# Buggy code
def hyperopt_loss_function(
    results: DataFrame,
    trade_count: int,
    min_date: datetime,
    max_date: datetime,
    *args,
    **kwargs,
) -> float:
    """
    Objective function, returns smaller number for more optimal results.

    Uses Sharpe Ratio calculation.
    """
    total_profit = results.profit_percent
    days_period = (max_date - min_date).days

    # adding slippage of 0.1% per trade
    total_profit = total_profit - 0.0005
    expected_yearly_return = total_profit.sum() / days_period

    if np.std(total_profit) != 0.0:
        sharp_ratio = expected_yearly_return / np.std(total_profit) * np.sqrt(365)
    else:
        # Define high (negative) sharpe ratio to be clear that this is NOT optimal.
        sharp_ratio = -20.0

    # print(expected_yearly_return, np.std(total_profit), sharp_ratio)
    return -sharp_ratio


# Traceback (Exception)
2020-02-20 22:47:28,025 - freqtrade - ERROR - Fatal exception!
Traceback (most recent call last):
File "/opt/tradebot/freqtrade/.env/lib/python3.7/site-packages/talib/__init__.py", line 20, in wrapper
for arg in chain(args, kwargs.values())
StopIteration

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "/freqtrade/freqtrade/main.py", line 36, in main
return_code = args['func'](args)
File "/freqtrade/freqtrade/commands/optimize_commands.py", line 76, in start_hyperopt
hyperopt.start()
File "/freqtrade/freqtrade/optimize/hyperopt.py", line 488, in start
preprocessed = self.backtesting.strategy.tickerdata_to_dataframe(data)
File "/freqtrade/freqtrade/strategy/interface.py", line 448, in tickerdata_to_dataframe
for pair, pair_data in tickerdata.items()}
File "/freqtrade/freqtrade/strategy/interface.py", line 448, in <dictcomp>
for pair, pair_data in tickerdata.items()}
File "/freqtrade/freqtrade/strategy/interface.py", line 464, in advise_indicators
return self.populate_indicators(dataframe, metadata)
File "/freqtrade/user_data/strategies/MyDev.py", line 205, in populate_indicators
dataframe['mfi'] = ta.MFI(dataframe)
File "talib/_abstract.pxi", line 352, in talib._ta_lib.Function.__call__
File "talib/_abstract.pxi", line 383, in talib._ta_lib.Function.__call_function
File "/opt/tradebot/freqtrade/.env/lib/python3.7/site-packages/talib/__init__.py", line 24, in wrapper
return func(*args, **kwargs)
File "talib/_func.pxi", line 8454, in talib._ta_lib.MFI
Exception: volume is not double

# Fixed code
def hyperopt_loss_function(
    results: DataFrame,
    trade_count: int,
    min_date: datetime,
    max_date: datetime,
    *args,
    **kwargs,
) -> float:
    """
    Objective function, returns smaller number for more optimal results.

    Uses Sharpe Ratio calculation.
    """
    total_profit = results["profit_percent"]
    days_period = (max_date - min_date).days

    # adding slippage of 0.1% per trade
    total_profit = total_profit - 0.0005
    expected_returns_mean = total_profit.sum() / days_period
    up_stdev = np.std(total_profit)

    if np.std(total_profit) != 0.0:
        sharp_ratio = expected_returns_mean / up_stdev * np.sqrt(365)
    else:
        # Define high (negative) sharpe ratio to be clear that this is NOT optimal.
        sharp_ratio = -20.0

    # print(expected_returns_mean, up_stdev, sharp_ratio)
    return -sharp_ratio