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  1. M

    pandas too slow for event driven backtesting

    not everyone knows how to write c/c++. python is not the most efficient way, but it is convenient.
  2. M

    pandas too slow for event driven backtesting

    I know the datetime64 data type in numpy. But this is not helping. I am not trying to perform arithmatic calculation on datetime. Just trying to find a better way to get time series data during backtesting:(
  3. M

    pandas too slow for event driven backtesting

    yes, I think numpy ndarray is the correct direction. I have timed the speed of numpy and pandas indexing. For numpy, indexing takes at the level of 100 nanoseconds to 1microsecond but for pandas the labeled indexing method .loc[] could take 100 microseconds to up to 10 milliseconds. This is...
  4. M

    pandas too slow for event driven backtesting

    Hi looking for some suggestions for how to store minute resolution data in memory for a better performance for backtesting. I am writing my own event-based backtesting framework in python, just for fun. The data is read into memory as a whole, stored as a pandas dataframe and then indexing will...
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