def create_daily_df_for_asset(trading_calendar, start_day, end_day,
                              interval=1):
    days = trading_calendar.sessions_in_range(start_day, end_day)
    days_count = len(days)
    days_arr = np.arange(days_count) + 2

    df = pd.DataFrame(
        {
            "open": days_arr + 1,
            "high": days_arr + 2,
            "low": days_arr - 1,
            "close": days_arr,
            "volume": days_arr * 100,
        },
        index=days,
    )

    if interval > 1:
        # only keep every 'interval' rows
        for idx, _ in enumerate(days_arr):
            if (idx + 1) % interval != 0:
                df["open"].iloc[idx] = 0
                df["high"].iloc[idx] = 0
                df["low"].iloc[idx] = 0
                df["close"].iloc[idx] = 0
                df["volume"].iloc[idx] = 0

    return df