import time # Record start time start_time = time.time() # Record path path = r'C:\\Users\\rambocha\\Desktop\\Intern_UCLA_AFP_2020' # What is the cut? cut = 0.10 # Consider only after 2009 post_2009 = True # Value weighted stocks_month_vw = cf.prep_monthly_rtn(path, cut, path + '\\Data\\fundamental_mods\\monthly_fund_rtn_val_wt_cut_' + str(0.1) + '.csv', post_2009) # Inverse value weighted stocks_month_ivw = cf.prep_monthly_rtn(path, cut, path + '\\Data\\fundamental_mods\\monthly_fund_rtn_inv_val_wt_cut_' + str(0.1) + '.csv', post_2009) # Clusters; transitive component equal weighted stocks_month_clu = cf.prep_monthly_rtn(path, cut, path + '\\Data\\fundamental_mods\\monthly_fund_rtn_cluster_cut_' + str(0.1) + '.csv', post_2009) print(0.25 * int((time.time() - start_time)/15), 'minutes so far...') # Get Fama-French data FF, RF = cf.prep_FF_monthly(path) # Use functions get_mom_ind = lambda data, signal, wt: cf.get_mom_ind(data, RF, 0, signal, monthly = True, sig_rtn = False, wt = wt) get_mom_fund = lambda data, signal: cf.get_mom_fund(data, RF, 0, signal, monthly = True, sig_rtn = False) get_mom_diff = lambda data, signal, wt: cf.get_mom_diff(data, RF, 0, signal, monthly = True, sig_rtn = False, wt = wt)
# What is the cut?
cut = 0.10
# Consider only after 2009?
post_2009 = True
# Where are the fundamental returns?
file = path + '\\Data\\monthly_fundamental_returns_fuller_cut_' + str(
cut) + '.csv'
# If file isn't none, in which folder should everything be place?
folder = None
# Get the month return data
stocks_month = cf.prep_monthly_rtn(path, cut, file, post_2009)
# Get Fama-French data
FF, RF = cf.prep_FF_monthly(path)
# Get duration
duration = (stocks_month['DATE'].dt.year).max() - (
stocks_month['DATE'].dt.year).min() + 1
# Use functions
get_mom_ind = lambda signal: cf.get_mom_ind(
stocks_month, RF, 0, signal, monthly=True, sig_rtn=True)
get_mom_fund = lambda signal: cf.get_mom_fund(
stocks_month, RF, 0, signal, monthly=True, sig_rtn=True)
get_mom_diff = lambda signal: cf.get_mom_diff(
stocks_month, RF, 0, signal, monthly=True, sig_rtn=True)
