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 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_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 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()
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 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_alpha_strategy_dataview():
dv = DataView()
dv.load_dataview(folder_path=dataview_dir_path)
props = {
"benchmark": BENCHMARK,
"universe": ','.join(dv.symbol),
"start_date": dv.start_date,
"end_date": dv.end_date,
"period": "day",
"days_delay": 0,
"init_balance": 1e8,
"position_ratio": 1.0,
"strategy_no": 44
}
props.update(data_config)
props.update(trade_config)
stock_selector = model.StockSelector()
stock_selector.add_filter(name='rank_ret_top10', func=my_selector)
strategy = AlphaStrategy(stock_selector=stock_selector,
pc_method='equal_weight')
pm = PortfolioManager()
if is_backtest:
bt = AlphaBacktestInstance()
trade_api = AlphaTradeApi()
ds = None
else:
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)
stock_selector.register_context(context)
bt.init_from_config(props)
bt.run_alpha()
if is_backtest:
bt.save_results(folder_path=backtest_result_dir_path)
else:
goal_positions = strategy.goal_positions
print(goal_positions)
def do_livetrade():
dv = DataView()
dv.load_dataview(folder_path=dataview_store_folder)
# print("total_mv", dv.get_ts('total_mv'))
# print("float_mv", dv.get_ts('float_mv'))
props = {"period": "day", "strategy_no": 1683, "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)
trade_api.set_ordstatus_callback(on_orderstatus)
trade_api.set_trade_callback(on_trade)
trade_api.set_task_callback(on_taskstatus)
bt.init_from_config(props)
bt.run_alpha()
goal_positions = strategy.goal_positions
# print("strategy.weights", strategy.weights)
# print("Length of goal positions:", len(goal_positions))
# print(goal_positions)
task_id, msg = trade_api.goal_portfolio(goal_positions)
print(task_id, msg)
def run_strategy():
if is_backtest:
props = {
"symbol": "rb1710.SHF",
"start_date": 20170510,
"end_date": 20170930,
"bar_type": "1M", # '1d'
"init_balance": 2e4
}
tapi = BacktestTradeApi()
ins = EventBacktestInstance()
else:
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)
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():
if is_backtest:
"""
回测模式
"""
ds = RemoteDataService()
ds.init_from_config(data_config)
symbol_list = ds.query_index_member(index, start_date, end_date)
# symbol_list = ['600887.SH']
# symbol_list = sample(symbol_list, 20)
print(symbol_list)
# add the benchmark index to the last position of symbol_list
symbol_list.append(index)
props = {"symbol": ','.join(symbol_list),
"holding_Count": 15,
"start_date": start_date,
"end_date": end_date,
"bar_type": "1d", # '1d'
"init_balance": 300000,
"commission_rate": 2E-4}
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 = RNNStrategy()
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)
ta = ana.EventAnalyzer()
ds = RemoteDataService()
ds.init_from_config(data_config)
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']]
temp = pd.read_csv(result_dir_path + '/trades.csv')
symbols = set(temp['symbol'].unique())
print(symbols)
ta.do_analyze(result_dir=result_dir_path, selected_sec=list(symbols))