def point_relative_normalization(series, reverse=False, last_value=None):
    """
    Computes the normalized value for the values of a
    given series by using the first element of the serie as p_0
    as a reference for each p_i.
    
    This technique comes from Siraj Raval's YouTube video
    "How to Predict Stock Prices Easily - Intro to Deep Learning #7",
    available at:
    
        https://www.youtube.com/watch?v=ftMq5ps503w
    
    Parameters
    ----------
    serie: list
        List with sequential values to use.
    
    reverse: bool, default True
        If the method should de-normalize data.
    
    last_value: int or float
        Used to de-normalize a dataset. Needs to 
        be passed if `reverse` is True.
    
    Returns
    -------
    result: list
        List with the normalized results.
    """
    if reverse:
        result = last_value * (series + 1)
    else:
        result = (series / series[0]) - 1

    return result