def save_dataview():
ds = RemoteDataService()
ds.init_from_config(data_config)
dv = DataView()
props = {'start_date': 20150101, 'end_date': 20170930, 'universe': '000905.SH',
'fields': ('turnover,float_mv,close_adj,pe,pb'),
'freq': 1}
dv.init_from_config(props, ds)
dv.prepare_data()
factor_formula = 'Cutoff(Standardize(turnover / 10000 / float_mv), 2)'
dv.add_formula('TO', factor_formula, is_quarterly=False)
factor_formula = 'Cutoff(Standardize(1/pb), 2)'
dv.add_formula('BP', factor_formula, is_quarterly=False)
factor_formula = 'Cutoff(Standardize(Return(close_adj, 20)), 2)'
dv.add_formula('REVS20', factor_formula, is_quarterly=False)
factor_formula = 'Cutoff(Standardize(Log(float_mv)), 2)'
dv.add_formula('float_mv_factor', factor_formula, is_quarterly=False)
factor_formula = 'Delay(Return(close_adj, 1), -1)'
dv.add_formula('NextRet', factor_formula, is_quarterly=False)
dv.save_dataview(folder_path=dataview_dir_path)
def save_dataview():
ds = RemoteDataService()
ds.init_from_config(data_config)
dv = DataView()
props = {
'start_date':
20170101,
'end_date':
20171030,
'universe':
'000300.SH',
'fields': (
'open,high,low,close,vwap,volume,turnover,sw1,'
# + 'pb,net_assets,'
+ 'eps_basic,total_mv,tot_profit,int_income'),
'freq':
1
}
dv.init_from_config(props, ds)
dv.prepare_data()
factor_formula = 'close >= Delay(Ts_Max(close, 20), 1)' # 20 days new high
factor_name = 'new_high'
dv.add_formula(factor_name, factor_formula, is_quarterly=False)
dv.add_formula('total_profit_growth',
formula='Return(tot_profit, 4)',
is_quarterly=True)
dv.save_dataview(folder_path=dataview_dir_path)
def test_save_dataview():
ds = RemoteDataService()
ds.init_from_config(data_config)
dv = DataView()
props = {
'start_date': 20170101,
'end_date': 20171001,
'universe': '000300.SH',
'fields': ('float_mv,pb,pe_ttm,sw2'),
'freq': 1
}
dv.init_from_config(props, ds)
dv.prepare_data()
factor_formula = 'GroupQuantile(-float_mv, sw2, 10)'
dv.add_formula('rank_mv', factor_formula, is_quarterly=False)
factor_formula = 'GroupQuantile(If(pb >= 0.2, pb, 100), sw2, 10)'
dv.add_formula('rank_pb', factor_formula, is_quarterly=False)
factor_formula = 'GroupQuantile(If(pe_ttm >= 3, pe_ttm, 9999.0), sw2, 10)'
dv.add_formula('rank_pe', factor_formula, is_quarterly=False)
dv.save_dataview(folder_path=dataview_dir_path)
def save_dataview():
ds = RemoteDataService()
ds.init_from_config(data_config)
dv = DataView()
props = {
'start_date': 20150101,
'end_date': 20171001,
'universe': '000300.SH',
'fields': 'volume,turnover,float_mv,pb,total_mv',
'freq': 1
}
dv.init_from_config(props, ds)
dv.prepare_data()
trade_status = dv.get_ts('trade_status')
mask_sus = trade_status == '停牌'
dv.append_df(mask_sus, 'suspended', is_quarterly=False)
dv.add_formula('not_index_member', '!index_member', is_quarterly=False)
dv.add_formula('limit_reached',
'Abs((open - Delay(close, 1)) / Delay(close, 1)) > 0.095',
is_quarterly=False)
dv.save_dataview(dataview_folder)
def save_dataview():
ds = RemoteDataService()
ds.init_from_config(data_config)
dv = DataView()
props = {
'start_date': 20150101,
'end_date': 20171001,
'universe': '000300.SH',
'fields': 'volume,turnover,float_mv,pb,total_mv',
'freq': 1
}
dv.init_from_config(props, ds)
dv.prepare_data()
# for convenience to check limit reachers
dv.add_formula('limit_reached',
'Abs((open - Delay(close, 1)) / Delay(close, 1)) > 0.095',
is_quarterly=False)
dv.add_formula('random', 'StdDev(volume, 20)', is_quarterly=False)
dv.add_formula('momentum', 'Return(close_adj, 20)', is_quarterly=False)
# dv.add_formula('size', '', is_quarterly=False)
dv.save_dataview(dataview_folder)
def save_data():
"""
This function fetches data from remote server and stores them locally.
Then we can use local data to do back-test.
"""
dataview_props = {'start_date': 20170101, # Start and end date of back-test
'end_date': 20171030,
'universe': UNIVERSE, # Investment universe and performance benchmark
'benchmark': '000905.SH',
'fields': 'high,low,close', # Data fields that we need
'freq': 1 # freq = 1 means we use daily data. Please do not change this.
}
# RemoteDataService communicates with a remote server to fetch data
ds = RemoteDataService()
# Use username and password in data_config to login
ds.init_from_config(data_config)
# DataView utilizes RemoteDataService to get various data and store them
dv = DataView()
dv.init_from_config(dataview_props, ds)
dv.prepare_data()
# 以9日为周期的KD线为例。首先须计算出最近9日的RSV值,即未成熟随机值,
# 计算公式为
# 9日RSV=(C-L9)÷(H9-L9)×100
# 式中,C为第9日的收盘价;L9为9日内的最低价;H9为9日内的最高价。
# K值=2/3×前一日K值+1/3×当日RSV
# D值=2/3×前一日K值+1/3×当日RSV
# J指标的计算公式为: J=3D—2K
factor_formula = '2/3*50 + (close-Ts_Min(low，5))/(Ts_Max(high，5)-Ts_Min(low，5)*100)'
dv.add_formula()
dv.save_dataview(folder_path=dataview_store_folder)
def save_dataview():
ds = RemoteDataService()
ds.init_from_config(data_config)
dv = DataView()
props = {'start_date': 20160101, 'end_date': 20171001, 'universe': '000300.SH',
'fields': 'volume,turnover',
'freq': 1}
dv.init_from_config(props, ds)
dv.prepare_data()
# for convenience to check limit reachers
dv.add_formula('limit_reached', 'Abs((open - Delay(close, 1)) / Delay(close, 1)) > 0.095', is_quarterly=False)
dv.add_formula('mask_limit_reached', 'limit_reached > 0', is_quarterly=False)
dv.add_formula('mask_index_member', '!(index_member > 0)', is_quarterly=False)
trade_status = dv.get_ts('trade_status')
mask_sus = trade_status == u'停牌'
dv.append_df(mask_sus, 'mask_sus', is_quarterly=False)
# dv.add_formula('size', '', is_quarterly=False)
dv.save_dataview(dataview_folder)
def save_data():
"""
This function fetches data from remote server and stores them locally.
Then we can use local data to do back-test.
"""
dataview_props = {
'start_date': 20170101, # Start and end date of back-test
'end_date': 20171030,
'universe': UNIVERSE, # Investment universe and performance benchmark
'benchmark': '000300.SH',
'fields': 'total_mv,turnover', # Data fields that we need
'freq':
1 # freq = 1 means we use daily data. Please do not change this.
}
# RemoteDataService communicates with a remote server to fetch data
ds = RemoteDataService()
# Use username and password in data_config to login
ds.init_from_config(data_config)
# DataView utilizes RemoteDataService to get various data and store them
dv = DataView()
dv.init_from_config(dataview_props, ds)
dv.prepare_data()
dv.save_dataview(folder_path=dataview_store_folder)
def prepare_dataview():
ds = RemoteDataService()
ds.init_from_config(data_config)
symbols = ['600036.SH', '000001.SZ']
dv_props = {'symbol': ','.join(symbols),
'start_date': backtest_props['start_date'],
'end_date': backtest_props['end_date'],
'benchmark': '000300.SH'}
dv = EventDataView()
dv.init_from_config(dv_props, ds)
dv.prepare_data()
import pandas as pd
# target security
diff_cols = ['open', 'high', 'low', 'close']
df0 = dv.get_symbol(symbols[0], fields=','.join(diff_cols))
df1 = dv.get_symbol(symbols[1], fields=','.join(diff_cols))
df_diff = df0 - df1
# calculate signal
df_signal = pd.concat([df0[['close']], df1[['close']], df_diff[['close']]], axis=1)
df_signal.columns = symbols + ['diff']
roll = df_signal['diff'].rolling(window=10)
df_signal.loc[:, 'signal'] = (df_signal['diff'] - roll.mean()) / roll.std()
dv.append_df_symbol(df_diff, '001.JZ')
dv.data_custom = df_signal
dv.save_dataview(dataview_dir_path)
def test_save_dataview():
ds = RemoteDataService()
ds.init_from_config(data_config)
dv = DataView()
props = {'start_date': 20150101, 'end_date': 20170930, 'universe': '000905.SH',
'fields': ('tot_cur_assets,tot_cur_liab,inventories,pre_pay,deferred_exp,'
'eps_basic,ebit,pe,pb,float_mv,sw1'),
'freq': 1}
dv.init_from_config(props, ds)
dv.prepare_data()
factor_formula = 'pe < 30'
dv.add_formula('pe_condition', factor_formula, is_quarterly=False)
factor_formula = 'pb < 3'
dv.add_formula('pb_condition', factor_formula, is_quarterly=False)
factor_formula = 'Return(eps_basic, 4) > 0'
dv.add_formula('eps_condition', factor_formula, is_quarterly=True)
factor_formula = 'Return(ebit, 4) > 0'
dv.add_formula('ebit_condition', factor_formula, is_quarterly=True)
factor_formula = 'tot_cur_assets/tot_cur_liab > 2'
dv.add_formula('current_condition', factor_formula, is_quarterly=True)
factor_formula = '(tot_cur_assets - inventories - pre_pay - deferred_exp)/tot_cur_liab > 1'
dv.add_formula('quick_condition', factor_formula, is_quarterly=True)
dv.add_formula('mv_rank', 'Rank(float_mv)', is_quarterly=False)
dv.save_dataview(folder_path=dataview_dir_path)
def test_dataview_universe():
ds = RemoteDataService()
ds.init_from_config(data_config)
dv = DataView()
props = {'start_date': 20170227, 'end_date': 20170327, 'universe': '000016.SH',
# 'symbol': 'rb1710.SHF,rb1801.SHF',
'fields': ('open,high,low,close,vwap,volume,turnover,'
+ 'sw1,zz2,'
+ 'roe,net_assets,'
+ 'total_oper_rev,oper_exp,tot_profit,int_income'
),
'freq': 1}
dv.init_from_config(props, ds)
dv.prepare_data()
data_bench = dv.data_benchmark.copy()
dv.data_benchmark = data_bench
try:
dv.data_benchmark = data_bench.iloc[3:]
except ValueError:
pass
dv.remove_field('roe,net_assets')
dv.remove_field('close')
def save_dataview():
ds = RemoteDataService()
ds.init_from_config(data_config)
dv = DataView()
props = {
'start_date': 20160101,
'end_date': 20171001,
'universe': '000300.SH',
'fields': 'volume,turnover',
'freq': 1
}
dv.init_from_config(props, ds)
dv.prepare_data()
# for convenience to check limit reachers
dv.add_formula('limit_reached',
'Abs((open - Delay(close, 1)) / Delay(close, 1)) > 0.095',
is_quarterly=False)
dv.add_formula('mask_limit_reached',
'limit_reached > 0',
is_quarterly=False)
dv.add_formula('mask_index_member',
'!(index_member > 0)',
is_quarterly=False)
trade_status = dv.get_ts('trade_status')
mask_sus = trade_status == u'停牌'
dv.append_df(mask_sus, 'mask_sus', is_quarterly=False)
# dv.add_formula('size', '', is_quarterly=False)
dv.save_dataview(dataview_folder)
def save_dataview():
ds = RemoteDataService()
ds.init_from_config(data_config)
dv = DataView()
props = {
'start_date': 20150101,
'end_date': 20170930,
'universe': '000905.SH',
'fields': ('turnover,float_mv,close_adj,pe,pb'),
'freq': 1
}
dv.init_from_config(props, ds)
dv.prepare_data()
factor_formula = 'Cutoff(Standardize(turnover / 10000 / float_mv), 2)'
dv.add_formula('TO', factor_formula, is_quarterly=False)
factor_formula = 'Cutoff(Standardize(1/pb), 2)'
dv.add_formula('BP', factor_formula, is_quarterly=False)
factor_formula = 'Cutoff(Standardize(Return(close_adj, 20)), 2)'
dv.add_formula('REVS20', factor_formula, is_quarterly=False)
factor_formula = 'Cutoff(Standardize(Log(float_mv)), 2)'
dv.add_formula('float_mv_factor', factor_formula, is_quarterly=False)
factor_formula = 'Delay(Return(close_adj, 1), -1)'
dv.add_formula('NextRet', factor_formula, is_quarterly=False)
dv.save_dataview(folder_path=dataview_dir_path)
def test_dataview_universe():
ds = RemoteDataService()
ds.init_from_config(data_config)
dv = DataView()
props = {
'start_date':
20170227,
'end_date':
20170327,
'universe':
'000016.SH',
# 'symbol': 'rb1710.SHF,rb1801.SHF',
'fields':
('open,high,low,close,vwap,volume,turnover,' + 'sw1,zz2,' +
'roe,net_assets,' + 'total_oper_rev,oper_exp,tot_profit,int_income'),
'freq':
1
}
dv.init_from_config(props, ds)
dv.prepare_data()
data_bench = dv.data_benchmark.copy()
dv.data_benchmark = data_bench
try:
dv.data_benchmark = data_bench.iloc[3:]
except ValueError:
pass
dv.remove_field('roe,net_assets')
dv.remove_field('close')
def test_write():
ds = RemoteDataService()
ds.init_from_config(data_config)
dv = DataView()
secs = '600030.SH,000063.SZ,000001.SZ'
props = {
'start_date': 20160601,
'end_date': 20170601,
'symbol': secs,
'fields': 'open,close,high,low,volume,pb,net_assets,pcf_ncf',
'freq': 1
}
dv.init_from_config(props, data_api=ds)
dv.prepare_data()
assert dv.data_d.shape == (281, 48)
assert dv.dates.shape == (281, )
# TODO
"""
PerformanceWarning:
your performance may suffer as PyTables will pickle object types that it cannot
map directly to c-types [inferred_type->mixed,key->block1_values] [items->[('000001.SZ', 'int_income'), ('000001.SZ', 'less_handling_chrg_comm_exp'), ('000001.SZ', 'net_int_income'), ('000001.SZ', 'oper_exp'), ('000001.SZ', 'symbol'), ('000063.SZ', 'int_income'), ('000063.SZ', 'less_handling_chrg_comm_exp'), ('000063.SZ', 'net_int_income'), ('000063.SZ', 'oper_exp'), ('000063.SZ', 'symbol'), ('600030.SH', 'int_income'), ('600030.SH', 'less_handling_chrg_comm_exp'), ('600030.SH', 'net_int_income'), ('600030.SH', 'oper_exp'), ('600030.SH', 'symbol')]]
"""
dv.save_dataview(folder_path=daily_path)
def test_livetrade():
props = {'symbol': 'rb1801.SHF', 'strategy_no': 46}
tapi = RealTimeTradeApi(trade_config)
ins = EventLiveTradeInstance()
props.update(data_config)
props.update(trade_config)
ds = RemoteDataService()
strat = DoubleMaStrategy()
pm = PortfolioManager()
context = model.Context(data_api=ds,
trade_api=tapi,
instance=ins,
strategy=strat,
pm=pm)
ins.init_from_config(props)
ds.subscribe(props['symbol'])
ins.run()
time.sleep(3)
ins.stop()
ins.save_results(result_dir_path)
do_analyze()
def save_data():
"""
This function fetches data from remote server and stores them locally.
Then we can use local data to do back-test.
"""
dataview_props = {# Start and end date of back-test
'start_date': 20170101, 'end_date': 20171030,
# Investment universe and performance benchmark
'universe': UNIVERSE, 'benchmark': '000300.SH',
# Data fields that we need
'fields': 'total_mv,turnover',
# freq = 1 means we use daily data. Please do not change this.
'freq': 1}
# RemoteDataService communicates with a remote server to fetch data
ds = RemoteDataService()
# Use username and password in data_config to login
ds.init_from_config(data_config)
# DataView utilizes RemoteDataService to get various data and store them
dv = DataView()
dv.init_from_config(dataview_props, ds)
dv.prepare_data()
dv.save_dataview(folder_path=dataview_store_folder)
def analyze():
ta = ana.EventAnalyzer()
ds = RemoteDataService()
ds.init_from_config(data_config)
ta.initialize(data_server_=ds, file_folder=result_dir_path)
ta.do_analyze(result_dir=result_dir_path, selected_sec=[])
def analyze():
ta = ana.EventAnalyzer()
ds = RemoteDataService()
ds.init_from_config(data_config)
ta.initialize(data_server_=ds, file_folder=result_dir_path)
ta.do_analyze(result_dir=result_dir_path, selected_sec=props['symbol'].split(','))
def run_strategy():
'''
universe可以自己定义吗，就是从我筛选的一组股票里面挑选
把universe改成symbol，然后值设置成一系列代码的字符串，用逗号隔开
:return:
'''
if is_backtest:
"""
回测模式
"""
props = {
"symbol": '600519.SH',
# "symbol": '002050.SZ',
# "benchmark": '002050.SZ',
"benchmark": '000300.SH',
"start_date": 20170101,
"end_date": 20171219,
"fast_ma_length": 3,
"slow_ma_length": 8,
"live_ma_length": 34,
"bar_type": "1d", # '1d'
"init_balance": 50000}
tapi = BacktestTradeApi()
ins = EventBacktestInstance()
else:
"""
实盘/仿真模式
"""
props = {'symbol': '600519.SH',
"fast_ma_length": 3,
"slow_ma_length": 5,
"live_ma_length": 34,
'strategy.no': 1062}
tapi = RealTimeTradeApi(trade_config)
ins = EventLiveTradeInstance()
props.update(data_config)
props.update(trade_config)
ds = RemoteDataService()
strat = TripleMaStrategy()
pm = PortfolioManager()
context = model.Context(data_api=ds, trade_api=tapi, instance=ins,
strategy=strat, pm=pm)
ins.init_from_config(props)
if not is_backtest:
ds.subscribe(props['symbol'])
ins.run()
if not is_backtest:
time.sleep(9999)
ins.save_results(folder_path=result_dir_path)
def test_add_field():
dv = DataView()
dv.load_dataview(folder_path=daily_path)
nrows, ncols = dv.data_d.shape
n_securities = len(dv.data_d.columns.levels[0])
ds = RemoteDataService()
ds.init_from_config(data_config)
dv.add_field('total_share', ds)
assert dv.data_d.shape == (nrows, ncols + 1 * n_securities)
def test_add_field():
dv = DataView()
dv.load_dataview(folder_path=daily_path)
nrows, ncols = dv.data_d.shape
n_securities = len(dv.data_d.columns.levels[0])
ds = RemoteDataService()
ds.init_from_config(data_config)
dv.add_field('total_share', ds)
assert dv.data_d.shape == (nrows, ncols + 1 * n_securities)
def test_bar():
from jaqs.data import RemoteDataService
from jaqs.trade.common import QUOTE_TYPE
ds = RemoteDataService()
ds.init_from_config(data_config)
df_quotes, msg = ds.bar(symbol='rb1710.SHF,hc1710.SHF', start_time=200000, end_time=160000,
trade_date=20170704, freq=QUOTE_TYPE.MIN)
bar_list = Bar.create_from_df(df_quotes)
bar = bar_list[0]
print(str(bar))
def test_inst_manager():
ds = RemoteDataService()
ds.init_from_config(data_config)
mgr = InstManager(ds)
mgr.load_instruments()
sym = '000001.SZ'
inst_obj = mgr.get_instrument(sym)
assert inst_obj.market == 'SZ'
assert inst_obj.symbol == sym
assert inst_obj.multiplier == 1
assert inst_obj.inst_type == 1
def test_inst_manager():
ds = RemoteDataService()
ds.init_from_config(data_config)
mgr = InstManager(ds)
mgr.load_instruments()
sym = '000001.SZ'
inst_obj = mgr.get_instrument(sym)
assert inst_obj.market == 'SZ'
assert inst_obj.symbol == sym
assert inst_obj.multiplier == 1
assert inst_obj.inst_type == 1
def test_bar():
from jaqs.data import RemoteDataService
from jaqs.trade.common import QUOTE_TYPE
ds = RemoteDataService()
ds.init_from_config(data_config)
df_quotes, msg = ds.bar(symbol='rb1710.SHF,hc1710.SHF',
start_time=200000,
end_time=160000,
trade_date=20170704,
freq=QUOTE_TYPE.MIN)
quotes_list = Bar.create_from_df(df_quotes)
def run_strategy():
if is_backtest:
"""
回测模式
"""
props = {
"symbol": '600519.SH',
"start_date": 20170101,
"end_date": 20171104,
"fast_ma_length": 5,
"slow_ma_length": 15,
"bar_type": "1d", # '1d'
"init_balance": 50000
}
tapi = BacktestTradeApi()
ins = EventBacktestInstance()
else:
"""
实盘/仿真模式
"""
props = {
'symbol': '600519.SH',
"fast_ma_length": 5,
"slow_ma_length": 15,
'strategy.no': 1062
}
tapi = RealTimeTradeApi(trade_config)
ins = EventLiveTradeInstance()
props.update(data_config)
props.update(trade_config)
ds = RemoteDataService()
strat = DoubleMaStrategy()
pm = PortfolioManager()
context = model.Context(data_api=ds,
trade_api=tapi,
instance=ins,
strategy=strat,
pm=pm)
ins.init_from_config(props)
if not is_backtest:
ds.subscribe(props['symbol'])
ins.run()
if not is_backtest:
time.sleep(9999)
ins.save_results(folder_path=result_dir_path)
def test_write_future():
ds = RemoteDataService()
ds.init_from_config(data_config)
dv = DataView()
secs = 'rb1710.SHF,j1710.DCE'
props = {'start_date': 20170401, 'end_date': 20170901, 'symbol': secs,
'fields': 'open,close,high,low,volume,oi',
'freq': 1, 'all_price': False}
dv.init_from_config(props, data_api=ds)
dv.prepare_data()
assert dv.data_d.shape == (145, 14)
def save_dataview():
ds = RemoteDataService()
ds.init_from_config(data_config)
dv = DataView()
props = {'start_date': 20160101, 'end_date': 20171001, 'universe': '000300.SH',
'fields': 'volume,turnover',
'freq': 1}
dv.init_from_config(props, ds)
dv.prepare_data()
dv.save_dataview(dataview_folder)
def test_save_dataview():
ds = RemoteDataService()
ds.init_from_config(data_config)
dv = DataView()
print(DataView)
props = {'start_date': 20170501, 'end_date': 20171001, 'universe': '000016.SH',
'fields': 'volume,pb,pe,ps,float_mv,sw1',
'freq': 1}
dv.init_from_config(props, ds)
dv.prepare_data()
dv.save_dataview(dataview_folder)
def test_q_add_field():
dv = DataView()
dv.load_dataview(folder_path=quarterly_path)
nrows, ncols = dv.data_q.shape
n_securities = len(dv.data_d.columns.levels[0])
ds = RemoteDataService()
ds.init_from_config(data_config)
dv.add_field('net_inc_other_ops', ds)
"""
dv.add_field('oper_rev', ds)
dv.add_field('turnover', ds)
"""
assert dv.data_q.shape == (nrows, ncols + 1 * n_securities)
def do_analyze():
from jaqs.trade.analyze.analyze import TradeRecordEmptyError
ta = ana.EventAnalyzer()
ds = RemoteDataService()
ds.init_from_config(data_config)
try:
ta.initialize(data_server_=ds, file_folder=result_dir_path)
ta.do_analyze(result_dir=result_dir_path, selected_sec=[])
except TradeRecordEmptyError:
pass
def test_add_formula_directly():
ds = RemoteDataService()
ds.init_from_config(data_config)
dv = DataView()
secs = '600030.SH,000063.SZ,000001.SZ'
props = {'start_date': 20160601, 'end_date': 20170601, 'symbol': secs,
'fields': 'open,close',
'freq': 1}
dv.init_from_config(props, data_api=ds)
dv.prepare_data()
dv.add_formula("myfactor", 'close / open', is_quarterly=False)
assert dv.data_d.shape == (281, 39)
def test_q_add_field():
dv = DataView()
dv.load_dataview(folder_path=quarterly_path)
nrows, ncols = dv.data_q.shape
n_securities = len(dv.data_d.columns.levels[0])
ds = RemoteDataService()
ds.init_from_config(data_config)
dv.add_field('net_inc_other_ops', ds)
"""
dv.add_field('oper_rev', ds)
dv.add_field('turnover', ds)
"""
assert dv.data_q.shape == (nrows, ncols + 1 * n_securities)
def test_align():
# -------------------------------------------------------------------------------------
# input and pre-process demo data
ds = RemoteDataService()
ds.init_from_config(data_config)
raw, msg = ds.query_lb_fin_stat('income', '600000.SH', 20151225, 20170501, 'oper_rev')
assert msg == '0,'
idx_list = ['report_date', 'symbol']
raw_idx = raw.set_index(idx_list)
raw_idx.sort_index(axis=0, level=idx_list, inplace=True)
df_ann = raw_idx.loc[pd.IndexSlice[:, :], 'ann_date']
df_ann = df_ann.unstack(level=1)
df_value = raw_idx.loc[pd.IndexSlice[:, :], 'oper_rev']
df_value = df_value.unstack(level=1)
date_arr = ds.query_trade_dates(20160101, 20170501)
df_close = pd.DataFrame(index=date_arr, columns=df_value.columns, data=1e3)
# -------------------------------------------------------------------------------------
# demo usage of parser
parser = Parser()
parser.register_function('Myfunc', lambda x: x * 0 + 1) # simultaneously test register function and align
expr_formula = 'signal / Myfunc(close)'
expression = parser.parse(expr_formula)
for i in range(100):
df_res = parser.evaluate({'signal': df_value, 'close': df_close}, df_ann, date_arr)
# -------------------------------------------------------------------------------------
sec = '600000.SH'
"""
# print to validate results
print "\n======Expression Formula:\n{:s}".format(expr_formula)
print "\n======Report date, ann_date and evaluation value:"
tmp = pd.concat([df_ann.loc[:, sec], df_value.loc[:, sec]], axis=1)
tmp.columns = ['df_ann', 'df_value']
print tmp
print "\n======Selection of result of expansion:"
print "20161028 {:.4f}".format(df_res.loc[20161028, sec])
print "20161031 {:.4f}".format(df_res.loc[20161031, sec])
print "20170427 {:.4f}".format(df_res.loc[20170427, sec])
"""
assert abs(df_res.loc[20161028, sec] - 82172000000) < 1
assert abs(df_res.loc[20161031, sec] - 120928000000) < 1
assert abs(df_res.loc[20170427, sec] - 42360000000) < 1
def do_analyze():
from jaqs.trade.analyze.analyze import TradeRecordEmptyError
ta = ana.EventAnalyzer()
ds = RemoteDataService()
ds.init_from_config(data_config)
try:
ta.initialize(data_server_=ds, file_folder=result_dir_path)
ta.do_analyze(result_dir=result_dir_path, selected_sec=[])
except TradeRecordEmptyError:
pass
def run_strategy():
"""
回测模式
"""
props = {"symbol": '510300.SH',
"start_date": 20160201,
"end_date": 20171231,
"fast_ma_length": 10,
"slow_ma_length": 20,
"bar_type": "1d",
"benchmark" : '000300.SH',
"init_balance": 50000}
tapi = BacktestTradeApi()
ins = EventBacktestInstance()
props.update(data_config)
props.update(trade_config)
ds = RemoteDataService()
strat = DoubleMaStrategy()
pm = PortfolioManager()
context = model.Context(data_api=ds, trade_api=tapi, instance=ins,
strategy=strat, pm=pm)
ins.init_from_config(props)
ins.run()
ins.save_results(folder_path=result_dir_path)
def test_backtest():
props = {
"symbol": "rb1710.SHF",
"start_date": 20170710,
"end_date": 20170730,
"bar_type": "1M", # '1d'
"init_balance": 2e4
}
tapi = BacktestTradeApi()
ins = EventBacktestInstance()
props.update(data_config)
props.update(trade_config)
ds = RemoteDataService()
strat = DoubleMaStrategy()
pm = PortfolioManager()
context = model.Context(data_api=ds,
trade_api=tapi,
instance=ins,
strategy=strat,
pm=pm)
ins.init_from_config(props)
ins.run()
ins.save_results(result_dir_path)
do_analyze()
def test_save_dataview():
ds = RemoteDataService()
ds.init_from_config(data_config)
dv = DataView()
props = {'start_date': 20170901, 'end_date': 20171129, 'universe': BENCHMARK,
'fields': 'close,volume,sw1',
'freq': 1}
dv.init_from_config(props, ds)
dv.prepare_data()
dv.add_formula('ret', 'Return(close_adj, 20)', is_quarterly=False)
dv.add_formula('rank_ret', 'Rank(ret)', is_quarterly=False)
dv.save_dataview(folder_path=dataview_dir_path)
def test_save_dataview():
ds = RemoteDataService()
ds.init_from_config(data_config)
dv = DataView()
props = {'start_date': 20170201, 'end_date': 20171001, 'universe': '000300.SH',
'fields': ('float_mv,sw2,sw1'),
'freq': 1}
dv.init_from_config(props, ds)
dv.prepare_data()
factor_formula = 'GroupQuantile(float_mv, sw1, 10)'
dv.add_formula('gq30', factor_formula, is_quarterly=False)
dv.save_dataview(folder_path=dataview_dir_path)
def do_livetrade():
dv = DataView()
dv.load_dataview(folder_path=dataview_store_folder)
props = {"period": "day", "strategy_no": 1044, "init_balance": 1e6}
props.update(data_config)
props.update(trade_config)
strategy = AlphaStrategy(pc_method='market_value_weight')
pm = PortfolioManager()
bt = AlphaLiveTradeInstance()
trade_api = RealTimeTradeApi(props)
ds = RemoteDataService()
context = model.Context(dataview=dv,
instance=bt,
strategy=strategy,
trade_api=trade_api,
pm=pm,
data_api=ds)
bt.init_from_config(props)
bt.run_alpha()
goal_positions = strategy.goal_positions
print("Length of goal positions:", len(goal_positions))
task_id, msg = trade_api.goal_portfolio(goal_positions)
print(task_id, msg)
def test_save_dataview():
ds = RemoteDataService()
ds.init_from_config(data_config)
dv = DataView()
props = {'start_date': 20170101, 'end_date': 20171001, 'universe': '000300.SH',
'fields': 'pe_ttm,net_profit_incl_min_int_inc',
'freq': 1}
dv.init_from_config(props, ds)
dv.prepare_data()
factor_formula = 'Return(net_profit_incl_min_int_inc, 4)'
factor_name = 'net_profit_growth'
dv.add_formula(factor_name, factor_formula, is_quarterly=True)
dv.save_dataview(folder_path=dataview_dir_path)
def download_data():
dataview_props = {
'start_date': 20080101,
'end_date': 20180731,
'universe': '000016.SH',
'fields': 'open,close,high,low',
'freq': 1
}
ds = RemoteDataService()
ds.init_from_config(data_config)
# DataView utilizes RemoteDataService to get various data and store them
dv = DataView()
dv.init_from_config(dataview_props, ds)
dv.prepare_data()
dv.save_dataview(folder_path=dataview_store_folder)
def save_data(self):
"""
This function fetches data from remote server and stores them locally.
Then we can use local data to do back-test.
"""
# RemoteDataService communicates with a remote server to fetch data
ds = RemoteDataService()
# Use username and password in data_config to login
ds.init_from_config(self.data_config)
# DataView utilizes RemoteDataService to get various data and store them
dv = DataView()
dv.init_from_config(self.dataview_props, ds)
dv.prepare_data()
dv.save_dataview(folder_path=self.dataview_store_folder)
def test_q():
ds = RemoteDataService()
ds.init_from_config(data_config)
dv = DataView()
secs = '600030.SH,000063.SZ,000001.SZ'
props = {'start_date': 20160609, 'end_date': 20170601, 'symbol': secs,
'fields': ('open,close,'
+ 'pb,net_assets,'
+ 'total_oper_rev,oper_exp,'
+ 'cash_paid_invest,'
+ 'capital_stk,'
+ 'roe'), 'freq': 1}
dv.init_from_config(props, data_api=ds)
dv.prepare_data()
dv.save_dataview(folder_path=quarterly_path)
def run_strategy():
if is_backtest:
"""
回测模式
"""
props = {"symbol": '600519.SH',
"start_date": 20170101,
"end_date": 20171104,
"fast_ma_length": 5,
"slow_ma_length": 15,
"bar_type": "1d", # '1d'
"init_balance": 50000}
tapi = BacktestTradeApi()
ins = EventBacktestInstance()
else:
"""
实盘/仿真模式
"""
props = {'symbol': '600519.SH',
"fast_ma_length": 5,
"slow_ma_length": 15,
'strategy.no': 1062}
tapi = RealTimeTradeApi(trade_config)
ins = EventLiveTradeInstance()
props.update(data_config)
props.update(trade_config)
ds = RemoteDataService()
strat = DoubleMaStrategy()
pm = PortfolioManager()
context = model.Context(data_api=ds, trade_api=tapi, instance=ins,
strategy=strat, pm=pm)
ins.init_from_config(props)
if not is_backtest:
ds.subscribe(props['symbol'])
ins.run()
if not is_backtest:
time.sleep(9999)
ins.save_results(folder_path=result_dir_path)
def run_strategy():
start_date = 20150501
end_date = 20171030
index = '399975.SZ'
ds = RemoteDataService()
ds.init_from_config(data_config)
symbol_list = ds.query_index_member(index, start_date, start_date)
# add the benchmark index to the last position of symbol_list
symbol_list.append(index)
props = {"symbol": ','.join(symbol_list),
"start_date": start_date,
"end_date": end_date,
"bar_type": "1d",
"init_balance": 1e7,
"std multiplier": 1.5,
"m": 10,
"n": 60,
"commission_rate": 2E-4}
props.update(data_config)
props.update(trade_config)
tapi = BacktestTradeApi()
ins = EventBacktestInstance()
strat = SectorRolling()
pm = PortfolioManager()
context = model.Context(data_api=ds, trade_api=tapi, instance=ins,
strategy=strat, pm=pm)
ins.init_from_config(props)
ins.run()
ins.save_results(folder_path=result_dir_path)
ta = ana.EventAnalyzer()
ta.initialize(data_server_=ds, file_folder=result_dir_path)
df_bench, _ = ds.daily(index, start_date=start_date, end_date=end_date)
ta.data_benchmark = df_bench.set_index('trade_date').loc[:, ['close']]
ta.do_analyze(result_dir=result_dir_path, selected_sec=props['symbol'].split(',')[:2])
def test_save_dataview(sub_folder='test_dataview'):
ds = RemoteDataService()
ds.init_from_config(data_config)
dv = DataView()
props = {'start_date': 20150101, 'end_date': 20170930, 'universe': '000905.SH',
'fields': ('float_mv,tot_shrhldr_eqy_excl_min_int,deferred_tax_assets,sw2'),
'freq': 1}
dv.init_from_config(props, ds)
dv.prepare_data()
factor_formula = 'Quantile(-float_mv,5)'
dv.add_formula('rank_mv', factor_formula, is_quarterly=False)
factor_formula = 'Quantile(float_mv/(tot_shrhldr_eqy_excl_min_int+deferred_tax_assets), 5)'
dv.add_formula('rank_pb', factor_formula, is_quarterly=False)
dv.save_dataview(folder_path=dataview_dir_path)
def save_dataview():
ds = RemoteDataService()
ds.init_from_config(data_config)
dv = DataView()
props = {'start_date': 20150101, 'end_date': 20171001, 'universe': '000300.SH',
'fields': 'volume,turnover,float_mv,pb,total_mv',
'freq': 1}
dv.init_from_config(props, ds)
dv.prepare_data()
trade_status = dv.get_ts('trade_status')
mask_sus = trade_status == '停牌'
dv.append_df(mask_sus, 'suspended', is_quarterly=False)
dv.add_formula('not_index_member', '!index_member', is_quarterly=False)
dv.add_formula('limit_reached', 'Abs((open - Delay(close, 1)) / Delay(close, 1)) > 0.095', is_quarterly=False)
dv.save_dataview(dataview_folder)
def test_write():
ds = RemoteDataService()
ds.init_from_config(data_config)
dv = DataView()
secs = '600030.SH,000063.SZ,000001.SZ'
props = {'start_date': 20160601, 'end_date': 20170601, 'symbol': secs,
'fields': 'open,close,high,low,volume,pb,net_assets,pcf_ncf',
'freq': 1}
dv.init_from_config(props, data_api=ds)
dv.prepare_data()
assert dv.data_d.shape == (281, 48)
assert dv.dates.shape == (281, )
# TODO
"""
PerformanceWarning:
your performance may suffer as PyTables will pickle object types that it cannot
map directly to c-types [inferred_type->mixed,key->block1_values] [items->[('000001.SZ', 'int_income'), ('000001.SZ', 'less_handling_chrg_comm_exp'), ('000001.SZ', 'net_int_income'), ('000001.SZ', 'oper_exp'), ('000001.SZ', 'symbol'), ('000063.SZ', 'int_income'), ('000063.SZ', 'less_handling_chrg_comm_exp'), ('000063.SZ', 'net_int_income'), ('000063.SZ', 'oper_exp'), ('000063.SZ', 'symbol'), ('600030.SH', 'int_income'), ('600030.SH', 'less_handling_chrg_comm_exp'), ('600030.SH', 'net_int_income'), ('600030.SH', 'oper_exp'), ('600030.SH', 'symbol')]]
"""
dv.save_dataview(folder_path=daily_path)
def test_save_dataview():
ds = RemoteDataService()
ds.init_from_config(data_config)
dv = DataView()
props = {'start_date': 20170101, 'end_date': 20171001, 'universe': '000300.SH',
'fields': ('float_mv,pb,pe_ttm,sw2'),
'freq': 1}
dv.init_from_config(props, ds)
dv.prepare_data()
factor_formula = 'GroupQuantile(-float_mv, sw2, 10)'
dv.add_formula('rank_mv', factor_formula, is_quarterly=False)
factor_formula = 'GroupQuantile(If(pb >= 0.2, pb, 100), sw2, 10)'
dv.add_formula('rank_pb', factor_formula, is_quarterly=False)
factor_formula = 'GroupQuantile(If(pe_ttm >= 3, pe_ttm, 9999.0), sw2, 10)'
dv.add_formula('rank_pe', factor_formula, is_quarterly=False)
dv.save_dataview(folder_path=dataview_dir_path)
def test_calendar():
ds = RemoteDataService()
ds.init_from_config(data_config)
res1 = ds.query_trade_dates(20121224, 20130201)
assert len(res1) == 27
day_zero = 20170102
res2 = ds.query_next_trade_date(day_zero)
assert res2 == 20170103
res2_last = ds.query_last_trade_date(res2)
assert res2_last == 20161230
res3 = ds.query_next_trade_date(20170104)
assert res3 == 20170105
res4 = ds.query_last_trade_date(res3)
assert res4 == 20170104
res11 = ds.query_trade_dates(20161224, 20170201)
assert len(res11) == 23
assert not ds.is_trade_date(20150101)
assert not ds.is_trade_date(20130501)
def test_livetrade():
props = {'symbol': 'rb1801.SHF',
'strategy_no': 1044}
tapi = RealTimeTradeApi(trade_config)
ins = EventLiveTradeInstance()
props.update(data_config)
props.update(trade_config)
ds = RemoteDataService()
strat = DoubleMaStrategy()
pm = PortfolioManager()
context = model.Context(data_api=ds, trade_api=tapi, instance=ins,
strategy=strat, pm=pm)
ins.init_from_config(props)
ds.subscribe(props['symbol'])
ins.run()
time.sleep(3)
ins.stop()
ins.save_results(result_dir_path)
do_analyze()
def my_globals(request):
ds = RemoteDataService()
ds.init_from_config(data_config)
request.function.__globals__.update({'ds': ds})
raise exc
'''
@pytest.fixture(autouse=True)
def my_globals(request):
ds = RemoteDataService()
ds.init_from_config(data_config)
request.function.__globals__.update({'ds': ds})
if __name__ == "__main__":
import time
t_start = time.time()
ds = RemoteDataService()
ds.init_from_config(data_config)
g = globals()
g = {k: v for k, v in g.items() if k.startswith('test_') and callable(v)}
for test_name, test_func in g.items():
print("\n==========\nTesting {:s}...".format(test_name))
test_func()
print("Test Complete.")
t3 = time.time() - t_start
print("\n\n\nTime lapsed in total: {:.1f}".format(t3))
