3. Analyzers.Returns - ValueError: math domain error
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Analyzers.Returns - ValueError: math domain error

  • C

    I often face an error using this analyzer during optimization.

    cerebro.addanalyzer(bt.analyzers.Returns, _name='return')

    Full traceback:

    multiprocessing.pool.RemoteTraceback:

Traceback (most recent call last):
  File "C:\ProgramData\Anaconda3\lib\multiprocessing\pool.py", line 119, in worker
    result = (True, func(*args, **kwds))
  File "C:\ProgramData\Anaconda3\lib\site-packages\backtrader\cerebro.py", line 1007, in __call__
    return self.runstrategies(iterstrat, predata=predata)
  File "C:\ProgramData\Anaconda3\lib\site-packages\backtrader\cerebro.py", line 1301, in runstrategies
    strat._stop()
  File "C:\ProgramData\Anaconda3\lib\site-packages\backtrader\strategy.py", line 464, in _stop
    analyzer._stop()
  File "C:\ProgramData\Anaconda3\lib\site-packages\backtrader\analyzer.py", line 200, in _stop
    self.stop()
  File "C:\ProgramData\Anaconda3\lib\site-packages\backtrader\analyzers\returns.py", line 128, in stop
    math.log(self._value_end / self._value_start))
ValueError: math domain error

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "Optimize Client.py", line 156, in <module>
    bt_tools.optimization(strategy, params)
  File "..\core.py", line 327, in optimization
    def optimization_results_handler(self, results_raw):
  File "C:\ProgramData\Anaconda3\lib\site-packages\backtrader\cerebro.py", line 1143, in run
    for r in pool.imap(self, iterstrats):
  File "C:\ProgramData\Anaconda3\lib\multiprocessing\pool.py", line 735, in next
    raise value
ValueError: math domain error
    0

  • Just as a guess - looks like it comes frommath.log which means that self._value_end / self._value_start is less than or equal to zero. So check the equity numbers, maybe it goes to zero some how.

    1
  • C

    to fix this added two lines:

            # Compound return
        if self._value_end <= 0:
            self._value_end = 0.00001

        self.rets['rtot'] = rtot = (
            math.log(self._value_end / self._value_start))

    it may be not the best solution, but it works

    0
  • B
    administrators

    The proper value should/would be float('-inf'), which is what the logarithmic function tends to when it approaches zero.

    There is a fix in the development branch at: https://github.com/backtrader/backtrader/commit/57545348763060e1077654f9a94ca71c090f0d2c

    0