def select_money(funddf):
fund_sharpe = fi.fund_sharp_annual(funddf)
codes = []
tag = {}
tag['sharpe1'] = fund_sharpe[0][0]
codes.append(fund_sharpe[0][0])
tag['sharpe2'] = fund_sharpe[1][0]
codes.append(fund_sharpe[0][0])
return codes, tag
def select_bond(funddf, fund_tags):
ratebond_codes = fund_tags['ratebond']
credit_codes = fund_tags['creditbond']
convertible_codes = fund_tags['convertiblebond']
need_rate = True
need_credit = True
need_convertible = True
fund_sharpe = fi.fund_sharp_annual(funddf)
codes = []
tag = {}
for i in range(0, len(fund_sharpe)):
code = fund_sharpe[i][0]
if code in set(ratebond_codes) and need_rate:
codes.append(code)
need_largecap = False
tag['ratebond'] = code
#print code, i
continue
if code in set(credit_codes) and need_credit:
codes.append(code)
need_credit = False
tag['creditbond'] = code
#print code, i
continue
if code in set(convertible_codes) and need_convertible:
codes.append(code)
need_convertible = False
tag['convertiblebond'] = code
#print code, i
continue
#print fund_sharpe
#print codes
return codes, tag
def bondfundfilter(start_date, end_date):
indicator = {}
funddf = data.bond_value(start_date, end_date)
indexdf = data.bond_index_value(start_date, end_date, 'H11001.CSI')
#按照基金创立时间过滤
setuptime_data = fundsetuptimefilter(funddf.columns, start_date, data.bond_establish_data())
#print setuptime_data
#按照jensen测度过滤
jensen_data = jensenfilter(funddf, indexdf, rf, 0.5)
#jensen_data = sf.jensenfilter(funddf, indexdf, rf, 1.0)
#按照索提诺比率过滤
sortino_data = sortinofilter(funddf, rf, 0.5)
#sortino_data = sf.sortinofilter(funddf, rf, 1.0)
#按照ppw测度过滤
ppw_data = ppwfilter(funddf, indexdf, rf, 0.5)
#ppw_data = sf.ppwfilter(funddf, indexdf, rf, 1.0)
#print ppw_data
stability_data = stabilityfilter(funddf, 2.0 / 3)
#stability_data = sf.stabilityfilter(funddf, 1.0)
sharpe_data = fi.fund_sharp_annual(funddf)
#print stability_data
#print 'jensen'
jensen_dict = {}
for k,v in jensen_data:
jensen_dict[k] = v
#print k, v
#print
#print 'sortino'
sortino_dict = {}
for k,v in sortino_data:
sortino_dict[k] = v
#print k,v
#print
#print 'ppw'
ppw_dict = {}
for k,v in ppw_data:
ppw_dict[k] = v
#print k,v
#print
#print 'statbility'
stability_dict = {}
for k,v in stability_data:
stability_dict[k] = v
#print k,v
sharpe_dict = {}
for k,v in sharpe_data:
sharpe_dict[k] = v
setuptime_set = set(setuptime_data)
jensen_set = set()
for k, v in jensen_data:
jensen_set.add(k)
sortino_set = set()
for k, v in sortino_data:
sortino_set.add(k)
ppw_set = set()
for k, v in ppw_data:
ppw_set.add(k)
stability_set = set()
for k, v in stability_data:
stability_set.add(k)
codes = []
for code in setuptime_set:
if (code in jensen_set) and (code in sortino_set) and (code in ppw_set) and (code in stability_set):
codes.append(code)
for code in codes:
ind = indicator.setdefault(code, {})
ind['sharpe'] = sharpe_dict[code]
ind['jensen'] = jensen_dict[code]
ind['sortino'] = sortino_dict[code]
ind['ppw'] = ppw_dict[code]
ind['stability'] = stability_dict[code]
indicator_set = set()
for code in setuptime_set:
indicator_set.add(code)
indicator_codes = []
indicator_datas = []
for code in indicator_set:
indicator_codes.append(code)
indicator_datas.append([sharpe_dict.setdefault(code, None), jensen_dict.setdefault(code, None), sortino_dict.setdefault(code, None), ppw_dict.setdefault(code, None), stability_dict.setdefault(code, None)])
indicator_df = pd.DataFrame(indicator_datas, index = indicator_codes, columns=['sharpe', 'jensen', 'sortino', 'ppw', 'stability'])
indicator_df.to_csv('./tmp/bond_indicator_' + end_date + '.csv')
f = open('./tmp/bondfilter_codes_' + end_date + '.csv','w')
for code in codes:
f.write(str(code) + '\n')
f.flush()
f.close()
return codes, indicator
#按照基金创立时间过滤
setuptime_data = sf.fundsetuptimefilter(funddf.columns, start_date, data.establish_data())
#按照jensen测度过滤
jensen_data = sf.jensenfilter(funddf, indexdf, const.rf, 1.0)
#按照索提诺比率过滤
sortino_data = sf.sortinofilter(funddf, const.rf, 1.0)
#按照ppw测度过滤
ppw_data = sf.ppwfilter(funddf, indexdf, const.rf, 1.0)
#print ppw_data
stability_data = sf.stabilityfilter(funddf, 3.0 / 3)
sharpe_data = fi.fund_sharp_annual(funddf)
jensen_dict = {}
for k,v in jensen_data:
jensen_dict[k] = v
#print k, v
#print
#print 'sortino'
sortino_dict = {}
for k,v in sortino_data:
sortino_dict[k] = v
#print k,v
#print
def fundfilter(start_date, end_date):
indicator = {}
funddf = data.fund_value(start_date, end_date)
#print 'hehe'
#print funddf['000457.OF']
#print funddf['163001.OF'].to_csv('./tmp/163001.csv')
indexdf = data.index_value(start_date, end_date, '000300.SH')
#按照规模过滤
scale_data = sf.scalefilter(2.0 / 3)
#scale_data = sf.scalefilter(1.0)
#print scale_data
#按照基金创立时间过滤
setuptime_data = sf.fundsetuptimefilter(funddf.columns, start_date, data.establish_data())
#print setuptime_data
#按照jensen测度过滤
jensen_data = sf.jensenfilter(funddf, indexdf, rf, 0.5)
#jensen_data = sf.jensenfilter(funddf, indexdf, rf, 1.0)
#按照索提诺比率过滤
sortino_data = sf.sortinofilter(funddf, rf, 0.5)
#sortino_data = sf.sortinofilter(funddf, rf, 1.0)
#按照ppw测度过滤
ppw_data = sf.ppwfilter(funddf, indexdf, rf, 0.5)
#ppw_data = sf.ppwfilter(funddf, indexdf, rf, 1.0)
#print ppw_data
stability_data = sf.stabilityfilter(funddf, 2.0 / 3)
#stability_data = sf.stabilityfilter(funddf, 1.0)
sharpe_data = fi.fund_sharp_annual(funddf)
#print stability_data
#print 'jensen'
jensen_dict = {}
for k,v in jensen_data:
jensen_dict[k] = v
#print k, v
#print
#print 'sortino'
sortino_dict = {}
for k,v in sortino_data:
sortino_dict[k] = v
#print k,v
#print
#print 'ppw'
ppw_dict = {}
for k,v in ppw_data:
ppw_dict[k] = v
#print k,v
#print
#print 'statbility'
stability_dict = {}
for k,v in stability_data:
stability_dict[k] = v
#print k,v
sharpe_dict = {}
for k,v in sharpe_data:
sharpe_dict[k] = v
'''
codes = list(jensen_dict.keys())
codes.sort()
jensen_array = []
sortino_array = []
ppw_array = []
stability_array = []
for code in codes:
jensen_array.append(jensen_dict[code] if jensen_dict.has_key(code) else 0)
sortino_array.append(sortino_dict[code] if sortino_dict.has_key(code) else 0)
ppw_array.append(ppw_dict[code] if ppw_dict.has_key(code) else 0)
stability_array.append(stability_dict[code] if stability_dict.has_key(code) else 0)
indicators = {'code':codes, 'jensen':jensen_array, 'sortino':sortino_array, 'ppw':ppw_array,'stability':stability_array}
frame = pd.DataFrame(indicators)
frame.to_csv('./wind/fund_indicator.csv')
'''
scale_set = set()
for k, v in scale_data:
scale_set.add(k)
setuptime_set = set(setuptime_data)
jensen_set = set()
for k, v in jensen_data:
jensen_set.add(k)
sortino_set = set()
for k, v in sortino_data:
sortino_set.add(k)
ppw_set = set()
for k, v in ppw_data:
ppw_set.add(k)
stability_set = set()
for k, v in stability_data:
stability_set.add(k)
#print 'jensen', '000457.OF' in jensen_set
#print 'sortino', '000457.OF' in sortino_set
#print 'ppw', '000457.OF' in ppw_set
#print 'stability', '000457.OF' in stability_set
codes = []
for code in scale_set:
if (code in setuptime_set) and (code in jensen_set) and (code in sortino_set) and (code in ppw_set) and (code in stability_set):
codes.append(code)
for code in codes:
ind = indicator.setdefault(code, {})
ind['sharpe'] = sharpe_dict[code]
ind['jensen'] = jensen_dict[code]
ind['sortino'] = sortino_dict[code]
ind['ppw'] = ppw_dict[code]
ind['stability'] = stability_dict[code]
'''
indicator_str = "%s,%f,%f,%f,%f,%f\n"
f = open('./tmp/indicator.csv','w')
f.write("code,sharpe,jensen,sortino,ppw,stability\n")
for code in codes:
f.write(indicator_str % (code, sharpe_dict[code],jensen_dict[code], sortino_dict[code], ppw_dict[code], stability_dict[code]))
#print code,jensen_dict[code], sortino_dict[code], ppw_dict[code], stability_dict[code]
f.flush()
f.close()
'''
#按照业绩持续性过滤
#stability_data = sf.stabilityfilter(funddf[codes], 2.0 / 3)
#print stability_data
#codes = []
#for k, v in stability_data:
# codes.append(k)
return codes, indicator
ts.append(key)
#fund_codes = list(tmp_codes)
#all_funddf = data.fund_value(start_date, end_date)
#fund_codes = list(indicator.keys())
#allocation_funddf = data.fund_value(allocation_start_date, end_date)
#allocation_funddf = allocation_funddf[fund_codes]
####################################################################
future_funddf = data.fund_value(end_date, future_end_date)
future_funddf = future_funddf[fund_pool]
future_codes = []
future_funddf_sharp = fi.fund_sharp_annual(future_funddf)
end_n = (int)(len(future_funddf_sharp) * 0.25)
start_n = (int)(len(future_funddf_sharp) * 0.125)
for n in range(start_n, end_n):
future_codes.append(future_funddf_sharp[n][0])
#fund_codes = future_codes
#####################################################################
return_data = fi.fund_return(allocation_funddf)
risk_data = fi.fund_risk(allocation_funddf)
return_dict = {}
for k,v in return_data:
return_dict[k] = v
risk_dict = {}
for k,v in risk_data:
def select_stock(funddf, fund_tags):
largecap_codes = fund_tags['largecap']
smallcap_codes = fund_tags['smallcap']
risefitness_codes = fund_tags['risefitness']
declinefitness_codes = fund_tags['declinefitness']
oscillationfitness_codes = fund_tags['oscillationfitness']
growthfitness_codes = fund_tags['growthfitness']
valuefitness_codes = fund_tags['valuefitness']
need_largecap = True
need_smallcap = True
need_risefitness = True
need_declinefitness = True
need_oscillationfitness = True
need_growthfitness = True
need_valuefitness = True
fund_sharpe = fi.fund_sharp_annual(funddf)
codes = []
tag = {}
for i in range(0, len(fund_sharpe)):
code = fund_sharpe[i][0]
if code in set(largecap_codes) and need_largecap:
codes.append(code)
need_largecap = False
tag['largecap'] = code
#print code, i
continue
if code in set(smallcap_codes) and need_smallcap:
codes.append(code)
need_smallcap = False
tag['smallcap'] = code
#print code, i
continue
if code in set(risefitness_codes) and need_risefitness:
codes.append(code)
need_risefitness = False
tag['rise'] = code
#print code, i
continue
if code in set(declinefitness_codes) and need_declinefitness:
codes.append(code)
need_declinefitness = False
tag['decline'] = code
#print code, i
continue
if code in set(oscillationfitness_codes) and need_oscillationfitness:
codes.append(code)
need_oscillationfitness = False
tag['oscillation'] = code
#print code, i
continue
if code in set(growthfitness_codes) and need_growthfitness:
codes.append(code)
need_growthfitness = False
tag['growth'] = code
#print code, i
continue
if code in set(valuefitness_codes) and need_valuefitness:
codes.append(code)
need_valuefitness = False
tag['value'] = code
#print code, i
continue
#print fund_sharpe
#print codes
return codes, tag