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factor model

Project description

This programme is built for back testing alpha factors. Each factor is tested alone.

sample with a single processor

from single_factor_model.single import preprocessing,back_testing,ic_measurement,ic_measure_summary,back_test_summary,bt_figure

parms={'factor_path':'factor_folder_path'# file name: xxx_yyyymmdd.csv columns(no order): StkID,factor1,factor2,...
      ,'ind_path':'industry_folder_path'# file name: xxx_yyyymmdd.csv columns(no order): StkID,level1,level2,...
      ,'price_path':'market_folder_path'# file name: xxx_yyyymmdd.csv columns(no order): StkID,vwap,adjfactor,susp_days,maxupordown
      ,'cap_path':'cap_folder_path' # file name: xxx_yyyymmdd.csv columns(no order): StkID,SRcap
      ,'index_weight_path':'index_weight_folder_path'  file name: xxx_yyyymmdd.csv columns(no header): StkID,weight
      ,'sub_factor':None # or list of factors of interest
      ,'flag':'monthly' # monthly or daily
      ,'day_lag':1 # lag of days to receive these factors
      ,'ind_mapping_flag':False # whether to use number to represent industry, this could spead up calculation
parms2={'n':5 # portfolio number
        ,'silent':True # whether to output detail
parms3={'window':3 # window for regression sample data
        ,'half_decay':200 # weight for regression parameters
T=back_testing(D) # back testing
T2=ic_measurement(D) # regression

Dict4=bt_figure(B,show_plot=True) # plot backtesting result


from RNWS import write

sample with multi processors

nearly same as single processor sample. Just replace single_factor_model.single to single_factor_model.multi. Then you can address 'processors' in parms and parms2 and parms3 as processors. Also if __name__=='__main__': is needed to run programme on Windows.

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