本文整理汇总了Python中mewp.simulate.report.Report.get_final_pnl方法的典型用法代码示例。如果您正苦于以下问题:Python Report.get_final_pnl方法的具体用法?Python Report.get_final_pnl怎么用?Python Report.get_final_pnl使用的例子?那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类mewp.simulate.report.Report
的用法示例。
在下文中一共展示了Report.get_final_pnl方法的2个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: run_simulation
# 需要导入模块: from mewp.simulate.report import Report [as 别名]
# 或者: from mewp.simulate.report.Report import get_final_pnl [as 别名]
def run_simulation(params):
date = '2015-01-01'
dateend = '2015-05-01'
ma_diff = []
dates = [str(x).split(' ')[0] for x in pd.date_range(date, dateend).tolist()]
algo = { 'class': MyMM }
temp = {'item': 'au1506'}
temp['ma_diff_length'] = params[0]
temp['trigger_diff'] = params[1]
temp['ma_window'] = params[2]
temp['spread'] = params[3]
temp['inv_coef'] = params[4]
temp['chunk'] = params[5]
temp['gap'] = params[6]
algo['param'] = temp
settings = { 'date': dates, 'algo': algo, 'tickset': 'top', 'verbose' : True,
'path': DATA_PATH }
runner = SingleRunner(settings)
runner.run()
report = Report(runner)
pnl = report.get_final_pnl()
sharp_ratio = report.get_sharpie_ratio()
del runner._algo.volatility_finder
del runner._algo
runner.close()
del runner._me
del runner._price_table
del runner
return pnl, sharp_ratio
示例2: run_simulation
# 需要导入模块: from mewp.simulate.report import Report [as 别名]
# 或者: from mewp.simulate.report.Report import get_final_pnl [as 别名]
def run_simulation(p):
runner.run(algo_param={'rolling': p[0], 'bollinger': p[1], 'stop_win': p[2]})
report = Report(runner)
runner._algo.tracker.order_winning_ratio()
pnl = float(report.get_final_pnl())
final_return = float(report.get_final_return())
sharpe_ratio = float(report.get_sharpie_ratio())
avg_draw_down = float(report.get_avg_max_draw_down())
max_draw_down = float(report.get_max_max_draw_down()[0])
order_winning_ratio = float(runner._algo.tracker.order_winning_ratio())
waiting_time = float(runner._algo.tracker.analyze_all_waiting()[0])
avg_profit = float(runner._algo.tracker.analyze_all_profit()[0])
num_orders = int(runner._algo.tracker.analyze_all_profit()[2])
return pnl, final_return, sharpe_ratio, avg_draw_down, max_draw_down, \
order_winning_ratio, waiting_time, avg_profit, num_orders