename to snake case
    stock_data.columns = stock_data.columns.str.replace(' ', '_')

    stock_data = stock_data[[
        'open', 'high', 'low', 'close',
        'volume', 'ex-dividend', 'split_ratio', 'ma5',
        'asset'
    ]]
    stock_data = stock_data.resample(granularity.upper()).ffill()
    stock_data['date'] = stock_data.index
    return stock_data