Esempio n. 1
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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=[])
Esempio n. 2
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def analyze():
    ta = ana.EventAnalyzer()
    
    dv = EventDataView()
    dv.load_dataview(dataview_dir_path)
    ta.initialize(dataview=dv,
                  file_folder=result_dir_path)
    
    ta.do_analyze(result_dir=result_dir_path, selected_sec=backtest_props['symbol'].split(','))
Esempio n. 3
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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
Esempio n. 4
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def run_strategy():

    start_date = 20150501
    end_date = 20171030
    index = '399975.SZ'

    ds = RemoteDataService()
    ds.init_from_config(data_config)
    symbol_list = ds.get_index_comp(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])
Esempio n. 5
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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))