def METHOD_NAME(
    to_symbol: str = "USD",
    from_symbol: str = "EUR",
    resolution: str = "d",
    interval: int = 5,
    start_date: str = "",
    end_date: str = "",
) -> pd.DataFrame:
    """Get historical forex data.
    Parameters
    ----------
    to_symbol : str
        To forex symbol
    from_symbol : str
        From forex symbol
    resolution : str, optional
        Resolution of data.  Can be "i", "d", "w", "m" for intraday, daily, weekly or monthly
    interval : int, optional
        Interval for intraday data
    start_date : str, optional
        Start date for data.
    end_date : str, optional
        End date for data.
    Returns
    -------
    pd.DataFrame
        Historical data for forex pair
    """
    d_res = {"i": "FX_INTRADAY", "d": "FX_DAILY", "w": "FX_WEEKLY", "m": "FX_MONTHLY"}
    url = f"https://www.alphavantage.co/query?function={d_res[resolution]}&from_symbol={from_symbol}"
    url += f"&to_symbol={to_symbol}&outputsize=full&apikey={get_current_user().credentials.API_KEY_ALPHAVANTAGE}"
    if resolution == "i":
        url += f"&interval={interval}min"
    r = request(url)
    response_json = r.json()
    if r.status_code != 200:
        return pd.DataFrame()
    df = pd.DataFrame()
    # If the returned data was unsuccessful
    if "Error Message" in response_json:
        console.print(response_json["Error Message"])
    elif "Note" in response_json:
        console.print(response_json["Note"])
    elif not response_json:
        console.print("No data found.\n")
    else:
        if "Meta Data" not in response_json and "Information" in response_json:
            console.print(response_json["Information"])
            return pd.DataFrame()
        key = list(response_json.keys())[1]
        df = pd.DataFrame.from_dict(response_json[key], orient="index")
        df.index = pd.to_datetime(df.index)
        if start_date and resolution != "i":
            df = df[df.index > start_date]
        if end_date and resolution != "i":
            df = df[df.index < end_date]
        if (df.index.hour != 0).any():
            # if intraday data, convert to local timezone
            df.index = df.index.tz_localize("UTC").tz_convert(get_user_timezone())
        df = df.rename(
            columns={
                "1. open": "Open",
                "2. high": "High",
                "3. low": "Low",
                "4. close": "Close",
            }
        )
        df.index = pd.DatetimeIndex(df.index)
        df = df[::-1]
    return df.astype(float)