def METHOD_NAME(default_conf, hyperopt_results, lossfunction) -> None:
    results_over = hyperopt_results.copy()
    results_over['profit_abs'] = hyperopt_results['profit_abs'] * 2 + 0.2
    results_over['profit_ratio'] = hyperopt_results['profit_ratio'] * 2
    results_under = hyperopt_results.copy()
    results_under['profit_abs'] = hyperopt_results['profit_abs'] / 2 - 0.2
    results_under['profit_ratio'] = hyperopt_results['profit_ratio'] / 2
    default_conf.update({'hyperopt_loss': lossfunction})
    hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
    correct = hl.hyperopt_loss_function(
        hyperopt_results,
        trade_count=len(hyperopt_results),
        min_date=datetime(2019, 1, 1),
        max_date=datetime(2019, 5, 1),
        config=default_conf,
        processed=None,
        backtest_stats={'profit_total': hyperopt_results['profit_abs'].sum()}
    )
    over = hl.hyperopt_loss_function(
        results_over,
        trade_count=len(results_over),
        min_date=datetime(2019, 1, 1),
        max_date=datetime(2019, 5, 1),
        config=default_conf,
        processed=None,
        backtest_stats={'profit_total': results_over['profit_abs'].sum()}
    )
    under = hl.hyperopt_loss_function(
        results_under,
        trade_count=len(results_under),
        min_date=datetime(2019, 1, 1),
        max_date=datetime(2019, 5, 1),
        config=default_conf,
        processed=None,
        backtest_stats={'profit_total': results_under['profit_abs'].sum()}
    )
    assert over < correct
    assert under > correct