def METHOD_NAME(
    weights_as_list: list, SR_list: list, avg_correlation: float, years_of_data: float
) -> list:
    if len(weights_as_list) == 1:
        return weights_as_list
    avg_SR = np.nanmean(SR_list)
    relative_SR_list = [SR - avg_SR for SR in SR_list]
    multipliers = [
        float(multiplier_from_relative_SR(relative_SR, avg_correlation, years_of_data))
        for relative_SR in relative_SR_list
    ]
    new_weights = list(np.array(weights_as_list) * np.array(multipliers))
    norm_new_weights = norm_weights(new_weights)
    return norm_new_weights